+1 (208) 254-6996 essayswallet@gmail.com

For this second assignment, you will analyze current research to support your evidence-based intervention project.

Use the “Reviewing the Literature” worksheet to complete this two-part assignment. For Part 1, the Literature Evaluation Table, you will locate and organize information from 10-12 peer-reviewed articles for your literature review. In Part 2, the Literature Analysis, you will analyze the articles you selected and write a review of the literature. Use the information from your Literature Evaluation Table to ensure the inclusion of key information in your narrative.

The Problem of Debt and Geriatric Physical Therapy David B. Gillette, PT, DPT; Todd E. Davenport, PT, DPT; Alicia Rabena-Amen, PT, DPT

The cost of higher education con­ tinues to rise: student loan debt has pro­ gressively become a greater concern. In the United States, the price of a public and private non-profit “4-year” (under­ graduate) college degree has increased at a rate much greater than predicted by inflation.1 An analysis of self-reported student loan debt from a cohort of graduating college seniors in 2015 indi­ cated almost 70% of graduates reported a debt balance that averaged a record value of $30,100; almost 20% of the debt “was in private (nonfederal) loans” that tends to be associated with higher costs and fewer protections.2 In 2012, those graduating with a doctoral degree in professional practice had $120,000 or more in cumulative student loan debt.3


Student loan debt greatly affects the individual borrower. Student loan debt correlates with subjective well-be­ ing,4 mental health,5,6 and substance use disorders.7 Student loan debt is also associated with life choices including living with parents,8 formation of their own family (getting married9 or hav­ ing children10), saving for the future, and availability of discretionary spend­ ing.11 Increased overall debt can have a negative impact on physical and mental health, including stress, depression, and high blood pressure.12

Student loan debt can affect the profession through the borrower. Stu­ dent loan debt is known to associate with career choices, including complet­ ing further training for pharmacists13 and nurses,14 reducing likelihood of specialization for dentists,15 and influ­ encing the choice of specialty for medi­ cal school graduates.10,16’18 Thus, the issue of student loan debt has great relevance to the financial, physical, and psychological well-being among gradu­ ating students, and the potential future of the profession. Most of the data available are for undergraduate students and medical students, so trends and po­

tential impacts on physical therapists of their educational costs remains unclear.

Many health professions in the United States, including physical ther­ apy, require a graduate degree for licen­ sure. The process of professionalization in physical therapy has involved an increase in level of the first professional degree required to enter the field and obtain licensure to a professional doc­ torate. Additional education up to 3 to 4 years post baccalaureate are required to accommodate the Doctor of Physical Therapy degree. This increased training time represents more direct and indirect costs of education to students. Direct costs include tuition and fees associated with the educational experience. Indi­ rect costs include living expenses and lost time for remunerative employment. Thus, although surveys specifically re­ lated to United States physical therapy education have not been conducted over time, it seems reasonable that increased training costs also may have resulted in an increased accumulation of stu­ dent debt among practicing physical therapists. Physical therapy graduate education is largely self-funded through savings, limited work, and loans.

Because physical therapy graduate education is self-funded through savings and loans, there may be a correlation between the cost of education and stu­ dent debt. Understanding the cost of physical therapy education helps to un­ derstand the debt burden in the profes­ sion, with potential impact on not only graduates but the profession as a whole. Graduates may experience physical and mental health ramifications, may make decisions of where to practice based on salary,11 and may choose not to pursue further training such as residencies or research doctorates. Additionally, there are indications that new graduates in physical therapy may be overleveraged with educational debt too high for the salary of a new graduate.19 This may impact the profession by creating areas of practice either in specialty or geogra­ phy with a dearth of physical therapists,

reducing the number of residency or fel­ lowship trained therapists, and reducing the number of research therapists even further, weakening academic institutions and progress in rehabilitation research.


To understand the concern of stu­ dent debt and geriatric physical therapy, one should look at the historical trends of 3 things in relation to the Consumer Price Index (CPI): tuition, salary, and Medicare expenditures (Table 1). The CPI records the price paid for various goods and services and is used to cal­ culate inflation. We took the value for each September starting in 2009.20

Students have limited opportunity to work during school. Funding must come through savings or loans, so tu­ ition could be viewed as a proxy for the estimate of student debt. Using CAPTE’s annual reports since 2009 when 86% of the programs were award­ ing the DPT,21’23 it can be observed that tuition has increased annually for both public and private institutions.

In looking at the historical data of the salary of physical therapists during the same time period, the assumption was made that the 10th percentile is a new grad, 25th is a new professional, and mean is the mid-career salary.19 Comparing these annual changes to the change in tuition, one can see that salary is not rising as quickly as tuition.24

Geriatric physical therapy is in all settings – acute, skilled nursing, home health, and outpatient. What is con­ sistent is the payor source-Medicare. However rules, diagnosis codes, and payment criteria change every year, which creates a challenge when trying to collect historical data. No studies have been conducted to look at the changes in payment for physical therapy services across multiple settings. It would be a fair assumption however to say that the relative amount that physical therapy receives as a whole for Medicare expen­ ditures has not significantly increased. Historical data for Medicare expendi-

26 GeriNotes, Vol. 26, No. 2 2019

Table 1. Table 2.

Education Cost, Salary, Medicare Expenditure, and CPI







* v / *

s – 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018

• ‘ Total Cost: Public $34,979 $39,082 $45,750 $50,294 $55,997 $48,135 $59,210 $60,627

…. .. Total Cost: Private $84,564 $85,289 S85.289 $94,251 $99,797 $105,229 $105,857 $109,099

«h > mm Salary: 10th percentile $53,620 $54,710 $55,620 $56,280 $56,800 $57,060 $58,190 S59.080

Salary: 25th percentile $64,230 $65,860 $66,950 $67,700 $68,690 $69,620 $70,680 $71,670

$77,990 $79,830 $81,110 $82,180 $83,940 $85,790 $87,220 $88,080

* Medicare per enrollee expenditure $11,146 $11,442 S11,462 $11,514 $11,702 $11,904 $12,046

— – CPI (Sept) 215.861 218.275 226.597 231.015 233.544 237.452 237.467 241.017 246.392

“Tota l Cost: Public

‘ Salary: 10th percentile

‘ Salary: Mean

•CPI (Sept)

“•■To ta l Cost: Private

Salary: 25th percentile

‘ ” Medicare per enrollee expenditure

tures per person was examined; that has increased at a slower rate than salaries during this same timeframe.25,26


When all these changes to the CPI are compared as a measure of inflation, there are several disconcerting observa­ tions that can be made when looking at the annual rate of growth (Table 2). First, salaries are not keeping up with the rise in tuition. If students are taking on the majority of their tuition as loans, this can become a problem where they become overleveraged in debt.19,27

Second, Medicare expenditures are not keeping up with salaries. If physical therapy reimbursement is keeping steady as a percentage of Medicare expen­ ditures, this will increase productivity pressures to keep company profits and salaries up. This may lead to increased burnout of new graduates. Third, sala­ ries are also not keeping up with infla­ tion. This is a concern not just for the student or new graduate, but also for the profession.

Rising student debt among early ca­ reer physical therapists eventually could limit participation in residency, fellow­ ship, and research training programs in

geriatric, neurologic, orthopedic, and other areas of physical therapy. In turn, there will be fewer clinical specialists available to serve patients and train new specialists. In addition, there may be future adverse effects of physical therapy education total program costs on the number of rehabilitation scientists who can inform geriatric physical therapy practice.

Taken together, these observations raise several concerns. First, the current trend of tuition in relation to salaries, re­ imbursement, and the CPI is unsustain­ able for individuals and the profession. Second, post-graduate training opportu­ nities only will be accessible to physical therapists who can afford them, which also could lower the representation of physical therapists from economically disadvantaged backgrounds in clinical specialist roles and the academe.

WHAT WE CAN DO Advocate: be involved with the

American Physical Therapy Association, and contact your legislators with the Action Center when called upon about reimbursement. This will not fix the problem as debt is rising too faster, but it can help.

Financial markers Annual rate of growth, 2009-2016

Consumer Price Index


Public cost 5.50%

Private cost 3.70%

Salary – 10th 1.40%

Salary – 25th 1.60%

Salary – mean 1.90%

Medicare expenditure 1.30%

Be fiscally responsible. As a stu­ dent, limit your use of credit and stick to a budget, and use any resources or assistance your program may have. As a physical therapist, diligently pay off your student loans. See if your employer has an assistance program. Both students and licensed therapists should call on the American Physical Therapy Associa­ tion and its components, including the Academy of Geriatric Physical Therapy, to assist their membership in seeking and obtaining debt management and financial counseling services, in order to maintain optimal financial health.

Call on the American Physical Therapy Association and physical ther­ apy education programs to examine not only the efficacy of their educational modalities, but also their cost effective­ ness. There is a great diversity in the length and nature of physical therapy education programs, which primarily appears driven by judgments of face va­ lidity. It is time for physical therapy educators to weigh the costs of their educational modalities to students with their effectiveness. Perhaps even more importantly, administrators in charge of setting physical therapy tuition and fees should consider the cost burdens with regard to managing student debt following graduation, in addition to the relative size and competitiveness of applicant pools. Universities should consider if continuing to increase the cost per credit is responsible and sustain­ able, particularly as programs have been lengthened to accommodate the doctor­ al degree. Programs need to decide if it truly is in their best long-term interest to continue leveraging supply and demand economics to achieve increasing profits

GeriNotes, Vol. 26, No. 2 2019 27

considering the detrimental effects on our profession discussed above.

As indicated earlier, there is no systematic survey of student loan debt in physical therapy. Other professional organizations, such as the American Psy­ chological Association, conduct periodic surveys of graduate students to measure the financial health of their profession­ als. The American Physical Therapy Association and its components should develop a similar mechanism to sur­ vey student physical therapists, physical therapist graduates, and practicing clini­ cians at various time points. Potential variables of interest to measure would be the amount of student loan debt; the originator, guarantor, and servicer of student loan debt; income, affect, and mental health related to debt manage­ ment; and career choices related to debt management. Analyses from these data would allow for a deeper discussion of the potential issues facing physical thera­ pists as they relate to paying for their training costs.

REFERENCES 1. National Center for Education

Statistics. Fast Facts – Tuition costs of colleges and universities. https://nces.ed.gov/fastfacts/dis- play.asp?id=76. Accessed December 7, 2018.

2. The Institute for College Access and success, student debt and the class of 2015. 11th Annual Report. Oc­ tober 2016. https://ticas.org/sites/ default/files/pub_files/classof2015. pdf._Accessed December 7, 2018.

3. The College Board. Trends in high­ er education: cumulative debt for undergraduate and graduate studies over time. https://trends.colleg- eboard.org/student-aid/figures-ta- bles/cumulative-debt-undergradu- ate-graduate-studies-time,. Accessed December 7, 2018.

4. Tay L, Batz C, Parrigon S, Kuyk­ endall L. Debt and subjective well­ being: the other side of the income- happiness coin. / Happiness Stud. 2017; 18(3):903-937.

5. Walsemann KM, Gee GC, Gentile D. Sick of our loans: Student bor­ rowing and the mental health of young adults in the United States. SocSci Med. 2015;124:85-93. doi: 10.1016/j.socscimed.2014.11.027.

6. Richardson T, Elliott P, Rob­ erts R, Jansen M. A longitudinal

study of financial difficulties and mental health in a national sam­ ple of British undergraduate stu­ dents. Community Ment Health J. 2017;53(3):344-352. doi: 10.1007/ s i0597-016-0052-0. Epub 2016 Jul 29.

7. Jackson ER, Shanafelt TD, Hasan O, Satele DV, Dyrbye LN. Burn­ out and alcohol abuse/dependence among U.S. medical students. Aca­ demic Medicine. 2016;91(9):1251- 1256.

8. Houle JN, Warner C. Into the red and back to the nest? Stu­ dent debt, college completion, and returning to the parental home among young adults. So- ciolEduc. 2017;90(1):89-108. doi: 1 0 .1 1 7 7 /0 0 3 8 0 4 0 7 1 6 6 8 5 8 7 3 . Epub 2017 Jan 5.

9. Addo FR. Debt, cohabitation, and marriage in young adulthood. De­ mography. 2014;51 (5): 1677-1701. doi: 10.1007/s 13524-014-0333-6.

10. Rohlfing J, Navarro R, Maniya OZ, Hughes BD, Rogalsky DK. Medical student debt and major life choices other than specialty. Med Educ Online. 2014;19(1):25603. doi: 10.3402/meo.vl9.25603.

11. Thompson K, Coon J, Handford L. Financing physical therapy doc­ toral education: methods used by entry-level students and the finan­ cial impact after graduation. J Allied Health. 2011 ;40(4): 169-173.

12. Sweet E, Nandi A, Adam EK, Mc- Dade TW. The high price of debt: household financial debt and its im­ pact on mental and physical health. Soc Sci Med. 2013;91:94-100. doi: 10.1016/j.socscimed.2013.05.009. Epub 2013 May 16

13. Hammond DA, Oyler DR, Devlin, JW, et al. Perceived motivating fac­ tors and barriers for the completion of postgraduate training among American pharmacy students prior to beginning advanced pharmacy practice experiences. Am J Pharm Educ. 2017;81(5):90.

14. Jones-Schenk J, Leafman J, Wallace L, Allen P. Addressing the cost, val­ ue, and student debt in nursing ed­ ucation. Nurs Econ. 2017;35( 1):7- 13, 29.

15. Nicholson S, Vujicic M, Wancheck T, Ziebert A, Menezes A. The ef­ fect of education debt on dentists’

career decisions. J Am Dent Assoc. 2015;l46(ll):800-807.

16. Rosenblatt RA, Andrilla CH. The impact of U.S. medical students’ debt on their choice of primary care careers: an analysis of data from the 2002 medical school gradu­ ation questionnaire. Acad Med. 2005;80(9):815-819.

17. Phillips JP, Weismantel DP, Gold KJ, Schwenk TL. Medical stu­ dent debt and primary care spe­ cialty intentions. Fam Med. 2010;42(9):616-622.

18. Phillips JP, Petterson SM, Bazemore AW, Phillips RL. A retrospective analysis of the relationship between medical student debt and primary care practice in the United States. Ann Fam Med. 2014;12:542-549.

19. Pabian PS, King KP, Tippett S. Stu­ dent debt in professional doctoral health care disciplines. J Phys Ther Educ. 2018;32(2): 159-168.

20. United States Department of Labor, Bureau of Labor Statistics. Con­ sumer Price Index. https://www. bls.gov/cpi/data.htm. Accessed De­ cember 7, 2018.

21. Commission on Accreditation in Physical Therapy Education (CAPTE). 2011-2012 Fact Sheet – Physical Therapist Education Pro­ grams. http://www.capteonline.org/ uploadedFiles/CAPTEorg/About_ C A PT E /R esources/A ggregate_ Program_Data/Archived_Aggre- gate_Program_Data/CAPTEPTAg- gregateData_2012.pdf . Accessed December 7, 2018. “CAPTE bears no responsibility for interpretations presented or conclusions reached based on analysis of the data.”

22. Commission on Accreditation in Physical Therapy Education (CAPTE). Aggregate program data 2 0 1 5 -2 0 1 6 physical therapist edu­ cation programs fact sheets, http:// w w w .capteonline.org/uploaded- Files/CAPTEorg/About_CAPTE/ Resources/Aggregate_Program _ D ata/A rchived_A ggregate_Pro- gram_Data/PTAggregateData2016. pdf . Accessed December 7, 2018. “CAPTE bears no responsibility for interpretations presented or conclu­ sions reached based on analysis of the data.”

23. Commission on Accreditation in Physical Therapy Education (CAPTE). Aggregate program data 2 0 1 7-2018 physical therapist edu-

28 GeriNotes, Vol. 26, No. 2 2019https://nces.ed.gov/fastfacts/dis-play.asp?id=76https://nces.ed.gov/fastfacts/dis-play.asp?id=76https://ticas.org/sites/https://trends.colleg-eboard.org/student-aid/figures-ta-bles/cumulative-debt-undergradu-ate-graduate-studies-timehttps://trends.colleg-eboard.org/student-aid/figures-ta-bles/cumulative-debt-undergradu-ate-graduate-studies-timehttps://trends.colleg-eboard.org/student-aid/figures-ta-bles/cumulative-debt-undergradu-ate-graduate-studies-timehttps://trends.colleg-eboard.org/student-aid/figures-ta-bles/cumulative-debt-undergradu-ate-graduate-studies-timehttps://wwwhttp://www.capteonline.org/http://www.capteonline.org/uploaded-Files/CAPTEorg/About_CAPTE/http://www.capteonline.org/uploaded-Files/CAPTEorg/About_CAPTE/

cation programs fact sheets, http:// w w w .capteonline.org/uploaded- Files/CAPTEorg/About_CAPTE/ Resources/A ggregate_Program _ Data/AggregateProgramData_PT- Programs.pdf. Accessed December 7, 2018. “CAPTE bears no respon­ sibility for interpretations presented or conclusions reached based on analysis of the data.”

24. United States Department of Labor Bureau of Labor Statistics. Oc­ cupational employment statistics. h ttps://w w w .bls.gov/oes/tab les. htm. Accessed December 7, 2018.

25. Martin AB, Hartman M, Washing­ ton B, Catlin A, National Health Expenditure Accounts Team. Na­ tional health spending: faster growth in 2015 as coverage expands and utilization increases. Health A ff (Millwood). 2 0 17;36(1): 166-176. doi: 10.1377/hlthaff.2016.1330. Epub 2016 Dec 2.

26. Hartman M, Martin AB, Espi­ nosa N, Catlin A, National Health Expenditure Accounts Team. Na­ tional health care spending in

American Geriatrics Society Unveils Beers Criteria for Potentially Inappropriate Medication Use in Older Adults

With more than 90% of older people using at least one prescription and more than 66% using 3 or more in any given month, the AGS Beers Criteria®— a compendium of medications potentially to avoid or consider with caution

because they often present an unfavorable balance of benefits and harms for older people— plays a vital role in helping health professionals, older adults, and caregivers work together to ensure medications are appropriate.

Read more at https://www.americangeriatrics.org/media-center/news/older-people- medications-are-common-updated-ags-beers-criteriar-aims-make-sure

PDPM and PDGM Resources A new MLN Matters Article MM 11081 on Home Health Patient-Driven Groupings M odel (PDGM)—

Spilt Implementation is available. Learn about the payment reform requirements.

A new MLN Matters Article M M 11152 on Implementation o f the Skilled Nursing Facility (SNF) Patient Driven Payment M odel (PDPM) is available. Learn about the required changes.

A New SNF PD PM Webinar Recording is Now Available An Overview of the Skilled Nursing Facility Patient-Driven Payment Model

webinar is now available at http://apta.adobeconnect.com/pch0i3flszlw/ The webinar was put together by the Post-Acute Care Educational Collaborative and was done by AGPT and

HPA members along with APTA staff. The webinar recording is open to all members and non-members.

CMS has a PDPM webpage at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM.html

2016: spending and enrollment growth slow after initial coverage expansions. Health A ff (Millwood). 2018;37(1): 150-160.

27. Shields RK, Dudley-Javoroski S. Physiotherapy education is a good financial investment, up to a cer­ tain level of student debt: an inter­ professional economic analysis. J Physiother. 2018;64(3):183-191. doi: 10.10 l6/j.jphys.2018.05.009. Epub 2018 Jun 15.

David Gillette, PT, DPT, GCS, is an Assistant Profes­ sor at University of the Pacific where he teaches several class­ es including geriat- rics. Dr. Gillette is

a board certified clinical specialist in geriatric physical therapy. He has had experience in skilled nursing and outpa­ tient care, and is now seeing patients in the home.

Todd E. Davenport, PT, DPT, MPH, OCS, is Professor and Program Direc­ tor with the Depart­ ment of Physical Therapy at Univer­ sity of the Pacific in

Stockton, California. Dr. Davenport is a board certified clinical specialist in orthopaedic physical therapy.

Alicia Rabena- Amen, PT, DPT, is an Assistant Profes­ sor and the Director of Clinical Educa­ tion for the Depart­ ment of Physical Therapy at the Uni­

versity of the Pacific in Stockton, Cali­ fornia. Dr. Rabena-Amen also serves as a board member to the Physical Therapy Board of California, as well as a volun­ teer for the Federation of State Boards of Physical Therapy.

* r –

■* .r f


GeriNotes, Vol. 26, No. 2 2019 29http://www.capteonline.org/uploaded-Files/CAPTEorg/About_CAPTE/http://www.capteonline.org/uploaded-Files/CAPTEorg/About_CAPTE/https://www.bls.gov/oes/tableshttps://www.americangeriatrics.org/media-center/news/older-people-medications-are-common-updated-ags-beers-criteriar-aims-make-surehttps://www.americangeriatrics.org/media-center/news/older-people-medications-are-common-updated-ags-beers-criteriar-aims-make-surehttp://apta.adobeconnect.com/pch0i3flszlw/https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM.html

Copyright of GeriNotes is the property of Academy of Geriatric Physical Therapy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.

5GeriNotes, Vol. 20, No. 2 2013



R ‘S M



When it comes right down to it, we are in a service industry. I had the opportunity recently to spend some time as a clinical mentor to a sales and

marketing group who work to increase referrals to rehabilitation professionals through physician outreach. We talked about why physicians should refer to physical therapy (PT), and about what PT has to offer older adults with some of the most common impairments and chronic conditions. However, I think maybe I got the most out of the meet- ing, because it jolted my neurons out of their usual pathways and got me think- ing about something new. I have spent a lot of time thinking about regulatory affairs lately, with all of the impending Medicare changes: the therapy cap, the Manual Medical Review process, the looming Multiple Procedure Payment Reduction. Clearly the reimbursement system for those of us treating older adults is going to continue to pose chal- lenges to providing clinically excellent care. And these proposed reductions and restrictions are coming into effect in the midst of a major change in who the “older adult” is. The boomers who are becoming Medicare eligible every day are vastly different than the older adults that most of us have treated thus far in our careers in geriatric therapy. These new older adults are super active, and they are going to need therapy for reasons that would make a Medicare auditor’s stomach turn. Imagine trying to find the medical necessity in the abil- ity to walk 18 holes or run a marathon. Anyway, I am going somewhere with all of this. It got me thinking about the likelihood that all of us will need to be- come better sales people ourselves, if we want to continue making a living doing what we love. We will need to convince

insurers that our services impact cost in a positive way (even cut costs through proactive health care) and are worth reimbursing, and convince our patients that what we have to offer is worth writing a check when the insurance company won’t.

I recently read an interview with Lois Vitt, PhD, Founding Director of the Institute for Socio-Financial Studies, who explained that most people fall into one of 4 categories in relation to what they find valuable: Personal-values peo- ple, social-values people, physical-values people, and financial-values people. By looking at what makes each type tick, maybe we can find some insight into how to promote the services we offer:

The personal-values person is the type who is happiest spending on self… the type with custom golf clubs or a closet full of shoes. I think the pitch here is pretty easy. The health and wellness we can deliver is unmatched. Heck, a great exercise prescription can keep you out of the hospital or get you into your skinny jeans! I know patients who started PT after an illness or injury and continued to pay privately long after insurance ben- efits were exhausted, because they loved the way they felt and looked after regular sessions with their physical therapist.

The social-values person is most likely to buy for others. This could ap- ply to our services in a couple of ways. First, when discussing paying for ser- vices with an older adult, we may face resistance, because they want to spend on their children and grandchildren, not themselves. However, what we do can absolutely benefit their families and their savings. Living as independently as possible, for as long as possible means avoiding the costs of hospitalization and institutionalization. It also means the ability to be actively involved with family and friends. We may also market to the social-values inclination of older adults’ families or powers of attorney who may be involved in their health care decisions. The strength, vitality, and in-

creased safety that can result from effec- tive PT intervention are certainly things worth buying for a loved one.

To explain our value to physical-value folks, we can emphasize the way healthy activity engages the senses. Whether it’s hiking, running, swimming, or even cre- ating something pleasing to the senses, like a beautiful garden or a renovated room, we can help ensure that the ability to achieve enjoyment of these experienc- es. My own father recently underwent elective knee surgery and PT to prolong his ability to trail run, an activity that is invaluable to him.

Finally, there are those driven by fi- nancial values, who relish saving, invest- ing, and getting good deals. We might lump insurers into this category, along with many individual spenders. Here we need to demonstrate the pure value of what we do. We need to devote time and energy to further studies demon- strating that effective PT keeps people at home, out of doctors’ offices, hospitals, and skilled nursing facilities. This is the kind of evidence that will appeal to these bottom-line spenders.

Overall, we need to be shaken out of the complacency that patients will be de- livered to our practices and accompanied by generous insurance benefits. Over the next few weeks, pay attention to health care marketing you see around you. You will hear and see ads for hospitals, physi- cian practices, plastic surgeons, sports orthopedic surgery groups, and a few of our peers. Everyone is vying for a piece of the pie. We need to be active partici- pants in the development of health care and reimbursement trends. We need to take pride in our skills and elevate the profile of our profession. This is essential to our growth and financial viability in the years to come.

editOr’S MeSSAGe: SeLLiNG GeriAtriC pt Melanie Sponholz, MSPT, GCS, CCEP, CHC

Copyright of GeriNotes is the property of American Physical Therapy Association, Geriatrics Section and its

content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s

express written permission. However, users may print, download, or email articles for individual use.

Copyright of Journal of Applied Biomechanics is the property of Human Kinetics Publishers, Inc. and its

content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s

express written permission. However, users may print, download, or email articles for individual use.

Journal of Bodywork & Movement Therapies (2010) 14, 289e293

ava i lab le at www.sc ienced i rec t . com

journa l homepage : www.e lsev ier . com/ jbmt


About prevention

LWarrick McNeill, MCSP, Associate Editor*


United Kingdom



N d E D IT O R : W A R R IC K


What is prevention?

About 4500 years ago, according to Chinese tradition, and Fletcher (1988), the Yellow Emperor, Huang-di, only paid his physician’s retainer when he was well and stopped paying when he was not. ‘The wise people (the sages) did not treat those who were already ill; they instructed those who were not yet ill.’ Preventative measures (nourishment, rest, exercise and sleep) consisted of 4 of the 5 modes of treatment espoused at that time.

Serge Gracovetsky, reports in an interview published on YouTube, that he once, while suffering back pain, went to see seven different Orthopaedic or Neuro Surgeons but received seven different diagnoses. Gracovetsky appears to have applied a similar principle and didn’t pay any of them to proceed with their suggested treatments. Four recom- mended surgery, three did not. He decided that the best course of action was to do nothing, but go to the Library to find out what he could about back pain.

Have we then come very far in the intervening four millennia?

On the safetylit.org website, an online source of injury prevention literature, they state: ‘Injuries have causes e they don’t simply befall us from fate or bad luck. To prevent injuries it is necessary to have information about the factors that contribute to their occurrence. With this information we may understand the options for prevention. Effective injury prevention requires a multifaceted, multidisciplinary approach.’ It is also a very broad remit. Too broad perhaps? Health and Safety Directives seem to be impinging on society and theworkplace. Enough so as to encourage theUK’s Health and Safety Executive to produce ‘Myth of the Month’ posters debunking ‘Great health and safety myths.’ November 2009s

* Tel.: þ44 7973 122996. E-mail address: warrick@physioworks.co.uk

1360-8592/$ – see front matter ª 2010 Elsevier Ltd. All rights reserved doi:10.1016/j.jbmt.2010.04.001


poster points out that it is amyth that Health and Safety rules stop classroom experiments. The cartoon shows a rather sad teacher and pupils wearing safety goggles watching paint dry on a card propped up in a safety-glass cabinet.

As a Physiotherapist I use the UK Health and Safety Regulations on Display Screen Equipment (1992) (based on the relevant EC directives) in the part of my practice which involves ergonomically assessing staff at their computer workstation, but even then, I’m a second tier external consultant e only brought in when the staff member is already reporting pain, and has usually already been seen by the in-house assessors. Is my role ‘preventative’?

Prevention, as a concept of health management, appears to be wasted on the young. The hubris and inde- structibility of youth becomes more glaring as one ages and becomes more risk adverse. The young appear not to listen to sound advice, they do not appear to learn by others mistakes rather they seem to want to sustain the injury to discover that they need to avoid injuring themselves in the first place. Being an Injury Prevention specialist working with the young might not possibly score highly on a job satisfaction questionnaire, but how much ‘prevention’ work actually occurs prior to first episode injuries?

When my Physiotherapy colleagues discuss prevention it is usually about preventing recurrence of the injury, so it is after the fact of the original insult, and becomes part of rehabilitation.

Mark Ford, a Pilates/Gyrotonic/Franklin Method instructor in Australia says, ‘To me rehabilitation and prevention can not be separated. Rehab is not complete if the client doesn’t understand causes, actions and conse- quences.’ (Ford, 2010).

Chaitow (2010) says eloquently in a personal communi- cation, ‘I work with a model in which dysfunction emerges from a background of failed adaptation (to overuse, misuse, abuse and disuse). In such a model prevention is seen to involve modifying or eliminating those stressors that can be


P R E Vhttp://safetylit.orgmailto:warrick@physioworks.co.ukhttp://www.elsevier.com/jbmthttp://www.sciencedirect.com

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identified e so reducing adaptation demands bodywide, or locally. In addition, prevention entails enhancing func- tionality (bodywide and/or locally) so enabling the system or area to better cope with adaptation demands. Rehabil- itation of existing dysfunction involves a similar model of care e with specifically focussed interventions and strate- gies, as well as generalised ones (better posture, breathing, nutrition, habits of use etc). Prevention therefore only differs from rehabilitation by virtue of the context and the objectives’.

So it appears, in the context of therapy and therapists, that prevention and rehabilitation treatments or strategies could possibly be the same thing, but just be a question of timing, before or after an incident (or injury provoking behaviour), that may itself be an original insult, second or third.

Chronic low back pain

Exciting advances made in motor control and pain research means that there is a diagnosis and management shift from a pathological and anatomical viewpoint to a dynamic systems approach according to Key (2010a). In the opening chapters of her recently published book, ‘Back Pain: A movement problem.’ Key neatly summarises Waddell who states that: only about 15% of patients with back pain show definite structural pathology, the relationship between imaging and symptoms is weak, and in the absence of a diagnosis Health professionals may look to psychological reasons for their pain, therefore, there is no surprise that the ‘biopsychosocial model’ has evolved.

While not discounting the biopsychosocial model readers of the Journal of Bodywork and Movement Therapies may too realise that hands-on or therapeutic exercise answers may exist for their clients neuromusculo-skeletal problems.

Key goes further and looks at classification systems for Chronic non-specific low back pain (CNLBP) or ‘ordinary’ back pain, quoting Riddle (1998) that current classification systems are confusing, looking at appropriate treatments, or prognoses, or pathology. She also quotes O’Sullivan (2005) who overviews 8 models, including the ‘Motor control model’ in which O’Sullivan bases his own work. Key suggests the ‘Functional movement model’ that combines many features of other CNLBP models including the bio- psychosocial (Key’s own bolding) and Motor control. She suggests that ‘altered function of the posturo-movement system is the primary problem largely responsible for the development and perpetuation of most pain syndromes.’

I asked Key (2010b) about how she considers prevention in the therapeutic context, she said, ‘I certainly consider that prevention is an important aspect of comprehensive therapeutic care e yet this aspect seems to have been largely usurped by the ‘fitness’ and related industries who have little ‘real rehabilitation’ training e hence who knows what they base their ‘‘prevention programs’’ on. I consider that if prevention strategies are to be meaningful and functionally useful, they need to be built upon a well informed understanding around a number of related aspects concerning movement control:

(a) What is ‘more ideal’ posturo-movement function? Appreciating this also enables better application of the

available evidence; to put research outcomes into the clinical context; and even question the clinical utility of some findings

(b) The evidence is pointing more towards deficiencies in motor control being associated with spinal pain disor- ders and so, more beneficial programs should focus upon the quality of our patterns of movement control rather than the ubiquitous ‘strengthening’ and ‘stretching’

(c) The practitioner needs to be cognisant of the fact that seemingly subtle changes in posturo-movement control are usually apparent before the onset of pain. These changes can tell us a lot about the potential or actual problems the patient may be/is experiencing and so this can also serve a certain predictive role e important for prevention programming.

(d) The practitioner needs to appreciate ‘‘what are the more likely patterns of dysfunctional response going to be’’? While evidence is giving us more answers in this area, at this point in time we need to rely more on our clinical pattern recognition and therapeutic skills to provide the substance of more meaningful prevention program.

(e) In essence, effective programs of care e therapeutic and preventative, depend upon a balance between artful clinical practice informed by the knowledge that science can offer.’

In summary Key said she ‘is trying to get the message out there that clients most probably need to work smarter not harder!’

We know that a marker for measuring the success of rehabilitation is in dropping recurrence rates, it is the underlining and exclamation point a researcher has when they publish their follow up study, see Hides et al. (2001) work on the deep multifidus.

The 3rd movement dysfunction conference 2009

During a dismally wet Edinburgh weekend Sahrmann (2009a) presented her Keynote Lecture on Low back pain: ‘Isolated or degenerative problem e what are the impli- cations?’. She stated that ‘90% of people are expected to experience low back pain during their life’ with a high recurrence rate ‘between 30 and 80%’ These high incidence and recurrence rates, she says, ‘are consistent with low back pain being associated with the degenerative process’ and this process consists of ‘temporary dysfunction and 4 stages of hyper-mobility before the final stage of hypo- mobility and spinal stenosis. If the ‘‘acute episodes’’ are part of the pattern of temporary dysfunction associated with segmental hyper-mobility then treatment should be directed toward control and prevention of the progressive hyper-mobility that at a minimum should slow the degen- erative process.’ She challenges physical therapists to ‘monitor the pattern of movement of the low back, designing and appropriately instructing the patient in corrective exercises and movement strategies rather than just providing episodic short-term treatment.’ Sahrmann reported that clinical examination is reliable, in trained

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people, in identifying movement faults and that there is validity in identifying (movement) subgroups (Sahrmann, 2009b).

Fass (1996), ‘Exercises: which ones are worth trying, for which patients, and when?’ found that more research on ‘different types of exercising’ in patients with chronic back pain was necessary. Sahrmann’s comments at the Move- ment Dysfunction conference suggests that there may eventually be a plethora of well reasoned, specific exer- cises for specific movement faults, identified by pattern recognition and clinical testing, that probably make up the 85% of CNLBP sufferers that do not have a structural pathology.

‘Movement screening’ was highlighted at the confer- ence, first by Gray Cook who introduced his Functional Movement Screen (FMS). Cook (2009) identified that the strongest predictor of future injury is previous injury. The FMS, is a reliable (Minick et al., 2010) predictive system for those who do not have a known musculo-skeletal injury. It assesses functional movement patterns looking for asym- metries and movement limitations, and therefore, he suggests, indicates what ‘to do’ with the client.

The test movements are relatively simple and include:

� a deep squat � a hurdle step � an in-line lunge � shoulder mobility � an active straight leg raise � a trunk stability push up, and � a rotation stability test.

Comerford (2009, 2004) in his presentation to confer- ence discussed that in sport (where improving performance becomes a major goal of the support staff, as opposed to, in the clinic where the major goal is reducing pain and disablement) the significant ‘Recurrence of injury and pain’ indicates that something is missing in our current screening and prevention strategies.

Comerford pointed out that assessments and screening of athletes is standard across the board. Screenings primarily look at testing joint range, muscle strength (power and endurance) and muscle extensibility. Comer- ford was clear that these are all relatively unsuccessful at predicting risk of re-injury or recurrence of pain. Like Cook, Comerford also identified that history of previous injury is the single most consistent and reliable predictor of high risk of re-injury. He identified that the isolationist testing of joint range of motion or normal muscle strength is not an adequate rehabilitation end point to prevent recurrence. Comerford suggested it is the assessment of the control of ‘real’ function that is the missing piece of the screening puzzle. He defines ‘real’ function as the influence of the multiple muscle interactions acting on multiple joints in functionally orientated tasks.

Comerford advocates the Perfomance Matrix screen, that he presented to the conference. I personally teach a version of this to the pilates community. At the centre of the screen is the assessment of the motion segment (or regional) ‘hyper-mobility’ referred to by Sahrmann earlier. This may be directional (i.e. flexion, extension, rotation etc) and, equally importantly, relates to the threshold at

which it occurs (low or high). Comerford terms this ‘uncontrolled movement.’ Sahrmann refers to the same concept as the ‘direction susceptible to movement’, and O’Sullivan as a ‘control impairment.’ Comerford suggests it is the threshold at which the failure occurs which dictates whether the specific exercises required to improve the uncontrolled movement should be slow motor unit domi- nant (low threshold) thereby showing a Central Nervous System (CNS) led ‘recruitment’ failure of the muscles that should be providing the control, or a fast motor unit dominant (high threshold) ‘weakness’ e meaning the hyper-mobile area needs muscular strength to provide the control. This is the key differentiation between the FMS and Performance Matrix approaches.

In the real world

Swart (2010), Physiotherapist for elite athletes in South Africa reports that ‘in the area of symptoms we mostly find uncontrolled movements with the low threshold tests which makes sense due to the fact that pain affects slow motor unit recruitment. With the Performance matrix or FMS we can determine risk factors for injury in other areas of the body before they occur preventing further time out due to injury. It is less time consuming to prevent injuries rather than treat the injuries, and athletes hate not being able to train. Once there is pathology it usually means the athlete has to rest for 6 weeks to allow for healing or at least I change their exercise program to allow them to perform unloaded training in water. Athletes usually start too quickly and try to progress too fast leading to recur- rences of injuries or injuries in other areas due to compensation.’

Barr (2010), an Injury Prevention Specialist for the New York Knicks Basketball Team, confirms the requirement for interdisciplinary co-operation. Barr does not regard re- active injury prevention programs as injury prevention e this, he says, ‘is just an extension of injury rehab.’ Like the Yellow Emperor before him Barr believes that, ‘optimal nutrition, hydration and sleep quality are all essential aspects of injury prevention. If these obvious basics are not taken care of fully, then any other injury prevention strategy employed will have a lesser effect.’

Barr suggests the athlete needs to:

� be specifically conditioned to perform in their specific sport,

� after previous bouts of exercise be fully recovered to perform,

� be in a ready state to perform physically (warmed up) and mentally (focused) and,

� have optimal neuromuscular control, stability, mobility and strength for the demands of their specific sport.

To ensure all these considerations are taken care of reliable screening and testing methods need to be frequently performed.

‘My area of expertise,’ says Barr, ‘and what I believe to be an essential part of the screening process, is the ‘‘analysis of the quality of movement.’’ In my experience screening for ‘‘movement control’’ and ‘‘producing injury

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prevention programs to improve the control of movement’’ have great success. Aside from traumatic injuries most other injuries can be related to ‘‘uncontrolled movement.’’ It is relating uncontrolled movement to the pathology that allows you to understand how uncontrolled movement is an injury risk and correcting uncontrolled movement is injury prevention.’

Crossover between pain and human performance

It is interesting to note that Cook and Comerford, system developers, and Swart and Barr, users of a system of assessing movement control, are physical (or physio) ther- apists who originally trained to treat pain and injury but have moved out from a narrow focus to look at human performance as well. They have the remit, via their professional training, to look at both patients (those in pain) and athletes (concentrating on those with perfor- mance deficits). Not all who read the JBMT will be able to move easily between these two camps. Some movement disciplines such as Pilates or Yoga are not widely regarded as ‘treatment’ and therefore their teachers should not work without the co-operation of a suitably qualified health professional or without clearance from a doctor who is knowledgeable (both about the patients condition and the discipline they are referring to). Yet many who present to Pilates or Yoga Teachers do so because they are in pain, perhaps they do not identify themselves as having pain for fear of being excluded from the session or perhaps they do not see that it is important for the teacher to know about their pain. It is often the wording of the practitioners insurance policy that defines who a Teacher can see, however, it is becoming very clear that movement dysfunctions are responsible for the internal environment that leads to pain. Pain is probably just a late sequelae of the same movement faults that Pilates and Yoga teachers see in every class that they teach. The Teachers have the tools to alter these movement faults by their interventions, cueing and handling, thereby ‘preventing’ the ‘pain’ that could have otherwise have been expected to follow.

It is the fact that exercise is often undertaken in group classes so that a teacher should ideally:

� keep the group size small, � know the clients extremely well, � have assistants, � play to the lowest common physical denominator, or ‘sub-group’ their classes to fit those with similar prob- lems together, to keep the individual in a group as ‘safe’ as possible.

Individual or ‘one to one’ sessions are a luxury that for many clients is imperative if they are to progress with the least risk of recurrence from being given an inappropriate exercise or trying too hard too soon or simply not working hard enough. In an individual session a teacher is able to discover the modifications that that client requires to zone a specific exercise into something that is maximally beneficial in that instance as opposed to performing

a ‘cheat’ in which the cheat becomes perpetuated. Criti- cism of the disciplines of Pilates and Yoga (Key, 2010a) to name but two disciplines is fair especially when poorly trained teachers, use exercise recipes and dogma instead of individual assessment, critical thought and exercise modification.

In my personal opinion the nascent scientific research looking at Pilates or Yoga often lets itself down by not defining within the research question what part of the discipline it is looking at. The disciplines have varied practices of the same activities yet a broad brush stroke description of what is undertaken is often deemed enough. Describing every detail, especially modifications of exercises encouraged and cueing used, may help the disciplines develop a scientific credibility that at present appears to be unfortunately lacking. Careful thought as to what exercises should be excluded from a particular study might be more beneficial than performing all the available repertoire. The history of chronic low back pain research over the last one or two decades, and recent thoughts on motor control and sub-grouping that are now developing, could be applied to help accelerate research in Pilates or Yoga.

Call to action

As this is the Prevention and Rehabilitation section of the Journal of Bodywork and Movement Therapies I would like to put a call out for papers with a focus on injury prevention or the prevention of injury recurrence. If we accept that motor control deficiencies eventually lead to pain and disability we want to know which movement strategies can be used as motor control tests, or whether those motor control tests currently in use are good predictors of injury risk.

Gracovetsky’s (2010) paper discussing ‘Range of Normality’ and injury prevention is an excellent example of the type of paper that improves our knowledge of injury prevention.

Feedback: core stability is a subset of motor control

Lederman’s (2010) Myth of core stability paper provoked a muted response in reply to my editorial (McNeill 2010), though it is currently, at the time of writing, the most downloaded article from the JBMT, via ScienceDirect. Comments made showed appreciation of a critical look at core stability, and reiterated that clinicians should be careful not to read too much into research that might not be there.

In relation to Core Strengthening, Marcus (2009) quoted ‘plus a change, plus c’est la mÁme chose’. (The more things change, the more they stay the same). He identified that in his time as a pain medicine MD that several exer- cise approaches have come and gone, ‘they become jargonized and thus useless. New is not necessarily better.’ Marcus et al. (2010) points out that he currently uses the Kraus exercise program in his chronic pain treatment protocol. This system (of what we might now regard as non-specific exercise) was developed in the

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1950s and reduced or eliminated back pain in 80% of those undertaking them.

It seems that despite science and fashion appearing perhaps to be opposite fields of endeavour they both appear influenced by seasons!

In this edition

In line with this editorials theme on prevention (and in this case ‘prevention of recurrence’), and with its prevalence in sports, Stephanie Panayi discusses the need for lumbar- pelvic assessment in chronic hamstring strain. Josephine Key, who has written before for the JBMT, elaborates further on Vladimir Janda’s ‘Pelvic crossed syndromes’ for this issue. Craig Liebenson’s popular self management: patient section wraps up this editions Prevention and Rehabilitation section.

As always, please feel free write to me in response to the Editorial, the papers, or the ongoing themes within the journal or affecting your own practice.


Barr, A., 2010. Personal correspondence. Chaitow, L., 2010. Personal correspondence. Comerford, M.J., 2004. Core stability: priorities in rehab of the

athlete. SportEx Medicine 22, 15e22. Comerford, M.J., 2009. Recurrence of injury and pain in sport e

what’s missing. Manual Therapy 14 (5), S1eS54. Cook, G., 2009. What is our baseline for movement? The clinical

need for movement screening and assessment. Manual Therapy 14 (5), S1eS54.

Fass, A., 1996. Exercises: which ones are worth trying, for which patients, and when? Spine 21 (24), 2874e2878.

Fletcher, G.F., 1988. Exercise in the Practice of Medicine, second revised ed. Futura Publishing, Mount Kisco, New York.

Ford, M., 2010. Personal correspondence. Gracovetsky, S., 2010. Range of normality versus range of motion:

a functional measure for the prevention and management of low back injury. Journal of Bodywork & Movement Therapies 14 (1), 40e49.

Hides, J.A., Jull, G.A., Richardson, C.A., 2001. Long term effects of specific stabilizing exercises for first episode low back pain. Spine 26 (11), 243e248.

HSE Booklet L26 Display screen equipment work: Health and Safety (Display Screen Equipment) Regulations 1992: guidance on regulations. ISBN: 0-7176-2582-6.

Key, J., 2010a. Back Pain: A Movement Problem. Churchill Living- stone Elsevier.

Key, J., 2010b. Personal correspondence. Lederman, E., 2010. The myth of core stability. Journal of Body-

work and Movement Therapies 14 (1), 84e98. Marcus, N., 2009. Personal correspondence. Marcus, N., Gracely, E., Keefe, K., 2010. A comprehensive protocol

to diagnose and treat pain of muscular origin may successfully and reliably decrease or eliminate pain in a chronic pain pop- ulation. Pain Medicine 11 (1), 25e34.

McNeill, W., 2010. Core stability is a subset of motor control. Journal of Bodywork and Movement Therapies 14 (1), 80e83.

Minick, K.I., Kiesel, K.B., Burton, L., Taylor, A., Plisky, P., Butler, R.J., 2010. Interrater reliability of the functional movement screen. Journal of Strength Conditioning Research 24 (2), 479e486.

O’Sullivan, P., 2005. Diagnosis and classification of chronic low back pain disorders: maladaptive movement and motor control impairments as an underlying mechanism. Manual Therapy 10, 242e255.

Riddle, D.L., 1998. Classification and low back pain: a review of the literature and critical analysis of selected systems. Physical Therapy 78 (7), 708e737.

Sahrmann, S., 2009a. Low back pain: isolated or degenerative problem e what are the implications? Manual Therapy 14 (5), S1eS54.

Swart, J., 2010. Personal correspondence.

Web sources

Science & Humour with Dr. Serge Gracovestsky e Part 1. http:// www.youtube.com/watch?vZqgh2C8M50Iw.

http://www.safetylit.org. http://www.hse.gov.uk/myth/nov09.pdf. Sahrmann, S., 2009b. http://www.webducate.net/icmd_blog/?

pZ53. www.functionalmovement.com. www.performance-stability.com.


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R E H A B IL IT A T Ihttp://www.youtube.com/watch?v=qgh2C8M50Iwhttp://www.youtube.com/watch?v=qgh2C8M50Iwhttp://www.safetylit.orghttp://www.hse.gov.uk/myth/nov09.pdfhttp://www.webducate.net/icmd_blog/p=53http://www.webducate.net/icmd_blog/%3Fp%3D53http://www.functionalmovement.comhttp://www.performance-stability.com

  • About prevention
    • What is prevention?
    • Chronic low back pain
    • The 3rd movement dysfunction conference 2009
    • In the real world
    • Crossover between pain and human performance
    • Call to action
    • Feedback: core stability is a subset of motor control
    • In this edition
    • References
    • Web sources

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———————————-———-——— expert perspective —————-———————————-—-

Forecasting Health Care Delivery for Older Adults in the Midst of Change: Challenges

and Opportunities for the Physical Therapy Profession in an Evolving Environment

Andrew A. Guccione, PT, PhD, DPT, FAPTA, Jody Frost, PT, DPT, PhD, and John O. Barr, PT, PhD, FAPTA

Vol 28, No 2, 2014 Journal of Physical Therapy Education 7

the third prong, by discussing how poten- tial changes in the delivery and utilization of care to older adults poses both challenges and opportunities for the physical therapy profession, and describing the demographic sociopolitical backdrop for the companion paper by Wong and associates, “Building the Physical Therapy Workforce for an Aging America,”2 that addresses the first 2 compo- nents of the IOM report related to the pro- fession of physical therapy, particularly the education of the workforce.

Leaders in physical therapy education are committed to preparing physical therapists and physical therapist assistants to provide services to older adults in the United States, therefore must prepare students entering the workforce with the abilities to negotiate a drastically altered heath care landscape, es- pecially when working with older adults. The purposes of this paper are to: (1) inform the physical therapy education community about important age-related population factors that deserve emphasis in physical therapy education curricula; (2) describe the evolving nature of health care financing and service utilization that will effect changes in health care delivery; and (3) identify the challenges and opportunities in the clinical practice of physical therapy that may arise in the profes- sion’s efforts to meet societal needs related to our aging population more effectively and efficiently.

POSITION AND RATIONALE It is our position that the profession of physi- cal therapy in the United States (US) needs to be nimble in an evolving environment that will change health care financing and deliv- ery over the next decade. The profession must also continue to exercise sure-footed steps forward in clinical practice and education that can maximize the contributions that the

Andrew Guccione is professor and chair of the Department of Rehabilitation Science, College of Health and Human Services, George Mason University. Jody Frost is a lead academic affairs specialist at the American Physical Therapy Association. John Barr is a professor in the Physical Thera- py Department, College of Health and Human Services, St. Ambrose University, 518 W Locust, Davenport, IA 52803 (barrjohno@sau.edu). Please address all correspondence to John Barr. The authors declare no conflicts of interest. Received July 13, 2013, and accepted November 25, 2013.

and must continue to exercise sure-footed steps forward in clinical practice and edu- cation to maximize the contributions that the profession can make to the growing population of older adults. Our rationale includes: the changing landscape of aging in the US; the changing pattern of health care services utilization; changing models of health care delivery for older adults; and current and potential innovations in organization and delivery of services. Discussion and Conclusion. In working with older adults, patient/client instruc- tion and performance of functional activi- ties in the environment of the home and community will become more impor- tant in coming years. Physical therapists must position themselves for a leadership role among health professions, master- ing a broad skill set, and adapting to fit the evolving organizational structure of health care financing for older adults. Keywords. Entry-level education, Faculty development, Geriatrics.

Background and Purpose. Providing a backdrop for the companion article in this issue by Wong et al, “Building the Physical Therapy Workforce for an Aging Ameri- ca,” this paper focuses on how potential changes in the utilization and delivery of care to older adults pose challenges and opportunities for the physical therapy profession. The purposes of this paper are to: (1) inform the physical therapy education community about age-related population factors that deserve emphasis in physical therapy education curricula; (2) describe the evolving nature of health care financing and service utilization that will effect changes in health care delivery; and (3) identify the challenges and oppor- tunities in the clinical practice of physical therapy that may arise in the profession’s efforts to meet societal needs related to our aging population more effectively and efficiently. Position and Rationale. The profession of physical therapy in the United States (US) needs to be nimble in an evolving envi- ronment that will change health care fi- nancing and delivery over the next decade

BACKGROUND AND PURPOSE In 2008, the Institute of Medicine’s (IOM) Committee on the Future Health Care Work- force for Older Americans released its report “Retooling for an Aging America: Build- ing the Health Care Workforce.”¹ As a call for fundamental reform in the way that the workforce is both trained and utilized in the care of older adults, this report advocated a 3-pronged approach to an aging America: enhancing the geriatric competence of the entire workforce; increasing recruitment and retention of geriatric specialists and caregiv- ers; and improving the way care is delivered to this population. This paper focuses on

profession can make to our growing popula- tion of older adults.

The Changing Landscape of Aging in the United States

In the past decade alone, the number of per- sons whose age is 65 years or older in the US grew faster than the rest of the population.3 In 2010, 40.3 million people counted in the US Census were 65 and older, representing 13% of the entire population.3 By 2030, it is estimated that the number of people 65 and older will reach to 72 million.4 By 2050 the number of individuals who are 65 years of age and older should reach 88.5 million, with about 19 million over the age of 85 who will account for over 4% of the population.4

With aging comes increased risk of man- aging one or more chronic diseases, often associated with disabilities. In the United States, over 45% of adults age 65 or over have 2-3 chronic conditions.5 Arthritis, hyperten- sion, diabetes, coronary heart disease, cancer, and chronic obstructive pulmonary disease appear most frequently as various dyads or triads of multiple chronic conditions among men and women in this age group.5 For non- institutionalized Americans, ambulatory disability (ie, serious difficulty in walking or climbing stairs) affects the highest pro- portion of the population. Stratified by age, 16% of 65-74-year-olds and 33% of those 75 years of age and older have an ambulatory disability.6 This segment of the population with multiple chronic conditions that impede daily function offers a critical opportunity for the profession, as many of these individuals are living and still working in the community and are not the typical geriatric patients seen in acute care, home care, or nursing home settings.7

There is a dynamic tension in the political landscape between government entitlements and individual responsibility, specifically with respect to which side of this equation should shrink and which should grow. If, for example, the Medicare cap on physical therapy were lifted, then presumably services to older adults would increase to cover needs that went unmet because of the cost to the in- dividual. If government entitlements shrink and individual responsibility grows, poten- tially there could be a shift in the number of older adults who choose to receive physical therapist services as out-of-pocket paid ex- penses after the defined benefits of Medicare or a private insurance plan are exhausted. Fur- thermore, with particular respect to federally funded benefits, disproportionate spending at the end of the life span could leave far less to distribute across the health status continu- um of older adults, including those function-

8 Journal of Physical Therapy Education Vol 28, No 2, 2014

ally limited, chronically ill older adults who rely solely on Medicare. Ultimately, physical therapist services will become a value propo- sition, paid for only when value is evident, re- gardless of whether the federal government, the private insurer, or the individual pays the proportionately largest amount.

In addition, trends in labor force growth rates show that the individuals born in the United States between 1946 and 1964, known as the Baby Boomers, continue to participate in the labor force as they approach and pass the typical retirement age and are expected to continue this pattern for at least the next decade.8 Even with this extended participa- tion in the labor force among older adults, the shift from defined-benefit employee health and retirement plans to increased employee health premiums and defined-contribution retirement plans that began in the 1990s plac- es more responsibility on the employee for health insurance premiums, diminishing the financial resources for working older adults as well as retirees who can be concerned that their resources will not be sufficient to sup- port them over the long run. Thus, some older adults must make a deliberate decision to pay for any health services that may be capped as a benefit, entail large copayments with each treatment received, or pose substantial out- of-pocket expenses for the episode of care. This will further complicate the decisions that older people need to make about their health care purchases and force them to determine whether the value of a given service makes it essential or optional.

The Changing Pattern of Health Care Services Utilization

Until recently, the US health care system was primarily an episodic medical care sys- tem, built around segmented networks of hospitals and primarily fee-for-service com- munity-based providers, including physical therapists. Access and availability have been largely dependent on one’s insurance benefits and locality. Services tended to be fragment- ed because the system lent itself toward frag- mentation by episodic “start and stop” service provision with little contact among providers and little opportunity for coordination of care to maximize health outcomes. Patients fell through the organizational cracks because these flaws were systemically part of health care delivery. However, market response to the Patient Protection and Affordable Care Act (PPACA),9 as well as some provisions of the law itself, may force some of these organizational faults to shift. The emphasis on identifying the drivers of increasing and unsustainable health care expenditures, as well as changes in the vertical and horizontal

integration of health care services under the auspices of accountable care organizations (ACOs), have placed increased attention on well-managed care transitions that are ex- pected to decrease costs and improve quality by promoting early problem detection and preventing costly hospitalizations and read- missions.

One of the primary roles for physical therapists has been the diagnosis and treat- ment of functional deficits in the context of remediating impairments, lessening the functional burden of disease, and improving quality of life. However, the knowledge and skills that physical therapists have contrib- uted to the general well-being of older adults, particularly community-based frail individu- als, has now been placed in the context of the financial sustainability of health care delivery systems. Physical therapists who can prevent problems before or as they arise, and dimin- ish the need for inpatient hospitalization, are more likely to be seen as valued collaborators if the profession can empirically demonstrate that physical therapist services can reduce costs to the system. While the previous re- habilitation paradigm focused on individual patients returning to the community after receiving high-quality care, the new para- digm of rehabilitation will center on patient populations remaining in the community and using fewer system resources. The quality of the service is assumed to stay the same. How- ever, it is not enough that the physical thera- pist service be cost-effective in and of itself. The reach of cost-effectiveness as an outcome variable of health care has been extended be- yond individual service provision to include the value of the service to reducing costs of the whole system.

Changing Models of Health Care Delivery for Older Adults

The PPACA,9 signed into law on March 30, 2010, is seen by many as having the poten- tial to transform the health care system. In actuality, there is still a great deal of uncer- tainty as to exactly how the new law will be implemented or changed as many of its pro- visions will take effect in 2014 and later. Key provisions removed many barriers to health insurance such as preexisting conditions and life-time limits, linked Medicare payments to quality measures, expanded coverage op- tions for Medicare beneficiaries, opened the door to preventive services under Medicare, and offered the possibility of innovation in community-based wellness programs.

Although there are some who are con- vinced that the long-term savings realized from improving the quality of health care while reducing the need for more costly

Vol 28, No 2, 2014 Journal of Physical Therapy Education 9

medical intervention will be sufficient to pay for an expanded array of services, there are equally as many who doubt that all of the pro- visions of PPACA will roll out as originally intended if spiraling health care costs are not controlled in the short term. Furthermore, despite earlier indications that disability among adults was on the decline, more recent analyses suggest a more troubling picture. It appears that there is increased disability among the first waves of Baby Boomers en- tering older adulthood compared to previous generations, particularly among non-white, obese, and socioeconomically disadvantaged subgroups, all factors which independently increase the risk of disability as well.10 While these facts could herald an opportunity for the profession, there is no certainty that the emerging description of an aging America is also the final word on the first decades of the 21st century. In actuality, the only certainties on which most nearly everyone can agree is that third-party payment for health care ser- vices is likely to decrease and reporting re- quirements are likely to increase. Therefore, physical therapists must expect that they will be asked to do more with less to provide the right service to the right people at the right time. High quality, evidence-based service provision is assumed; cost-effectiveness with both short- and long-term savings to the sys- tem is expected.

Innovations in Organization and Delivery

Although the PPACA9 is regarded as a major breakthrough in moving away from a proce- dure-focused medical care system towards a wellness-oriented health care system, there have been small scale attempts over the past 40 years to demonstrate the clinical effective- ness and cost utility of organizing an array of physical, psychological, and social health services to older adults living in the commu- nity. Many of the most innovative programs emphasize care coordination and the impor- tance of interprofessional team practice. The Eldercare Workforce Alliance, of which the American Physical Therapy Association is a member, partnered with the National Coali- tion on Care Coordination to produce an is- sue brief that reviews the critical elements of care coordination, as well as emerging mod- els.11 However, it is critical to note that many of these emerging models imply that physi- cal therapists are part of the team, yet fail to explicitly name our profession as part of the team.

Established models of rehabilitation for frail older adults. The following programs are recognized as exemplary models for orga- nization and delivery of care to older adults.

They also include elements of interprofes- sional practice. On Lok is considered by many to be the first program of its kind to of- fer comprehensive health and social services in a single point of care to community-based frail older adults who were eligible for nursing home placement.12 Shortly after its inception, On Lok was eligible for Medicaid reimburse- ment, taking on the challenge of providing coordinated comprehensive services to low income and impoverished older adults. Sub- sequently, On Lok became the model for mul- tiple replication projects across the country in which the organization assumed the financial risk for providing care to enrollees for a fixed capitated payment. Over the past 25 years, On Lok evolved to become the entity now known as the Program of All-Inclusive Care for the Elderly (PACE). PACE was recognized by Medicare as a financially viable alterna- tive to traditional Medicare plans, known as special needs plans (SNPs), along with other Medicare Advantage plans.12

Physical therapists are extensively in- volved in PACE programs due to the health and functional status of individuals enrolled in this type of program. A key admission re- quirement is that the person be eligible for nursing home placement. Therefore, only frail older adults with substantial limitations in performing activities of daily living are served by the clinical team of providers across the professional spectrum. Although the point of care and the highly coordinated team approach may be innovative, the goals of care and the methods of one-on-one service deliv- ery, dictated by the needs of the patient, are similar to what one would expect for physical therapists working in other geriatric settings.

Some SNPs such as Evercare, operated un- der the auspices of United Healthcare, have targeted specific market segments, such as chronically ill individuals, who experience or are at great risk for functional decline, as well as palliative and hospice care.13 Evercare provides services at home, in assisted living residences, and in nursing homes. A major emphasis of Evercare’s approach is care coor- dination and problem surveillance by nurse practitioners. Again, due to the health and functional status of the individuals enrolled in this type of health insurance plan, physi- cal therapists play a major role in providing services to remediate impairments, improve function and support quality of life, such as they perform under other insurance models.

Models of rehabilitation for community- based older adults. Fifteen years ago, Rim- mer14 presented a model of health promotion for adults with chronic illness and disability that described a major community-based role for physical therapists in secondary preven-

tion. Secondary prevention, intervening early in disease progression to limit its effects on morbidity, is a role that unfortunately re- mains largely marginalized in contemporary physical therapist practice.15 Rimmer’s model distinguishes between clinically supervised health promotion, which a small but increas- ing number of physical therapists routinely provide as an extension of rehabilitation, and community-based health promotion programs, typically run by fitness profes- sionals who are not licensed as health care providers.16 Specifically, Rimmer notes that implementing a therapist-to-trainer model strengthens these sorts of programs by bring- ing the physical therapist’s clinical expertise in treating this population to bear on the de- sign of post-rehabilitation fitness programs as they are implemented in the communi- ty.17 Reintegrating older adults back into the community by facilitating their transition to non-health care, community-based fitness facilities promotes the full inclusion of in- dividuals with disabilities in environments intended for the general population. Further- more, these programs can diminish some of the accessibility and affordability barriers to maintaining a healthy lifestyle while living with a chronic condition.18 Actively embrac- ing emerging models of service provision such as these offers an unparalleled opportu- nity for innovative leadership in community- based health promotion. Participation of PT educators and clinicians in community-based exercise and fitness programs has the poten- tial to extend the success of a rehabilitation program by promoting behavioral change and adherence to prescribed exercise and physical activity recommendations that are critical to the health status of older adults, particularly those living with chronic illnesses.19

Evolving payment priorities. At one time, it was assumed that an increased number of older adults would translate to more physi- cal therapy (and thus, more physical thera- pists and physical therapist assistants). Such growth is not likely to occur in an environ- ment where sustainability is the overriding financial concern. While the specifics of re- imbursement and payment policy are uncer- tain at the moment, the move begun in the 1990s toward managed care and away from procedure-oriented fee-for-service will con- tinue.20 Moreover, it is reasonable to antici- pate that government programs will seriously consider capitation for complete episodes of care, including rehabilitation services, as a potential strategy in devising an alterna- tive payment system mandated by Congress and that private insurers would follow suit if such an alternative payment system were implemented. A high value has already been placed on services that decrease overall costs

10 Journal of Physical Therapy Education Vol 28, No 2, 2014

as capitated systems are incentivized toward savings. Although physical therapists and pa- tients tend to recognize the intrinsic value of physical therapy as it reduces impairments, increases function, and promotes quality of life, the profession should expect increased emphasis on its extrinsic financial value to save money. Physical therapist services that increase the costs of care without reducing or eliminating other health care costs will not be seen as valuable by health care systems, whatever their intrinsic value to patients. This value will be easiest to ascertain in closed sys- tems, such as self-insured hospital groups or employer-based insurance programs.

The emerging market shift does not nec- essarily entail a complete end to outpatient fee-for-service private practices, or even sound the death knell for self-pay practices. The number of older adults with potentially disabling conditions is clearly increasing, and the relevance of physical therapy to the func- tion and health of this population is generally accepted. Older adults with financial means will continue to seek out services they find beneficial. However, given the real and rela- tively high costs of providing physical thera- pist services, there are limits as to what the market will bear. The older adult patients with the most health care needs are likely to have lesser economic means to pay for them. Therefore services that are relatively infre- quent, produce long-term results, and make best use of personnel mix to lower costs are likely to benefit from changing demograph- ics and economic incentives. However, the profession also needs to consider that simi- lar services from less educated (and therefore less costly) providers are likely to increase at the same time, and the quality/cost ratio will remain in delicate balance for consumers and payers. Simply put, our profession will have to provide the right service to the right pa- tient using the right personnel at the right time in the right way for the right outcome at the right price.

DISCUSSION AND CONCLUSION There are 3 components to physical therapist practice as described in the Guide to Physical Therapist Practice21: documentation and care coordination, patient/client-related instruc- tion, and procedural interventions. The last of these, treatment for the older adult patient, is not the major challenge for the profession, presuming adequate academic education and clinical training in geriatric physical therapy as described by Wong and associates.2 Physi- cal therapists experienced in working with older adults know how to diagnose and treat those with multiple comorbidities and return them to the highest level of function. Howev-

er, the teaching component of physical thera- pist intervention could change drastically in an evolved health care delivery system in the decades ahead, particularly given the em- phasis placed on patient self-management, use of technology, and incentivizing to limit utilization. The patient in this system of the future is likely to be ethnically and racially more diverse, sicker with multiple chronic conditions, and generally less well-educated, which also means likely to have less economic means. English may not be the first language, and cultural preferences in diet, attitudes to- ward exercise and physical activity (outside of paid labor), and living conditions such as neighborhood amenities may not support be- havioral changes necessary to living well as an older adult at risk for deterioration of health and functional status. These individuals may not be well-integrated into traditional chan- nels of health care or have designated health care providers.

Evidence-based practice is more critical than ever, clinically and economically. The profession cannot meet the challenges ahead unless it sets aside a disposition to do what has always been done, commits to providing only those services whose efficacy is estab- lished, and promotes interventions whose effectiveness has been tested. Furthermore, goal-setting must fully incorporate the pa- tient’s perspective. While movement dysfunc- tion is central to diagnosis and intervention by physical therapists, developing the ca- pacity for movement (ie, movement under controlled clinical conditions) is not patient- centric. Physical therapists and physical ther- apist assistants must recognize that patients regard performance of functional activities in the natural environment of the home and the community as the standard for function- ing. Moreover, such a shift in perspective will increase the attention given to the patient’s physical and social environment as factors that influence disability.

Physical therapists must also position themselves for a leadership role among the array of professions who are attempting to corner the “post-rehabilitation” market, while recognizing that market forces will favor less expensive personnel over more highly edu- cated providers. Thus, physical therapists may need to grow more comfortable design- ing programs that can be implemented by supervising non-licensed personnel. Without uncontestable evidence that more expensive personnel, including physical therapist as- sistants, are safer or more effective than less expensive personnel, economics will prevail over professional provincialism. While it has become fashionable to speak of population- based physical therapy, on a practical level

much of physical therapy is appropriately delivered as a service to individuals. Gen- erally, physical therapist services are not population-based in the same respect as im- munization services are population-based. Innovation by physical therapists in health promotion by leading community-based fitness programs for older adults, especially individuals with chronic illness, will be a critical first step of physical therapy into public health . However, our profession has generally been reluctant to engage in popula- tion-based policy formulation or in planning services that meet the needs of any popula- tion segment, particularly if such policy or planning might engage service providers outside of physical therapy.

The profession is very aware of this im- pending evolution. The American Physical Therapy Association (APTA) has taken steps in recent years to address workforce and service delivery issues related to our aging population. As a member of the Eldercare Workforce Alliance, APTA has worked in a national coalition concerned with both the immediate and future workforce crisis in caring for older adults, by focusing on the workforce shortage, training and compen- sation, and advancing models of care.22 Ad- ditionally, as a member of the Partnership for Health in Aging, APTA was active in the development of Multidisciplinary Competen- cies in the Care of Older Adults at the Com- pletion of the Entry-level Health Professional Degree,23 and has endorsed the Partnership for Health in Aging Statement on Interdis- ciplinary Team Training in Geriatrics.24 In 2010, APTA explored innovative practice models being utilized to deliver physical therapist services in the US and found a di- versity of models being employed in a range of settings, including university-based, many having direct implications for older adults.25 Recently, APTA hosted the Innovation Summit: Collaborative Care Models, which brought together physical therapists, physi- cians, policy makers, and representatives from large health systems to discuss both current and future roles for physical thera- pists in integrated care models.26 In early 2014, APTA intends to initiate Innovation 2.0 to provide both guidance and funding to innovators who are developing or promoting the roles of physical therapists in collabora- tive care models.27

To effectively manage the emerging health care crisis, the workforce engaged in the practice of physical therapy with older adults will need to master a broad skill set. Perhaps most importantly, physical therapists who are ready to value the teaching components of practice as much as, or perhaps even

Vol 28, No 2, 2014 Journal of Physical Therapy Education 11

more than, direct treatment components, are primed to serve older adult populations in the coming decades. Future cohorts of older adults will need to understand how physical activity promotes high-level functioning and health across the lifespan, how exercise can improve balance and decrease falls and frac- tures, and how increasing functional well- being can diminish the impact of clinical and subclinical depression in the aftermath of sudden illness or injury such as stroke, heart attack, or other chronic illness. How- ever, physical therapists who succeed in the coming decades will need to develop a keen appreciation of the theory and practice of be- havioral changes as the system shifts greater responsibility to the individual for managing one’s own health.

There are certainly barriers to the adapta- tion and evolution needed by our profession to thrive in this challenging environment. Physical therapy is deeply embedded in tra- ditional reimbursement models that are rap- idly eroding. Whether physical therapists are prepared to accept a largely capitated system remains uncertain. The profession has typi- cally approached its role in the well-being of older adults through a fee-for-service system focused on treating disease. The profession has simultaneously ignored the underserved market of health promotion services for older adults with chronic illness. There is no doubt that the profession of physical therapy can provide knowledge and skills to support health maintenance and health promotion for older adults as a fundamental component of a restructured health care delivery system. The question is whether our profession is willing to move away from unsustainable economic models of health care delivery and adapt our expertise to fit the evolving organizational structure of health care financing for older adults.

REFERENCES 1. Institute of Medicine. Retooling for an aging

America: building the health care workforce. http://www.iom.edu/Reports/2008/Retooling- for-an-aging-America-Building-the-Health- Care-Workforce.aspx. Published April 11, 2008. Accessed February 21, 2014.

2. Wong R, Odom CJ, Barr JO. Building the phys- ical therapy workforce for an aging America. J Phys Ther Educ. 2014;28(2):12-21.

3. Werner CA. Census 2010 Brief C2010BR-09: The Older Population: 2010. Washington, DC: US Census Bureau; 2011. http://www.census. gov/prod/cen2010/briefs/c2010br-09.pdf. Ac- cessed February 21, 2014.

4. Vincent GK, Velkoff VA. The Next Four De- cades: The Older Population in the United States: 2010 to 2050. Washington, DC: US Census Bureau; 2010:P25-1138. https://www. census.gov/prod/2010pubs/p25-1138.pdf. Ac- cessed February 21, 2014.

5. Ward BW, Schiller JS. Prevalence of multiple chronic conditions among US adults: estimates from the National Health Interview Survey, 2010. Prev Chronic Dis. 2013;10:120203.

6. Erickson W, Lee C, von Schrader S. 2011 Dis- ability Status Report: United States. Ithaca, NY: Cornell University Employment and Disability Institute; 2012.

7. Sullivan KJ, Wallace JG Jr, O’Neil ME, et al. A vision for society: physical therapy as part- ners in the national health agenda. Phys Ther. 2011;91:1664-1672.

8. Toossi M. Labor force projections to 2020: a more slowly growing workforce. Monthly La- bor Review. Jan 2012:43-64.

9. Patient Protection and Affordable Care Act, Pub L No. 111-148, §2702, 124 Stat. 119, 318- 319 (2010).

10. Seeman TE, Merkin SS, Crimmins EM, Kar- lamangla AS. Disability trends among older Americans: National Health and Nutrition Ex- amination Surveys, 1988-1994 and 1999-2004. Am J Public Health. 2010;100:100-107.

11. Eldercare Workforce Alliance; National Co- alition on Care Coordination. Care coordi- nation and older adults issue brief. http:// www.eldercareworkforce.org/research/is- sue-briefs/research:care-coordination-brief. Accessed October 28, 2013.

12. Hirth V, Baskins J, Dever-Bumba M. Program of All-Inclusive Care (PACE): past, present and future. J Am Med Dir Assoc. 2009;10:155-160.

13. Kappas-Larson P. The Evercare story: re- shaping the health care model, revolution- izing long-term care. J Nurs Practitioners. 2008;4(2):132-136.

14. Rimmer JH. Health promotion for people with disabilities: the emerging paradigm shift from disability prevention to prevention of second- ary conditions. Phys Ther. 1999;79:495-502

15. Dibble L, Billinger S. On the front lines but not engaged in the battle. J Neurol Phys Ther. 2013; 37(2): 49-50.

16. Rimmer JH. Getting beyond the plateau: bridging the gap between rehabilitation and community-based exercise. Phys Med Rehabil. 2012;4:857-861.

17. Rimmer JH, Henley KY. Building the cross- road between inpatient/outpatient rehabilita- tion and lifelong community-based fitness for people with neurologic disability. J Neurol Phys Ther. 2013;37(2):72–77.

18. Rose DK, Schafer J, Conroy C. Extend- ing the continuum of care poststroke: creating a partnership to provide a communi- ty-based wellness program. J Neurol Phys Ther. 2013;37(2):78–84.

19. Ellis T, Motl RW. Physical activity behavior change in persons with neurologic disorders: overview and examples from Parkinson dis- ease and multiple sclerosis. J Neurol Phys Ther. 2013;37(2):85-90.

20. Guccione AA, Harwood KJ, Goldstein MS, Miller SC. Can “severity-intensity” be the con- ceptual basis of an alternative payment model for therapy services provided under Medicare? Phys Ther. 2011;91:1564-1569.

21. American Physical Therapy Association. Guide to Physical Therapist Practice. Rev 2nd ed. Al- exandria, VA: American Physical Therapy As- sociation; 2003.

22. Eldercare Workforce Alliance website. Who We Are. http://www.eldercareworkforce.org/ about-us/who-we-are/. Accessed December 1, 2013.

23. Partnership for Health in Aging. Multidis- ciplinary Competencies in the Care of Older Adults at the Completion of the Entry-level Health Professional Degree. http://american- geriatrics.org/pha/partnership_for_health_ in_aging/multidisciplinary_competencies. Accessed October 28, 2013.

24. American Geriatrics Society. Interdisciplin- ary Team Training in Geriatrics: An Essen- tial Component of Quality Healthcare for Older Adults. http://americangeriatrics.org/pha/ p a r t n e r s h i p _ f o r _ h e a l t h _ i n _ a g i n g / interdisciplinary_team_training_statement. Accessed October 28, 2013.

25. American Physical Therapy Association. In- novations in practice. http://www.apta.org/ InnovationsinPractice/. Accessed December 1, 2013.

26. American Physical Therapy Association. In- novation Summit: Collaborative Care Mod- els. http://www.apta.org/InnovationSummit/. Accessed December 1, 2013.

27. American Physical Therapy Association. Get ready for Innovation 2.0. PT in Motion News Now. http://apta.org/PTinMotion/News- Now/2013/12/20/Innovation2014/. Published December 20, 2013. Accessed December 21, 2013.

Learning What is Important: A Quality Improvement Initiative to Enhance Patient-Centred Care in Home Care

Patricia Millera, Caroline Gillb, Kathy Mazzab, C�elynne Pilonb, and Melissa Hillb

aIAHS Room 403, School of Rehabilitation Science, McMaster University, Hamilton, Ontario, Canada; bCBI Health Group West Tower, Toronto, Ontario, Canada

ABSTRACT Aim: A quality improvement initiative was undertaken to increase the utilization of a new tool designed to facilitate the provision of patient-centred care in the homecare setting. Methods: The tool, entitled Life Through My Eyes (LTME), is completed voluntarily by the patient or a family member. In order to personalize the patient’s care, it captures information about what is important to the patient and ways to make the patient feel comfortable. Patients and families played an inte- gral role in the Plan, Do, Study, Act cycle used to introduce the tool into practice. Results: Patients and family members (n¼ 19) and personnel (n¼ 7) offered feedback that directed revisions to the tool’s format, and additional strategies were implemented to increase personnel’s familiarity with the tool. Conclusion: Improvements in the format and in the implemen- tation process for the LTME tool were identified through a QI initiative, and the revised tool has now been distrib- uted broadly.

ARTICLE HISTORY Received 23 August 2018 Accepted 2 January 2019

KEYWORDS Quality improvement; home care services; communication


Patient-centred care, which may also be referred to as client-centred care, is endorsed by numerous international health organizations and associa- tions, and ensures that the patients’ interests are integrated into the care provided and into the healthcare decisions made in partnership with the healthcare provider.1,2 Across the various definitions for a patient-centred approach to care, there is “a strong emphasis on a collaborative approach or partnership, respect for the client, facilitating choice and involving the client in determining the occupational goals that emerge from his or her

CONTACT Pat Miller pmiller@mcmaster.ca IAHS Room 403, School of Rehabilitation Science, McMaster University, 1400 Main Street West, Hamilton, Ontario, Canada L8S 1C7 �C�elynne Pilon was an employee at CBI Health Group at the time the quality improvement initiative was con- ducted. She has recently moved to a new job at MD Financial Management, 1870 Alta Vista Drive, Ottawa, Ontario, Canada K1G 6R7. This material was presented in part as a poster at Hospice Palliative Care Ontario (HPCO) in April 2017, and as a presentation at the Health Shared Services Ontario conference in June 2017, and at the Canadian Hospice Palliative Care Association Conference (CHPCA) in September 2017. � 2019 Taylor & Francis Group, LLC

PHYSICAL & OCCUPATIONAL THERAPY IN GERIATRICS 2019, VOL. 37, NO. 1, 3–15 https://doi.org/10.1080/02703181.2019.1567643http://crossmark.crossref.org/dialog/?doi=10.1080/02703181.2019.1567643&domain=pdfhttps://doi.org./10.1080/02703181.2019.1567643http://www.tandfonline.com

choices”.3 The provision of patient-centred care has been shown to posi- tively influence clinical outcomes, including patient satisfaction and self- management.4 Furthermore, patient-centred care is becoming a recognized quality indicator on which organizations should be evaluated.4

Many authors have noted the importance of getting to know your patient, and making an effort to understand what things are important to them. In a recent concept mapping exercise undertaken in Australia to identify the requirements of patient-centred care, involving stakeholders including patients, carers, health professionals, and managers, “knowing and valuing the patient” was one of the clusters identified. It fell under the domain of “Humanity and partnership”.5 Similarly, when Sumsion and Law undertook a critical review of the literature to identify the key elements of client-centred practice, they identified the overarching theme of power, along with the additional themes of listening and communicating, partner- ship, choice, and hope.3 One of the practice questions provided by Sumsion and Law to consider when offering patient-centred care is “Do I facilitate a process of ensuring my client’s voice is heard?”3 Thus, it is incumbent upon both individuals and organizations to employ strategies to better understand the wishes of the patient which can, in turn, facilitate the provision of patient-centred care regardless of where the person receives care along the continuum of care. There is an increasing number of individuals receiving care in their

home which enables them to receive the care they need while living with independence and dignity.6 Home care is defined as “an array of services for people of all ages, provided in the home and community setting, that encompasses health promotion and teaching, rehabilitation, support and maintenance, social adaptation and integration, end-of-life care, and sup- port for family caregivers”.7 Home care services, based on individual need, are provided to individuals of all ages with both acute and chronic condi- tions, including adults with disabilities and the frail elderly.6 Indeed, the majority of patients (63%) receiving home care services in the province of Ontario, Canada, in 2015/2016 were 65 years of age or older.8 In keeping with the trend towards patient-centred care across the healthcare con- tinuum, it is not surprising that one of the six principles of the Harmonized Principles of Home Care of the Canadian Home Care Association, designed to support consistency and equity among those receiving home care services, is “Client- and Family- Centred Care”.9

The Ontario division of CBI Home Health (CBI Home Health-Ontario) provides a range of health care services, including personal care, nursing and therapy services to persons living at home, in long-term care facilities, hospi- tals, and other settings.10 Personnel providing direct care includes both regu- lated healthcare providers (e.g., registered nurses, physical and occupational


therapists) and unregulated healthcare providers (e.g., personal support workers) who are supervised by registered nurses. As a Registered Nurses’ Association of Ontario Best Practice Spotlight OrganizationTM,11 CBI Home Health- Ontario has implemented the person- and family-centred care best practice guideline, among others.12 Recently, the Life Through My Eyes (LTME) tool was developed and introduced as a strategy to improve patient- centred care within the homecare setting. It was anticipated that the use of this tool could enhance the provision of more personalized care across per- sonnel, services, and regions by increasing CBI personnel’s awareness of what was important to the patient. The purpose of this quality improvement (QI) initiative, using Plan-Do-Study-Act (PDSA) cycle,13 was to increase the utilization of the new LTME tool. Below we describe the iterative process of developing and testing the new tool through the four stages of the PSDA cycle, and we outline the changes made in response to feedback from patients, family, and CBI personnel. The results of the QI initiative directed changes to the format of the tool and to the process by which the LTME tool was introduced to patients, families, and personnel in one province prior to being distributed more broadly.


The PDSA cycle is one the most commonly methodologies used in health- care.13 It engages a small-scale, iterative approach to test interventions and build confidence for change on a larger scale.14 Because it occurs on a small scale, there is minimal risk to the patient and the organization, and the process offers flexibility to respond to feedback while developing solu- tions.14 In the Plan stage, the new LTME tool was developed by an inter- disciplinary committee that also included a patient advisor. In the Do stage, the tool was pilot-tested with a small number of patients, and revised prior to being introduced into practice with selected patients and families (i.e., a small group of volunteers) in several regions in one province. In the Study stage, feedback was solicited from those patients and their families and the respective CBI personnel using short surveys. In the Act stage, both the content and processes regarding the use of the LTME tool were modified, prior to it being introduced provincially. The Hamilton Integrated Research Ethics Board confirmed that we did not require formal ethical approval because this was a QI project.

Plan Stage (2015–March 2016)

The LTME tool is a short questionnaire completed voluntarily by the patient and/or their family. It was developed by the national


interdisciplinary CBI Patient- and Family-Centred Care (PFCC) Committee that included organizational leaders, direct care personnel and a patient advisor. The patient advisor was a parent of a patient who had been receiv- ing care for several years. The role of the committee is to promote and monitor activities related to PFCC. Integrating PFCC as a tenet of care aligns with CBI values of ‘We Really Care, We Make It Happen, We Aim Higher and We Do Great Work Together’.15 The LTME tool was derived from similar tools, including one by Janes.16

The tool provides an opportunity for the patient or their family to pro- vide a short summary about people or things that are important to them, and activities that can be done by CBI personnel in order to provide indi- vidualized care and comfort. Family members were included because for many older individuals, the family plays a critical role in the patient’s care in the homecare setting. Indeed, in many instances, the CBI personnel sup- plement the care the family provides to their family member. The input of the family is especially critical when the patient’s cognitive or physical sta- tus limits their ability to make their own needs known, and/or to complete the tool. The tool includes five questions/items intended to gather import- ant personal information from the patient used to direct individualized care provided by CBI personnel. They are: “I would like to share with you the most important connections and relationships in my life (e.g., people, pets, beliefs, traditions, places)”, “I will enjoy my day if I am comfortable, so please don’t forget (glasses, lotion, hearing aids, etc.)”, “If I become frightened or upset, these things may help me:”, “Some of the favourite things I enjoy are (e.g., music, movies, TV shows, books, magazines, food or drinks, activities)”, and “Here are a few more things I’d like you to know” (Appendix 1). The patient or their family member writes the answers to these five questions/items on the form, or alternatively they may request the assistance of the CBI personnel to record their answers. The completed LTME tool then becomes part of the care documents that remain in the home with the patient and are available for review by every care provider.

Do Stage (April 2016–February 2017)

The initial version of the LTME tool developed by the PFCC Committee was introduced in one location in Ontario in April 2016 where CBI person- nel provided nursing and personal support services. After several months, members of the PFCC committee recognized that utilization of the tool was limited and they identified the need to initiate a QI initiative to iden- tify the barriers facing patients and personnel which had resulted in the lower than expected acceptance of the LTME tool.


By using a structured QI methodology, the PDSA cycle,13 the time and effort of a smaller working group of the PFCC committee, namely the LTME Quality Team which included three organizational leaders (CG, KM, CP), brought additional rigour and focus to the initiative. They designed a series of questions to use to seek feedback from both patients and their families, and CBI personnel, in a small number of selected jurisdictions. Commencing in September 2016, CBI personnel shared the tool with inter- ested patients and/or their family members who were receiving nursing, therapy, and personal support services in four jurisdictions in southwestern Ontario. Following approval from the funders (i.e., Community Care Access Centres), CBI personnel obtained consent from patients or their family member to be contacted by a member of the LTME Quality Team approximately two weeks after the new tool had been introduced as part of the patient’s care.

Study Stage (September 2016–February 2017)

The LTME tool was shared with 49 patients of all ages over a seven month period. All patients or their family members agreed to complete the tool as part of their care, and to subsequently answer a series of short questions about the new tool over the phone. Three members of the LTME Quality Team (CG, KM, CP) conducted the short telephone survey (approximately 20minutes in length) using a semi-structured interview format, seeking feed- back about the tool and capturing verbatim responses from the patient or family member when possible. The survey included questions regarding the time it took to complete the form, and questions about the tool’s content, format and usefulness. Examples of questions were: “What did you think about the length of time it took to complete the document?” “Were you comfortable sharing information to all of the questions?” “Do you feel there was anything missing from the document?” Additionally, a short online sur- vey was circulated by email to CBI personnel who had distributed the tool to their patients (e.g., personal support workers, supervisors, nurses and therapists). This survey included questions about its content, format, and usefulness. Examples of questions were: “Based on your impressions, how much ease or difficulty did you perceive the client had when filling out the document?” “Did the use of this tool affect your practice?” “What has been the biggest surprise in the use of this tool?” The responses of patient, family members, and personnel were anonymized and analyzed by the evaluation team (PM, CC, KM, CP, MH) using qualitative content analysis.17

After the tool had been made available for several months, the LTME Quality Team recognized that the number of patient respondents was lower than expected. In keeping with iterative PDSA methodology, strategies were


introduced to address this deficiency. The LTME Quality Team developed resources to highlight the role and key features of the LTME tool. This included the distribution of a summary sheet for personal support workers which highlighted the intent and the value of using the tool, and a coach- ing session conducted via teleconference for the supervisors to encourage greater uptake of the tool among their staff. Twenty patients or family members, of the 49 patients who received the

LTME tool, completed the telephone survey over seven months (i.e., 41% response rate). Feedback was not received from the other 29 patients who received the tool because they did not complete the tool, or they were unavailable to answer the survey questions (e.g., admitted to hospital, reported that they could not remember the tool well enough), or they were unable to be contacted despite repeated attempts. The results associated with 19 patients of the 20 patients who were in middle or late adulthood are reported, and the results from the family member of one younger patient were excluded. The sample included 12 female and 7 male patients, com- prised of patients, and spouses and adult children of the patients (Table 1) with patients’ mean age of 78 years (range 53–93). Five patients were in mid- dle adulthood, the 14 others were in late adulthood (Table 2). Patients in middle and late adulthood were considered together because they were receiving similar care and therapy, including assistance with personal care (e.g., bathing, feeding) or requiring therapy or social work services following discharge from hospital (e.g., exercise prescription, safety and support in the home). Fifty-eight percent (n¼ 11) of patients had been receiving care for more than a month, the others were considered to be “new” to the service. Respondents reported 16minutes as the average time to complete the

form, (range 3 to 60minutes). Seventeen of the respondents (90%) reported that the amount of time to complete the form was acceptable. There was a unanimous positive response (n¼ 17/19), with responses missing from two patients, to the question “Do you feel that CBI Home Health should con- tinue asking clients to complete the document?”

Feedback from patients and their families

Seventeen of the 19 respondents (89%) either “agreed” or “strongly agreed” that they were comfortable answering the questions on the tool. Both

Table 1. Relationship of questionnaire respondents to patient (n¼ 19). Respondent

Patient him/herself 10 Son/daughter of patient 4 Spouse of patient 3 Other relative 1 Caregiver 1


patient and family members indicated they appreciated the importance of sharing personal information so that care providers were able to provide more personalized care.

� “I’m fine with sharing, [the information] helps people coming in to care for me to know me better.” (58 year old female client)

� “I would share anything with someone who came here. It’s all for helping me.” (62 year old male client)

� “I think it is essential to share the information. I have no problem with sharing. It’s a disease, and we’re living with it, and anything that can help us, we’re game to try.” (wife of 82 year old male client)

Various benefits of the LTME tool were noted by the respondents. The use of the tool was noted to prevent the unnecessary repetition of key personal information including preferences with changing personnel. Some respondents noted they appreciated the opportunity to discuss comfort measures.

� “They’re [questions] all good, and what is not covered in the questions can be covered in the last one about anything they would like to share.” (Wife of 76 year old male client)

� “I’m dependent on my family, so that question [about important relation- ships] was the most important.” (93 year old female client)

� “ … [the form] increases your comfort level and makes you believe that CBI is concerned about your well-being.” (81 year old male client)

Some respondents had suggestions about how to improve the tool or its implementation. While most felt the questions were sufficient, one noted there was no way to know if the care providers read the document. Another noted this was an important tool to use with new personnel. Others requested more space to include additional information.

“I think it will [be useful] but I want to add more about how she expresses herself- in other words, ‘Treat me with respect, I’m still in here.’” (Daughter of 88 year old female client)

Feedback from personnel

Responses, including both benefits and challenges, were received from seven CBI personnel: two personal support workers, two supervisors, two

Table 2. Ages of patients (n¼ 19). n Mean (range)

Middle adulthood 5 59 (53–63) Late adulthood 14 84 (74–93)


therapists and one nurse. Most identified the tool’s value for new patients, and there were several specific examples of how information in the tool had unexpectedly enhanced care for longstanding patients.

� “It reinforces what I know about the client, and adds details like “favourites” that I can reinforce.” (Registered Practical Nurse (RPN))

� “[The] client got hearing aides and for three weeks we didn’t know about it, until we introduced this tool and the family wrote “Please don’t forget to use the hearing aids.” It was really surprising because for so long, we didn’t know the hearing aides were present.” (RPN in a Supervisor role)

Act stage (March–October 2017)

Based on the feedback from patients, their families, and personnel, the PFCC Committee made further changes to the content of the LTME tool and the process for its integration into practice. The changes made were as follows. The purpose of the LTME tool was explicitly stated on the form: “We would like to get to know you and learn what is most important to you.” New sections were added so that patients could provide additional information about past events as well as their current situation. Greater space was made for additional personal details. To increase accountability, each CBI personnel who provides care is required to sign and date the form to indicate they have reviewed it in order to become more familiar with the preferences and needs of the patient. This is also to ensure that the patient or their family member does not have to provide their story more than once (Appendix 1).

New cycle- plan stage (November 2017 onwards)

Building on the results of the first PDSA cycle, a second PDSA cycle has been implemented with the introduction of the LTME tool throughout the province. A ‘train the trainer’ webinar was developed and delivered to all provincial PFCC leaders. Coaching techniques include an explanation of the benefits of LTME, the ‘why’ of PFCC and emphasizing the ‘win-win’ for patients and personnel. Members of the PFCC Committee also recog- nized the need for additional training to optimize the successful integration of the new tool into the homecare setting. A specific training program was developed for supervisors to use when coaching frontline personnel. It includes information on the use of PFCC principles and outlines strategies for optimizing patient-centred care that includes the LTME tool. Furthermore, the tool and the results of the PDSA cycle have been

shared with the clinical leaders in all provinces. The long term goal is to


formally evaluate the use of the LTME tool using a larger sample of patients and families, including different services across a range of locations throughout the country.


Feedback from patients, their families and CBI personnel through the PDSA cycle has lead to changes in both the format and implementation of the LTME tool. The PSDA methodology, with its iterative cycles, was well suited to this QI initiative. Members of the LTME Quality Team had the opportunity to respond quickly to implement strategies within a limited number of jurisdictions in order to increase uptake of the tool, and to develop short surveys to use to gather feedback about its acceptability and usage. The results of these surveys then guided changes and improvements to the tool and its implementation. The LTME tool, which is a concrete strategy by which personnel can

ensure that the patient’s preferences are known, would fall under the “Listening and Communicating” domain identified by Sumsion and Law.3

While the sample size was small, the patient and family members who offered feedback validated the importance of sharing these personal details with the care providers, and CBI personnel shared a number of specific examples of how the use of the LTME tool improved the care or comfort of patients. Indeed, physical comfort, a dimension of patient-centred care, has been shown to be strongly correlated with the patients’ overall ratings of the quality of care they received.4 While our results may be based on the feedback of only those who agreed to use the tool and liked it, this initia- tive has indicated that there is a sample of patients for whom CBI person- nel will be able to use the LTME tool to gain personal information about the client which can, in turn, facilitate the provision of patient-cen- tred care. Patients and their families played an integral role in design and revision

of the LTME tool. A patient advisor was part of the CBI PFCC Committee that created the initial form and directed this QI initiative. Feedback from patients and their family members was a critical source of feedback that directed the revision of the LTME tool, which, in turn, can enhance the ability of CBI personnel to provide personalized care and comfort for patients. Baker and colleagues identify that patient engagement in QI initia- tives can yield many benefits, including their role here to problem-solve and co-design improvements to care.18 They suggest that involvement of patients in such quality improvement may help establish a platform for broader engagement in patient care and organizational decision-making.18



The LTME tool, designed to enhance patient-centred care in the homecare setting, was developed and implemented under the direction of the CBI PFCC Committee with patient engagement being an integral aspect of the process. Guided by a PDSA cycle, and based on feedback from patients, their families, and personnel, changes were made to the tool to improve it ability to capture information about what is important to the patient and ways to for personnel to make the patient feel comfortable. The results of this QI initiative, introduced in selected regions in one province, directed changes to the tool’s format and to the processes related to its use, prior to its introduction provincially, with national distribution planned.


Members of the LTME Quality Team sincerely thank the patients, their families, and per- sonnel who shared their feedback.

Disclosure Statement

Patricia Miller received payment as a consultant from CBI regarding the implementation of this quality improvement initiative and for assistance in the preparation of material for presentation and this manuscript. Caroline Gill, Kathy Mazza, C�elynne Pilon, and Melissa Hill were employees of CBI Health at the time of the quality improvement initiative. Caroline Gill and Kathy Mazza received funds reimbursing them for attending a profes- sional conference to present this material in part.


1. Montague T, Gogovor A, Aylen J, et al. Patient-centred care in Canada: key compo- nents and the path forward. Healthc Q. 2017;20(1):50–56.

2. McCormack B, Borg M, Cardiff S. et al. Person-centredness – the ’state’ of the art. Int Pract Dev J. 2015;5 (Suppl.1):1–15.

3. Sumsion T, Law M. A review of evidence on the conceptual elements informing cli- ent-centred practice. Can J Occup Ther. 2006;73(3):153–162.

4. Rathert C, Wyrwich M, Boren S. Patient-centered care and outcomes: a systematic review of the literature. Med Care Res Rev. 2013;70(4):351–379. doi.org/10.1177/ 1077558712465774

5. Ogden K, Barr J, Greenfield D. Determining requirements for patient-centred care: a participatory concept mapping study. BMC Health Serv Res. 2017;17:780. http://doi. org/10.1186/s12913-017-2741-y

6. Yakerson A. Home care in Ontario: perspectives on equity. Int J Health Serv. 2018; 49(2):260–272. doi.org/10.1177/0020731418804403

7. Home care in Canada: Advancing quality improvement and integrated care. Canadian Home Care Association. Published May 2015. http://www.cdnhomecare.ca/ media.php?mid¼4328 Accessed November 21, 2018.

12 P. MILLER ET AL.https://doi.org/10.1177/1077558712465774https://doi.org/10.1177/1077558712465774http://doi.org/10.1186/s12913-017-2741-yhttp://doi.org/10.1186/s12913-017-2741-yhttps://doi.org/10.1177/0020731418804403http://www.cdnhomecare.ca/media.php?mid=4328http://www.cdnhomecare.ca/media.php?mid=4328

8. Facts and Figures: Publicly Funded Home Care. Home Care Ontario. https://www. homecareontario.ca/home-care-services/facts-figures/publiclyfundedhomecare Accessed November 21, 2018.

9. Backgrounder: Harmonized principles for home care. Canadian Home Care Association. Published April 2016. http://www.cdnhomecare.ca/media.php?mid¼4650 Accessed November 21, 2018.

10. CBI Home Health. https://www.cbi.ca/web/home-health Accessed November 21, 2018 11. Registered Nurses’ Association of Ontario. Best Practice Spotlight Organizations.

http://rnao.ca/bpg/bpso Accessed November 21, 2018 12. Registered Nurses’ Association of Ontario. Person- and Family-Centred Care (2015).

Toronto, ON. http://rnao.ca/bpg/guidelines/person-and-family-centred-care Accessed November 21, 2018.

13. Varkey P, Reller K, Resar RK. Basics of quality improvement in health care. Mayo Clin Proc. 2007;82 (6): 735–739. doi.org/10.4065/82.6.735

14. Taylor M, McNicholas C, Nicolay C, Darzi A, Bell D, Reed J. Systematic review of the application of the plan–do–study–act method to improve quality in healthcare. BMJ Qual Saf. 2013;23(4): 290–298. doi.org/10.1136/bmjqs-2013-001862

15. CBI Home Health, Welcome Home. https://www.cbi.ca/web/home-health/welcome- home Accessed November 21, 2018.

16. Janes, N. “Getting to know me” In Registered Nurses Association of Ontario (2004). Caregiving Strategies for Older Adults with Delirium, Dementia and Depression. (Appendix 0, p. 156) http://rnao.ca/sites/rnao-ca/files/Caregiving_Strategies_for_ Older_Adults_with_Delirium_Dementia_and_Depression.pdf Accessed November 21, 2018.

17. Hsieh H, Shannon S. Three approaches to qualitative content analysis. Qual Health Res. 2005;15 (9):1277–1288. doi.org/10.1177/1049732305276687

18. Baker G, Fancott C, Judd M, O’Connor P. Expanding patient engagement in quality improvement and health system redesign: three Canadian case studies. Healthc Manage Forum 2016;29(5):176–182. doi.org/10.1177/0840470416645601

PHYSICAL & OCCUPATIONAL THERAPY IN GERIATRICS 13https://www.homecareontario.ca/home-care-services/facts-figures/publiclyfundedhomecarehttps://www.homecareontario.ca/home-care-services/facts-figures/publiclyfundedhomecarehttp://www.cdnhomecare.ca/media.php?mid=4650https://www.cbi.ca/web/home-healthhttp://rnao.ca/bpg/bpsohttp://rnao.ca/bpg/guidelines/person-and-family-centred-carehttps://doi.org/10.4065/82.6.735https://doi.org/10.1136/bmjqs-2013-001862https://www.cbi.ca/web/home-health/welcome-homehttps://www.cbi.ca/web/home-health/welcome-homehttp://rnao.ca/sites/rnao-ca/files/Caregiving_Strategies_for_Older_Adults_with_Delirium_Dementia_and_Depression.pdfhttp://rnao.ca/sites/rnao-ca/files/Caregiving_Strategies_for_Older_Adults_with_Delirium_Dementia_and_Depression.pdfhttps://doi.org/10.1177/1049732305276687https://doi.org/10.1177/0840470416645601

Appendix 1



Copyright of Physical & Occupational Therapy in Geriatrics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.

  • Abstract
    • Introduction
    • Methods
      • Plan Stage 2015March 2016
      • Do Stage April 2016February 2017
      • Study Stage September 2016February 2017
      • Feedback from patients and their families
      • Feedback from personnel
      • Act stage MarchOctober 2017
      • New cycle- plan stage November 2017 onwards
    • Discussion
    • Conclusion
    • Acknowledgements
    • Disclosure Statement
    • References
      • mkchap1567643_s1015_sec


Course CodeClass CodeAssignment TitleTotal Points
HLT-490VHLT-490V-O500Reviewing the Literature110.0
CriteriaPercentageUnsatisfactory (0.00%)Less Than Satisfactory (65.00%)Satisfactory (75.00%)Good (85.00%)Excellent (100.00%)CommentsPoints Earned
Summary of Clinical Issue2.0%Summary of clinical issue is omitted.The clinical issue is only partially discussed.The clinical issue is generally outlined. More information or support is needed.The clinical issue is described. Minor detail is needed for accuracy or clarity.The clinical issue is succinct and thoroughly described.
PICO Questions3.0%The PICO question for the proposed topic is omitted.NANANAThe PICO question for the proposed topic is stated.
Literature Evaluation Table15.0%The table is incomplete or fails to meet the assignment criteria overall.Fewer than 10 articles in support of the proposed topic are presented. Fewer than six articles are peer reviewed or research based. The criteria for this assignment are only partially met.Ten to 12 articles in support of the proposed topic are presented. One or two articles are not peer reviewed. Only six or seven articles are research based. The criteria are generally met for each article. There are some omissions or inaccuracies.Ten to 12 peer-reviewed articles in support of the proposed topic are presented. At least eight of the articles are research based. The criteria are adequate and met for each article.Ten to 12 peer-reviewed articles in support of the proposed topic are presented. Eight or more of the articles are research based. The criteria are complete, informative, and fully met for each article.
Analysis of Literature: Summary of Purpose15.0%The analysis of the literature is incomplete.The appraisal of each article is inaccurate or contains omissions. The overall summary analysis presented does not demonstrate support for the PICO question.Each article is appraised, and the purpose is generally summarized. Some aspects are vague. The overall summary analysis of the research demonstrates general support for the PICO question. More information or support is needed.Each article is appraised, and the purpose is discussed. The summary is informative and concise for each article. The overall summary analysis of the research demonstrates support for the PICO question. Some detail is needed for support or accuracy.Each article is clearly appraised, and the purpose is detailed and concise. The summary is informative and concise for each article. The overall summary analysis of the research demonstrates compelling support for the PICO question.
Analysis of Literature: Relation of Research to Proposed Project Topic15.0%How each article or the research relates to the selected health care problem or issue is not discussed. The narrative does not support the selected problem or issue.How each article or the research relates to the selected health care problem or issue is only partially discussed. The narrative only partially supports the selected problem or issue.A summary for how each article or the research relates to the selected health care problem or issue is presented. Some aspects are vague. The narrative generally supports the selected problem or issue. More information or support is needed.How each article or the research relates to the selected health care problem or issue is described. The narrative establishes support for the selected problem or issue. Some detail is needed for support or accuracy.A description for how each article or the research relates to the selected health care problem or issue is detailed. The narrative is thorough, well supported, and establishes support for the selected problem or issue.
Analysis of Literature: Explanation of How Research Evidence Supports Proposed Intervention20.0%An explanation for how the evidence in the article or the research supports the proposed intervention is not presented. The evidence does not support the proposed interventionThe explanation for how the evidence in the article or the research supports the proposed intervention is incomplete. The evidence only partially supports the proposed intervention.A summary for how the evidence in the article or the research supports the proposed intervention is presented. The evidence generally supports the proposed intervention.An explanation for how the evidence in the article or the research supports the proposed intervention is presented. The evidence supports the proposed intervention.A well-supported explanation for how the evidence in the article or the research supports the proposed intervention is presented. The evidence demonstrates strong support for the proposed intervention.
Organization, Effectiveness, and Format30.0%
Thesis Development and Purpose7.0%Paper lacks any discernible overall purpose or organizing claim.Thesis is insufficiently developed or vague. Purpose is not clear.Thesis is apparent and appropriate to purpose.Thesis is clear and forecasts the development of the paper. Thesis is descriptive and reflective of the arguments and appropriate to the purpose.Thesis is comprehensive and contains the essence of the paper. Thesis statement makes the purpose of the paper clear.
Argument Logic and Construction8.0%Statement of purpose is not justified by the conclusion. The conclusion does not support the claim made. Argument is incoherent and uses noncredible sources.Sufficient justification of claims is lacking. Argument lacks consistent unity. There are obvious flaws in the logic. Some sources have questionable credibility.Argument is orderly but may have a few inconsistencies. The argument presents minimal justification of claims. Argument logically, but not thoroughly, supports the purpose. Sources used are credible. Introduction and conclusion bracket the thesis.Argument shows logical progression. Techniques of argumentation are evident. There is a smooth progression of claims from introduction to conclusion. Most sources are authoritative.Clear and convincing argument presents a persuasive claim in a distinctive and compelling manner. All sources are authoritative.
Mechanics of Writing (includes spelling, punctuation, grammar, language use)5.0%Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used.Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied.Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed.Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech.Writer is clearly in command of standard, written, academic English.
Paper Format (use of appropriate style for the major and assignment)5.0%Template is not used appropriately, or documentation format is rarely followed correctly.Appropriate template is used, but some elements are missing or mistaken. A lack of control with formatting is apparent.Appropriate template is used. Formatting is correct, although some minor errors may be present.Appropriate template is fully used. There are virtually no errors in formatting style.All format elements are correct.
Documentation of Sources (citations, footnotes, references, bibliography, etc., as appropriate to assignment and style)5.0%Sources are not documented.Documentation of sources is inconsistent or incorrect, as appropriate to assignment and style, with numerous formatting errors.Sources are documented, as appropriate to assignment and style, although some formatting errors may be present.Sources are documented, as appropriate to assignment and style, and format is mostly correct.Sources are completely and correctly documented, as appropriate to assignment and style, and format is free of error.
Total Weightage100%

Reviewing the Literature

Student Name:

Summary of Clinical Issue (200-250 words):

PICO Question:

Part 1: Literature Evaluation Table

Locate a minimum of 10-12 peer-reviewed articles that support your proposed topic. Eight of the 10-12 peer-reviewed articles must be research-based (i.e., a study which is qualitative, quantitative, descriptive, or longitudinal).

Begin your search for literature by utilizing the databases located in the GCU Library. Contact your instructor, the librarian, or library staff for additional researching tips and keyword suggestions.

Preview each of the articles chosen by reading the article abstracts and summaries. Article abstracts and summaries provide a concise description of the topic, research outcomes, and significance of findings.

CriteriaArticle 1Article 2Article 3
APA-Formatted Article Citation With Permalink
How Does the Article Relate to the PICO Question?
Quantitative, Qualitative (How do you know?)
Purpose Statement
Research Question
Setting(Where did the study take place?)
Key Findings of the Study
Recommendations of the Researcher
CriteriaArticle 4Article 5Article 6
APA-Formatted Article Citation With Permalink
How Does the Article Relate to the PICO Question?
Quantitative, Qualitative (How do you know?)
Purpose Statement
Research Question
Setting(Where did the study take place?)
Key Findings of the Study
Recommendations of the Researcher
CriteriaArticle 7Article 8Article 9
APA-Formatted Article Citation With Permalink
How Does the Article Relate to the PICO Question?
Quantitative, Qualitative (How do you know?)
Purpose Statement
Research Question
Setting(Where did the study take place?)
Key Findings of the Study
Recommendations of the Researcher
CriteriaArticle 10Article 11Article 12
APA-Formatted Article Citation With Permalink
How Does the Article Relate to the PICO Question?
Quantitative, Qualitative (How do you know?)
Purpose Statement
Research Question
Setting(Where did the study take place?)
Key Findings of the Study
Recommendations of the Researcher

Part 2: Analysis of Literature

In 750-1,000 words, write a review of the literature. This section should comprehensively summarize previous research related to your topic and demonstrate support for your PICO question.

Remember, you are building an argument to for your proposed evidence-based project; this is not simply an article review.

Appraise each article and answer the following questions for each (one to two sentences is sufficient to answer each question):

0. Summarize the purpose of the article or research.

0. Describe how the article or research relates to the health care problem or issue you selected.

0. Explain how the evidence in the article or research supports your proposed intervention.

© 2021. Grand Canyon University. All Rights Reserved.



Typing Template for APA Papers: A Sample of Proper Formatting for APA Style

Student A. Sample

College Name, Grand Canyon University

Course Number: Course Title

Instructor’s Name



Assignment Due Date

Typing Template for APA Papers: A Sample of Proper Formatting for APA Style

This is an electronic template for papers written according to the style of the American Psychological Association (APA, 2020) as outlined in the seventh edition of the Publication Manual of the American Psychological Association. The purpose of the template is to help students set the margins and spacing. Margins are set at 1 inch for top, bottom, left, and right. The text is left-justified only; that means the left margin is straight, but the right margin is ragged. Each paragraph is indented 0.5 inch. It is best to use the tab key to indent, or set a first-line indent in the paragraph settings. The line spacing is double throughout the paper, even on the reference page. One space is used after punctuation at the end of sentences. The font style used in this template is Times New Roman and the font size is 12 point. This font and size is required for GCU papers.

The Section Heading

The heading above would be used if you want to have your paper divided into sections based on content. This is a Level 1 heading, and it is centered and bolded, and the initial word and each word of four or more letters is capitalized. The heading should be a short descriptor of the section. Note that not all papers will have headings or subheadings in them. Papers for beginning undergraduate courses (100 or 200 level) will generally not need headings beyond Level 1. The paper title serves as the heading for the first paragraph of the paper, so “Introduction” is not used as a heading.

Subsection Heading

The subheading above would be used if there are several sections within the topic labeled in a first level heading. This is a Level 2 heading, and it is flush left and bolded, and the initial word and each word of four or more letters is capitalized.

Subsection Heading

APA dictates that you should avoid having only one subsection heading and subsection within a section. In other words, use at least two subheadings under a main heading, or do not use any at all. Headings are used in order, so a paper must use Level 1 before using Level 2. Do not adjust spacing to change where on the page a heading falls, even if it would be the last line on a page.

The Title Page

When you are ready to write, and after having read these instructions completely, you can delete these directions and start typing. The formatting should stay the same. You will also need to change the items on the title page. Fill in your own title, name, course, college, instructor, and date. List the college to which the course belongs, such as College of Theology, College of Business, or College of Humanities and Social Sciences. GCU uses three letters and numbers with a hyphen for course numbers, such as CWV-101 or UNV-104. The date should be written as Month Day, Year. Spell out the month name.

Formatting References and Citations

APA Style includes rules for citing resources. The Publication Manual (APA, 2020) also discusses the desired tone of writing, grammar, punctuation, formatting for numbers, and a variety of other important topics. Although APA Style rules are used in this template, the purpose of the template is only to demonstrate spacing and the general parts of the paper. GCU has prepared an APA Style Guide available in the Student Success Center and on the GCU Library’s Citing Sources in APA guide (https://libguides.gcu.edu/APA) for help in correctly formatting according to APA Style.

The reference list should appear at the end of a paper. It provides the information necessary for a reader to locate and retrieve any source you cite in the body of the paper. Each source you cite in the paper must appear in your reference list; likewise, each entry in the reference list must be cited in your text. A sample reference page is included below. This page includes examples of how to format different reference types. The first reference is to a webpage without a clear date, which is common with organizational websites (American Nurses Association, n.d.). Next is the Publication Manual referred to throughout this template (APA, 2020). Notice that the manual reference includes the DOI number, even though this is a print book, as the DOI was listed on book, and does not include a publisher name since the publisher is also the author. A journal article reference will also often include a DOI, and as this article has four authors, only the first would appear in the in-text citation (Copeland et al., 2013). Government publications like the Treatment Improvement Protocol series documents from the Center for Substance Abuse Treatment (2014) are another common source found online. A book without a DOI is the last example (Holland & Forrest, 2017).


American Nurses Association. (n.d.). Scope of practice. https://www.nursingworld.org/practice-policy/scope-of-practice/

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

Center for Substance Abuse Treatment. (2014). Improving cultural competence (HHS Publication No. 14-4849). U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration. https://www.ncbi.nlm.nih.gov/books/NBK248428/

Copeland, T., Henderson, B., Mayer, B., & Nicholson, S. (2013). Three different paths for tabletop gaming in school libraries. Library Trends, 61(4), 825–835. https://doi.org/10.1353/lib.2013.0018

Holland, R. A., & Forrest, B. K. (2017). Good arguments: Making your case in writing and public speaking. Baker Academic.

Sources for capstone research project

Evidence-based National Consensus: Recommendations for Physiotherapy Management in COVID-19 in Acute Care Indian Setup


Summary of respiratory rehabilitation and physical therapy guidelines for patients with COVID-19 based on recommendations of World Confederation for Physical Therapy and National Association of Physical Therapy





D a








a t t i 1 t y u i t g 1 t g


h 0

Journal of Health Economics 57 (2018) 60–74

Contents lists available at ScienceDirect

Journal of Health Economics

jo u r n al homep age: www.elsev ier .com/ locate /econbase

ealth care expenditures, age, proximity to death and morbidity: mplications for an ageing population

aniel Howdona,∗, Nigel Riceb,c

Department of Economics, Econometrics and Finance, University of Groningen, Duisenberg Building, Nettelbosje 2, 9747AE Groningen, Netherlands Centre for Health Economics, University of York, York YO10 5DD, UK Department of Economics and Related Studies, University of York, York YO10 5DD, UK

r t i c l e i n f o

rticle history: eceived 18 April 2016 eceived in revised form 10 October 2017 ccepted 1 November 2017 vailable online 15 November 2017

EL classification: 51


a b s t r a c t

This paper uses Hospital Episode Statistics, English administrative data, to investigate the growth in admitted patient health care expenditures and the implications of an ageing population. We use two samples of around 40,000 individuals who (a) used inpatient health care in the financial year 2005/06 and died by the end of 2011/12 and (b) died in 2011/12 and had some hospital utilisation since 2005/06. We use a panel structure to follow individuals over seven years of this administrative data, containing estimates of inpatient health care expenditures (HCE), information regarding individuals’ age, time-to- death (TTD), morbidities at the time of an admission, as well as the hospital provider, year and season of admission. We show that HCE is principally determined by proximity to death rather than age, and that


eywords: ealth care expenditures geing ime-to-death

proximity to death is itself a proxy for morbidity. © 2017 Elsevier B.V. All rights reserved.


. Introduction

There is concern that the demographic pressures of population geing will lead to an unprecedented rise in public expenditures o levels unsustainable under current financing arrangements. In he UK in 2013 approximately 17% of the population (11 million ndividuals) were aged 65 years or over. This represents a rise of 7.3% in this age group on a decade earlier. Projections suggest hat by 2050 this group will have increased disproportionately to ounger age groups, accounting for approximately 25% of the pop- lation (Cracknell, 2010). The growth in the proportion of older

ndividuals is partly due to increased longevity and partly due to he age structure of the population, particularly the ageing of the eneration of baby boomers of the post war period to the early970s. Health care expenditures in the UK have also risen substan- ially over time, both in real terms and proportional to economic rowth. Close to the inception of the National Health Service (NHS),

∗ Corresponding author at: Department of Economics, Econometrics and Finance, niversity of Groningen, Duisenberg Building, Nettelbosje 2, 9747AE Groningen, etherlands.

E-mail address: d.d.howdon@rug.nl (D. Howdon).

ttps://doi.org/10.1016/j.jhealeco.2017.11.001 167-6296/© 2017 Elsevier B.V. All rights reserved.

net expenditure (net of patient charges and receipts) on the UK NHS in 1950/51 was £11.7b (GBP, in 2010/11 prices), representing 3.5% of Gross Domestic Product (GDP). This had risen to £121.3b by 2010/11, approximately 8.2% of GDP. Over the twenty-five year period from 1999/00 to 2014/15, expenditure in England almost doubled to £103.7b (2010/11 prices), with an average expenditure per head of population of £1900 (Harker, 2012). Abstracting from issues such as technological innovation, the concern is that as the share of the population at older ages rises, the economic burden of providing healthcare will become increasingly unsupportable.

Interest in the link between ageing populations and health care expenditures can be traced back 25 years, when the International Monetary Fund (IMF) asserted that ‘demographic pressures [in the UK] of an aging population will be associated with increased demand for medical services’, and presented descriptive statistics from various countries, showing that older patients, on average, had greater health care costs than younger patients (Heller et al., 1986). A report by the Organisation for Economic Co-operation and Development (OECD) predicted that across Europe population age-ing will create a rise in age-related social expenditures from around 19% of GDP in 2000 to around 26% by 2050. Old-age pension pay- ments and expenditure on health and long-term care was deemed responsible for approximately half this increase (Dang et al., 2001).https://doi.org/10.1016/j.jhealeco.2017.11.001http://www.sciencedirect.com/science/journal/01676296http://www.elsevier.com/locate/econbasehttp://crossmark.crossref.org/dialog/?doi=10.1016/j.jhealeco.2017.11.001&domain=pdfmailto:d.d.howdon@rug.nlhttps://doi.org/10.1016/j.jhealeco.2017.11.001


A f f n h e p i

t ‘ t h o i 2 o l c ‘ t c I c t i t a o i d r a o t t i a m k t b m m w u v ( e



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D. Howdon, N. Rice / Journal of

pproaches to predicting expenditure growth vary, but in a simple orm this consists of computing observed expenditures per head or different age-sex groups, and multiplying by projections of the umber of people expected to fall into each group. This approach, owever, fails to consider the underlying drivers of heath care xpenditures and the relative role of age, or, as has been suggested, roximity to death, or underlying levels of disability and ill-health,

n determining expenditures and its likely growth (see Gray, 2005). Additional to projections of population ageing is the poten-

ial change in the health profile of the population over time. An expansion of morbidity’ hypothesis has proposed that the ‘net con- ribution of our successes has actually been to worsen the people’s ealth’, as improvements in health care tend to lengthen the lives f those living with illness disproportionately to the effect of such mprovements on the lifespan of those living without (Gruenberg, 005). Should population ageing occur alongside a deterioration f health at older ages, then this will exacerbate impacts on pub- ic expenditures. While subsequent academic research into these laims – notably, research in the ‘compression of morbidity’ and red herring’ strands of literature – have given reason to suggest hat such concerns may have been misplaced or exaggerated, con- ern over the impact of an ageing population on HCE has persisted. ndeed, even in 2012, the UK’s then-Secretary of State for Health laimed that the fact that ‘the number of people aged over 85 in his country will double in the next 20 years’ was one of two factors n ‘costs . . . rising at an unaffordable rate’ (Lansley, 2012). He fur- her argued that ‘age is the principal determinant of health need’,1

nd that local NHS budgets should be recalibrated to be based n this, as a result (Williams, 2012). This paper uses UK admin- strative data from Hospital Episode Statistics (HES), and deaths ata from the Office for National Statistics (ONS), to consider two elated research areas. The first, in line with the ‘red herring’ thesis dvanced by Zweifel et al. (1999), is to explore the determinants f inpatient health care expenditures, with particular attention to he role played by age, time-to-death (TTD), and morbidity. We do his in a unique way by following samples of individuals who died n England, over seven years of HES data from 2005/06 to 2011/12, nd constructing a panel on individual health care expenditures and orbidity over this period. We show that TTD dominates age as a

ey driver of health care expenditures and morbidity characteris- ics dominate TTD. This finding extends the ‘red herring’ literature y showing that TTD is itself a ‘red herring’ and acts as a proxy for orbidity. This links to a second area of research by locating the odelling of health care expenditures for individuals close to death ithin the broader literature on prospective prediction of hospital se to inform resource allocation, particularly those based on indi- idual level data and which incorporate information on morbidity for example, see Iezzoni et al., 1998; van de Ven et al., 2003; Pope t al., 2004; Dixon et al., 2011).

. Literature review

.1. Compression of morbidity

The ‘compression of morbidity’ strand of literature beginning ith Fries (1980) suggests that, ‘[i]n its simplest form, “the age

t first appearance of symptoms of aging and chronic disease can ncrease more rapidly than life expectancy”’ (Fries et al., 2011).ries (2005) identifies three separate ‘eras’ of illness and well-being xperienced during the 20th Century and beyond: an era of infec- ious disease, followed by an era of chronic disease, followed by an ra described by the author as ‘directly related to the process of

1 Emphasis ours.

h Economics 57 (2018) 60–74 61

senescence, where the aging process itself, independent of specific disease, will constitute a major burden of disease’. Senescence – the process of ageing – is characterised by the ‘decline of maximal function of [all] vital organs’, beginning before any chronic disease takes hold: deaths where this function declines below a level nec- essary to sustain life, in the absence of any disease occasioning this, may be termed ‘natural deaths’ (Fries, 2005).

The implications for HCE of an ageing population become less clear in the light of compression of morbidity, and there are two aspects to this which deserve attention. First, as the “age at first appearance of symptoms of aging and chronic disease” increases, individuals can be said to age more healthily: the implications of this for HCE are considered below. Second, the compression of mor- bidity thesis takes for granted an increase in life expectancy. The implications of this for HCE can be considered at a population level for any given year of spending. Setting aside the causal process for this health ageing (again, considered below), as the average person ages more healthily, they require lower HCE at any given age. As more people live to very old age – for instance, 90 years old – each individual requires lower health spending at that age. The overall picture for HCE is however ambiguous: a larger number of people requiring lower HCE may require greater overall costs at a popula- tion level than a smaller number of people requiring higher HCE. Similarly, an individual, who dies at age 90 and requires lower HCE at any given age than they would had they been born into an ear- lier cohort, may require greater cumulative HCE over their lifespan than they would had they aged less healthily and died at the age of 70. The implications for HCE in the presence of healthy ageing and increased lifespan may differ at an individual level to a population level.

Freedman et al. (2002), in a systematic review covering research that had been conducted between 1990 and 2002, found that many measures of disability and limitations in old age had seen declines in recent years: in particular, a change of −1.55% to −0.92% per year in those reporting any disability during the late 1980s and 1990s. Romeu Gordo (2011) observes a cohort-on-cohort fall in the num- ber of individuals with high levels of disability-related functional problems in their everyday life for those born between 1924 and 1947 in the US. Cutler et al. (2013), using Medicare records from the US, present evidence of an increase in disability-free life between 1991 and 2009. The authors conclude that ‘The major question raised by our results is why this has occurred. How much of this trend is a result of medical care versus other social and environ- mental factors?’.

Cross-country international evidence on the changing pat- terns of disability rates across nine OECD countries is provide by Jacobzone et al. (2000). Consistent with the above literature, they report evidence of significant falls in severe disability rates. The importance of this issue for forecasting HCE depends upon how changes in mortality, changes in morbidity, and changes in dis- ability occur and interact with each other. If the onset of chronic conditions – those imposing large costs on health systems – can be postponed out of an individual’s lifetime, then health care costs may fall as later cohorts enjoy a longer lifespan, with a reduced level of necessary treatment for chronic conditions. Dormont et al. (2006), for instance, find that improvements in morbidity profiles in France between 1992 and 2000 have caused reductions in HCE that more than offset the rise in HCE induced by an ageing population.

The morbidity and disability profile of individuals, according tothis research, at any given age has improved over time, leading to health problems being experienced later in life and more closely to death. In the illustrated case (Figs. 1 and 22), individuals live

2 Adapted from Fries (1980) and http://www.aei.org/files/2008/06/27/20080626 WashingtonAEI.pdf.http://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdfhttp://www.aei.org/files/2008/06/27/20080626_WashingtonAEI.pdf

62 D. Howdon, N. Rice / Journal of Healt

Fig. 1. Stylised change in survival curves.

u o o h a e g g i T m t t c c


r p t


Fig. 2. Stylised change in health profiles.

p to a longer observed maximum age (indicated by the shift out f the survival curve from S1 to S2 in Fig. 1), and have a higher bserved level of health at all ages (indicated by the shift out of the ealth status curve from H1 to H2 in Fig. 2). Both survival curves nd health status curves have become increasingly rectangular. The ffect on health care expenditure (HCE) is ambiguous, given that enerally more healthy ageing – a decrease in morbidity at any iven age – puts downward pressure on HCE, while an increase n life expectancy, ceteris paribus, puts upward pressure on HCE. he actual relationship between health care costs and changes in orbidity and mortality profiles at every given age depends upon

he changing shape of these two curves, and also the extent to which he changes in each are due to or caused by the healthcare that reates these HCE. The use of age per se in predicting future health are costs should be approached with caution, as a result.

.2. Age, time-to-death and healthcare expenditures

The ‘red herring’ strand of literature further gives empiricaleason to suggest that claims of steeply-rising future HCE due to opulation ageing3 may have been exaggerated, potentially owing o morbidity being concentrated in later years of life. Zweifel et al.

3 HCE may rise due to technological change brought about by new expensive nnovations in health care treatments, or due to shifting patterns of morbidity.

h Economics 57 (2018) 60–74

(1999), using Swiss sickness fund data, find that no effect of age on health care expenditures existed after controlling for TTD, i.e. the time from any given point of observation to death for an individual. Owing to the number of individuals with zero HCE, a two-step model (with a probit first stage and OLS second stage) was employed, with only deceased patients included in the model. Such work was criticised on the grounds of potential endogene- ity, with time-to-death affected by both present, previous (and, due to the nature of how TTD must be measured) future HCE. In a subsequent paper, Zweifel et al. (2004) seek to test for such prob- lems, finding that while TTD is endogenous, their results were ‘fairly robust’ to the error this induces. Werblow et al. (2007) find that age is a small (but statistically significant) determinant of HCE after controlling for TTD for patients using long-term care (LTC), such as those in care homes, and is not associated with HCE for non- LTC patients. More complicated methods, such as those employing generalised linear models, have since been used, for example by Werblow et al. (2007), in order to deal with the non-normal prop- erties (such as positive skewness) exhibited in the distribution of HCE. These papers have corroborated results obtained using probit and OLS two-step models. Felder et al. (2010), in a recent paper in this series, first predict individuals’ survival based on observed HCE and socioeconomic characteristics (in early waves), before using predicted values based on this as an instrument for TTD in explain- ing HCE in later waves. The authors find that, while TTD cannot be deemed exogenous, any effect of age on HCE becomes insignificant when TTD (or instrumented TTD) is included in the model. Further- more, results regarding the relative importance of TTD compared to age have also been corroborated in a disease-specific study carried out by Wong et al. (2011).

While use has been made of morbidity markers in models of long-term care expenditures (LTCE) (see de Meijer et al., 2011), such use has not been made in models explicitly investigating the link between HCE and population ageing. One possibility is that TTD is itself a red herring, in that it is simply a proxy for morbidity, unob- served in existing HCE models in the red herring strand of literature. Such a theory has been provisionally borne out empirically in liter- ature related to economic evaluation of healthcare, with Gheorghe et al. (2015) finding that quality of life (as measured by SF-6D scores) declines with proximity to death, and also by biological and medical literature. Indeed, Dalgaard and Strulik (2014), proposing an alternative life cycle model of ageing, note that previous work in the ‘red herring’ strand of literature is consistent with biolog- ical and medical research (see, inter alia Mitnitski et al., 2002a,b, 2005; Rockwood and Mitnitski, 2006, 2007), showing that concep- tions of ageing focusing on time-from-birth (such as that inherent in Grossman (1972)) are erroneous. This model conceptualises the human body as a system which has substantial inbuilt redundancy (that is, an ability to function at a level well over and above that required to sustain life) in youth, but redundancy which declines as ‘deficits’ (a decline in function of individual parts of the body) are accumulated. Ageing depends not upon a ‘biological clock’, but is a process of increasing frailty which is the outcome of investments in health, available health technology, the lived environment, and a physiological ‘force of aging’ parameter. According to such a model, health is predicted to decline at an increasing rate when the individ- ual’s health status is lower. The authors note that existing research in the ‘red herring’ strand of literature, in line with this, ‘suggests that health status (e.g., frailty), and not the year on the birth certifi- cate, is what matters to health investments’. The latent assumption here is that a TTD variable proxies for this health status, which declines as individuals become more morbid as they approachdeath, and with ever-increasing levels of health investment to (partly) offset this decline in health status and postpone death.

This seems intuitively plausible: in the years before death, it is likely that morbidity will increase, leading to more treatment,


a b ( t t D t t i t L f t v e

t t d a t a b l a p o t o t t t f c l o v w 1 s c e t t i l

s p R w b n

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the HES dataset, which has been published for each financial year since 1989/90 and is available for admitted patient care, outpa- tient, accident and emergency and maternity cases. The admitted

D. Howdon, N. Rice / Journal of

nd that comorbidities complicating the treatment of the disease ringing about the hospital episode will also increase. Shwartz et al. 1996), in work predating the original red herring hypothesis, note hat the inclusion of variables for comorbidities increase substan- ially the explanatory power of models. It seems likely that, as algaard and Strulik (2014) suggest, variables incorporating ‘time-

o-death’ in more recent models of HCE are picking up, in large part, hese comorbidities, which are not included in existing HCE models n the red herring literature. Indeed, de Meijer et al. (2011) conclude hat time-to-death ‘largely approximates disability’ in models of TCE. Dixon et al. (2011), in proposing individual-level formulae or resource allocation in the UK’s National Health Service (often ermed ‘Person-Based Resource Allocation’, or PBRA) include indi- idual level morbidity markers, finding that these have a ‘powerful ffect. . . in predicting individual level expenditure’.

The process generating HCE is clearly not a simple function of hose explanatory variables used in existing ‘red herring’ research: he actual data-generating process behind these health care expen- itures is unlikely to be characterised accurately by a simple use of ge, historical time and time-to-death. In addition to the aforemen- ioned problems surrounding TTD and age as a proxy for morbidity, s Breyer et al. (2014) note, many existing models are likely to e characterised with substantial endogeneity problems, which

ead to potential bias in the estimation of the change in HCE as n individual ages or approaches death. The authors control for otential endogeneity introduced by differential treatment based n a physician’s view of the patient’s expected health benefits from reatment, proxied by actuarial tables of life expectancy conditional n age. If physicians expect individuals to respond differently to reatment, this may cause those who are more likely to respond to reatment to be treated more intensely than those who are not, hus increasing expected HCE for individuals who are younger, urther-from-death or with fewer comorbidities because of physi- ian selection. Conversely, HCE for older individuals – or, more ikely, individuals in the final years of life – may rise as intensity f treatment becomes stronger with heroic efforts to save an indi- idual’s life, possibly motivated by ethical ‘rule of rescue’ concerns hen faced with an identifiable, gravely sick individual (Jonsen,

986). Breyer et al. (2014) jointly estimate this possible physician election based on life expectancy alongside a model for health are expenditures, incorporating both age and time-to-death as xplanatory variables. They find that increasing survival rates for he elderly in Germany have positive impacts on HCE, arguing that his is explained by physician selection: treating patients more ntensively if they expect positive results from treatment over a onger time span.

Datasets used within the ‘red herring’ literature are, in general, ickness fund datasets, with only Seshamani and Gray (2004) using opulation-level (for users of NHS treatment) data, the Oxford ecord Linkage Study, a longitudinal dataset of all individuals ithin an area of Oxfordshire, England. We believe our paper to

e the first to use a sample of individuals from a comprehensive ational-level dataset of health care users.

The extent to which ‘red herring’ and related issues are of inter- st depends upon the intended use of such research. Much existing iterature focuses on projections of future health care costs given an geing population, with the headline results of some papers (such s Stearns and Norton (2004) and Seshamani and Gray (2004)) eing the overestimation of expected costs for a given future year hen TTD is an omitted variable. This is due to the collinearity

etween TTD and age for a given individual: an individual who gets ne year closer to death also gets one year older, and so the impactf TTD is picked up by age in such models. The inclusion of morbid- ty markers in addition to, or replacing, TTD would allow greater recision of future estimates where reliable estimates of morbidity revalence, and the cost of treatments, conditional on age and TTD

h Economics 57 (2018) 60–74 63

were known. Certainly, if the compression of morbidity hypothesis holds, and individuals are able to postpone the onset of chronic dis- eases – with associated higher HCE – to a time period closer to their death, or even indefinitely, explicitly considering morbidity rather than proxying this by age or TTD becomes ever more important.

We build upon the compression of morbidity and red her- ring strands of existing literature, seeking to further examine the relationship between ageing, time-to-death and health care expenditures. The original red herring hypothesis is that, once time- to-death is included in models of HCE, age per se does not explain changes in HCE. While models intended for resource allocation (Dixon et al., 2011) have already included morbidity as an explana- tory variable in HCE for the general population, other applications of models of HCE have not – in particular, those focusing explicitly on ageing populations, or costs in the years approaching death.

While hospital inpatient care forms only one part of health and social care incurred later in life, it is responsible for a large pro- portion of such expenditures. While it may seem that expenditures from other categories of health-related expenditures such as that arising from general practice, prescriptions, and even long-term care should be considered in the aggregate, much richer, more uni- versal and more reliable individual-level administrative data is at our disposal for the UK for hospital expenditures than for other types of expenditure, and information regarding the relationships examined in this paper are likely to be informative for specific avenues of NHS budget-setting. Furthermore, conflicting evidence exists regarding end-of-life long-term care expenditures and their functional relationships with age and TTD (de Meijer et al., 2011; Karlsson and Klohn, 2014), and the UK’s institutional structure and its resultant incentives regarding (predominantly privately- financed) long-term care and (predominantly socially-financed) hospital care is such that different relationships for each that are particular to the UK may well be expected. Finally, hospital expen- diture is a major contributor to end-of-life health care costs: French et al. (2017) find that hospital expenditure is dominant in the final year of life with non-hospital expenditure, of which long-term care is a major component, playing a greater role in periods prior to this. Indeed, they estimate that for England 11.6% of hospital expendi- ture occurs in the last year of life.

This paper seeks to bridge the gap between the red herring strand of literature and models of resource allocation, treating mor- bidity measures as omitted variables in models of current health care expenditure, and examining what the relationship between age, TTD and HCE is once morbidity is included in these models (see, for instance, Aragon et al., 2016).

3. Data

3.1. Data sources

Information on patient-level hospital use and associated refer- ence costs for treatment are derived from the Hospital Episodes Statistics (HES) dataset, published by the Health and Social Care Information Centre (HSCIC). This is complemented with small-area data on years of potential life lost (YPLL) published by the ONS, and individual level mortality information, jointly published by the HSCIC and the ONS.

We use successive years (financial years 2005/06 to 2011/12) of 4

patient (commonly, ‘inpatient’) care HES dataset that we use pro-

4 In the UK, the financial year runs from April to March.

6 Healt

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4 D. Howdon, N. Rice / Journal of

ides information on individual-level patient characteristics and iagnoses and procedures undergone for all patients admitted to ospitals in England.5

Information regarding inpatient spells is used to associate ref- rence costs to each spell. Reference costs are based on each NHS rovider’s estimates of their own costs for each patient spell, cat- gorised by Healthcare Resource Group (HRG, the NHS’s system of rouping clinically-similar events with comparable resource use). hese reference costs are derived from accounting costs for each RG, submitted by each organisation providing secondary care in ngland (Department of Health, 2012). The NHS Costing Manual rovides guidance to all providers to support the calculation of ref- rence costs and to enforce more uniform standards for costing ethodologies. We use the estimate provided by the hospital pro-

iding treatment as our estimated cost for the patient’s episode. The H’s Reference Cost data is submitted on a full absorption basis –

hat is, taking account of all direct and indirect costs relating to he activities in question, as well as a proportion of an estimate of ll overhead costs relating to the overall running of the provider. urther, to account for the fact that costs will vary even within RGs, hospitals are required to provide per diem costs for longer dmissions that exceed a given ‘trim point’, which differs by each RG. This trim point is defined as the upper quartile of length of

tay, plus 1.5 times the inter-quartile range for length of stay for hat HRG (Department of Health, 2012). Moreover, we augment the tandard costs incurred in each episode with the ‘unbundled’ costs here recorded for the episode. This represents one or more extra xed costs associated with the episode where additional, unusual, igh-cost treatment or procedures were involved. Even within the ame primary HRG, costs are not identical but differ according to he patient’s length of stay. An estimate of costs for each inpatient pell is obtained by matching data on costs for that provider in the eference Costs database to HRG for each episode in the relevant ear’s HES data.

HES contains diagnostic data, categorised (since 1995/96) ccording to the tenth revision of the World Health Organiza- ion’s International Classification of Diseases (ICD-10). Details of rocedures and interventions are recorded according to the fourth evision of the Office of Population, Censuses and Surveys’ Classifi- ation of Intervention and Procedures (OPCS-4) (Health and Social are Information Centre, 2013).

HES is broken down by completed “episode” – each record onsists of a continuous period of care at a single provider of reatment under the same consultant. A new record is generated hen a patient is either transferred to the care of either a new

onsultant, transferred to a new provider, or is discharged from ospital. Although individuals are not identifiable, individuals can e tracked across episodes by an anonymised identification num- er. The costing of a patient’s time in hospital and the recording of heir diagnoses and procedures undergone are made at the episode evel.

Patients can be tracked across different years of the HES dataset, hich enables the creation of a panel structure for the data. Infor- ation within the HES dataset – most commonly, information

egarding diagnosis, treatment and age of the patient – is used o apply the most appropriate Healthcare Resource Group (HRG) ategorisation to the dataset. We use the Health and Social Care nformation Centre’s Consultation ‘Grouper’ software in order toarry out this first step. We use the most recent version of this rouper – for the 2011/12 financial year – for all seven of the years e use, to categorise patients into HRGs. HRGs are used to cate-

5 This dataset includes both day cases (patients without an overnight stay) as ell as patients who have at least one night’s stay in hospital. Our use of ‘inpatient’

hroughout this text includes both types of patient.

h Economics 57 (2018) 60–74

gorise patient spells not only by broad diagnosis, but by the type and complexity of the patient’s spell, into one of over 1400 group- ings. This allows us to apply the current best-practice methods for grouping patients into HRGs based on the information available. We apply available estimates of hospital costs for each inpatient spell, using reference costs data for the relevant financial year.

We add information regarding an individual’s death from linked HES-ONS mortality data. The latest version of this data provides information on deaths to the end of the 2012 calendar year, and therefore provides information on some individuals whose deaths are known to have occurred after the end of the final wave in our dataset. Where individuals are known to have died, they are included up to and including the final quarter of their life, and not included in the panel in following years. TTD can only be measured – for decedents – retrospectively, using information available at the time of the individual’s death. We observe individuals for a maxi- mum of seven years (from 2005/06 to 2011/12) or 28 quarters and code TTD from 1 to 28, with TTD = 1 denoting the final quarter in which death occurs.6

We adopt a strategy that employs two complementary sampling procedures, each incorporating approximately 40,000 individuals. The first draws a sample of individuals who died in 2011/12, the final year of our analysis, and who had at least one quarter of recorded positive HCE in the 28 quarters of our data. The second draws a sample of individuals who had at least one quarter of recorded positive HCE in 2005/06, and died in or before 2011/12. We believe that each of these sampling procedures has advantages and disadvantages but that, together, they can be used to establish a clear conclusion on our research question.

Our first sample for analysis consists of a random sample of 39,381 individuals (18,690 men and 20,691 women) aged 50 years and older, taken from those with at least one inpatient episode between 2005/06 and 2011/12, and whose death was recorded by the ONS in the financial year 2011/12. Our second sample consists of a random sample of 39,796 individuals (19,673 men and 20,123 women) aged 50 years and older, taken from those with at least one inpatient episode in 2005/06, and whose death was recorded by the ONS after this point, and by the end of the financial year 2011/12. Sample size was selected to enable computations not to become burdensome, and the age cut-off was selected to ensure sufficient deaths were observed in the data to make meaningful inference. We follow all sampled individuals across all quarters until their death to observe their subsequent inpatient health care use and associated morbidity characteristics.

We collapse all inpatient episodes for each individual from HES for a given quarter into a single observation in our data. This obser- vation contains the sum of all hospital costs incurred in all episodes finishing in that quarter, as well as diagnostic information con- tained in the ICD-10 codes for those episodes in that quarter. In principle, the ICD-10 classification allows for up to 14,400 dif- ferent diagnoses. To make these more manageable for analysis, however, we collapse this information using the US Agency for Healthcare Research and Quality’s Clinical Classifications Software (CCS) method to convert ICD-10 codes to CCS codes (US Agency for Healthcare Research and Quality, 2009). This reduces the number of different groupings to a more manageable 260 mutually-exclusive, and clinically meaningful, categories.7 Where individuals do not have any episodes in a given quarter, we separately adopt two dis-tinct methods in order to deal with such cases. In one approach, they are recorded as having zero hospital costs, and as having zero observed morbidities arising from diagnostic information. In the

6 Coding TTD in this way is akin to assuming all deaths occur at the end of a quarter.

7 A full list of these CCS groupings is provided in Appendix A.

Health Economics 57 (2018) 60–74 65

a h i a m i a c f m

i d i t n

I ( d o u o E 3 S

o u e C u a c l a L U f 2 ( f t t U a c g Y t W a

d p p o (

i p


Table 1 Summary statistics (quarter 1, men, first year sample).

Variable Mean Std. Dev. Min Max

HCE [missing treated as zero] 475.60 1740.26 0 82,901.09 log(HCE) [missing treated as zero] 1.57 3.00 0 11.32 log(HCE) [missing treated as missing] 7.19 1.01 3.42 11.32 Quarters to death (QTD) 9.53 7.77 0 27 log(QTD) 2.02 0.88 0 3.33 Age 75.03 10.24 50 105.66 YPLL (IMD 2007) 65.50 15.71 33.80 180.8

Table 2 Summary statistics (quarter 1, women, first year sample).

Variable Mean Std. Dev. Min Max

HCE [missing treated as zero] 504.42 1629.34 0 45,095.81 log(HCE) [missing treated as zero] 1.56 3.03 0 10.71 log(HCE) [missing treated as missing] 7.30 0.99 3.39 10.71 Quarters to death (QTD) 9.86 7.89 0 27 log(QTD) 2.05 0.89 0 3.33 Age 78.11 10.93 50 111.15 YPLL (IMD 2007) 65.85 15.54 33.30 191.5

Table 3 Summary statistics (quarter 1, men, final year sample).

Variable Mean Std. Dev. Min Max

HCE [missing treated as zero] 220.74 1339.96 0 66,770.92 log(HCE) [missing treated as zero] 0.61 2.05 0 11.11 log(HCE) [missing treated as missing] 7.28 1.08 3.85 11.11 Quarters to death (QTD) 25.57 1.13 24.00 27.00 log(QTD) 3.28 0.04 3.22 3.33 Age 72.93 9.82 50 100.83 YPLL (IMD 2007) 64.14 15.09 33.80 162.90

Table 4 Summary statistics (quarter 1, women, final year sample).

Variable Mean Std. Dev. Min Max

HCE [missing treated as zero] 213.89 1310.72 0 64,392.08 log(HCE) [missing treated as zero] 0.56 1.98 0 11.07 log(HCE) [missing treated as missing] 7.36 1.08 3.34 11.07 Quarters to death (QTD) 25.59 1.13 24.00 27.00

D. Howdon, N. Rice / Journal of

bsence of additional information on the gravity of any residual ealth problem, this assumes that such health issues are insignif-

cant relative to those leading to a hospitalisation. In a second pproach, we recognise that the recording of zero morbidities ight be unrealistic for patients observed to have hospitalisations

n recent periods and for whom there is likely to exist an underlying, lbeit less grave, health problem. Consequently, we model these ases in our second approach under the assumption that episodes or which no information is available represent non-informative,

issing data. While we include a sum of all hospital costs for episodes ending

n the quarter in question, we include only a maximum of three iagnoses for each individual, for a maximum of five episodes end-

ng in that quarter. Using the merged mortality data, we are able o add a variable for the individual’s time-to-death, measured in umber of quarters to death.

In addition, we make use of the Office for National Statistics’ ndices of Multiple Deprivation (IMD), by Lower Super Output Area LSOA) in order to construct an instrument for TTD. LSOAs are efined at the time of the UK’s decennial Census and are made up f similarly-sized small areas of the country. HES data, for the years sed in our dataset, provides information on the individual’s LSOA f residence at the time of the 2001 Census. At this time, LSOAs in ngland consisted of 32,482 areas of populations between 1000 and 000, with between 400 and 1200 households (Office for National tatistics, 2011).

Indices of Multiple Deprivation, at this LSOA level, are measures f the levels of deprivation in those small areas. Although made p of seven domains (income, employment, health and disability, ducation, housing, living environment and crime (Department for ommunities and Local Government, 2011)), we primarily make se of one of the indicators that forms part of the health and dis- bility IMD score: years of potential life lost per 1000 people. This onsists of a standardised measure of premature mortality calcu- ated using information for all individuals to have died before the ge of 75, as described in Blane and Drever (1998).8,9 Although the SOAs themselves are defined every ten years at the time of the K’s census, statistics for each domain are collected and published

or these areas more regularly: we make use of those published in 007 (produced using data from 2001 to 2005 inclusive), and 2010 produced using data from 2004 to 2008 inclusive) (Department or Communities and Local Government, 2008, 2011). For each of hese years, we use LSOAs as defined in the 2001 UK Census. While hese figures are comparable within years, the data collector (the K’s Department for Communities and Local Government) caution gainst using this data for trend analysis. These measures are highly orrelated with TTD and, by virtue of being calculated at an aggre- ate level, exogenous in a model of HCE. That is, while the level of PLL at an LSOA level is a strong predictor of an individual’s TTD, his YPLL level is not influenced by the HCE for a given individual.

e therefore include at least one wave of this measure separately s instruments.

Tables 1 and 2 present descriptive statistics for the sample of ecedents from the first wave of data, under our strategy of sam- ling from the first year of observations (2005/06). Tables 3 and 4 resent descriptive statistics from the first wave of data, underur strategy of sampling from the final year of observations 2011/12).

8 The Office for National Statistics, however, use 75 rather than 65 years, in their mplementation of this method, as the age at which mortality is considered to be remature (Department for Communities and Local Government, 2011). 9 Details of the method employed by the ONS were obtained in personal commu- ication with the study’s author, Chris Dibben.

log(QTD) 3.28 0.04 3.22 3.33 Age 76.80 10.02 50 105.58 YPLL (IMD 2007) 64.78 15.07 33.80 180.80

As is usual, the distribution of HCE is positively skewed, with this skewness reduced somewhat when we take a logarithmic transformation.10 As would be expected due to their longer lifes- pan, on average, the average age of women in the sample is somewhat higher than that for men. Similarly, women are observed for, on average, slightly more waves. HCE, with missing waves treated as zero-(log)-cost observations, is on average higher when sampling from the first financial year of data than when sam- pling from those who died in the final year of analysis. This is as expected: the former is drawn from those with an inpatient episode in 2005/06, whereas the latter is drawn from those with an inpa- tient episode in any of the seven financial years of analysis. Indeed, HCE is approximately similar when missing waves are treated as missing observations.

Diagrams, presented in Figs. 3 and 4, based on descriptive statis- tics from a sample of 9,957,084 individual quarterly observationsin HES, provide some illustration of the existing red herring the- sis. HCE appear to increase with age (top-left panel): this is the usual age-expenditure curve that is used to infer rising costs with

10 Due to log(0) being undefined, we add a value of one to such observations in our modelling strategies that include zero-cost quarters.

66 D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74

by age

p l o h e h m ( t a a t T H i a


w b t

Fig. 3. Healthcare expenditures

opulation ageing, with the assumption being that as the popu- ation ages, the curve continues to rise as an extrapolation of the bserved trend.11 The observation that expenditures rise with age, owever, is an artefact of a compositional effect. The naïve age- xpenditure curve is composed of individuals who are known to ave died during the period of observation (the sample used in esti- ation) – who have, on average, high expenditures for this period

top-right panel) – and individuals who are known to have survived o at least the end of the period of observation who have, on aver- ge, lower expenditures for this period (bottom-left panel).12 The verage expenditures for individuals observed to have died during he sample period are far greater than for individuals who survive. his suggests an important role for time-to-death in explainingCE. As the proportion of the full population who are decedents

ncreases with age, the näive observed relationship between age nd expenditure displays an increasing trend. Note, however, that

11 We set aside here the drop in expenditures at very high ages, as this is likely to e due to the substantially lower sample sizes observed here. 12 While some of these survivors will be closer to death than other and therefore ould be classed as decedents over a longer observation period, such an effect would

ias us against finding a visual difference in these graphs. We therefore consider this o be strong evidence of a different age profile of HCE for decedents and survivors.

and proximity to death, males.

average expenditures for both decedents and survivors display a flatter profile than that depicted for the full population suggest- ing a less important role for age. Indeed, expenditure on decedents generally decrease, with this decrease particularly pronounced for women. Expenditure on survivors generally increase, but with a shallower gradient than observed for the full population, and at a lower average cost.

When we focus on decedents, and consider average HCE by proximity to death, we observe a large increase in costs in termi- nal quarters – particularly in the year immediately before death. Fig. 7 in Appendix A shows a similar relationship between expen- ditures and TTD for men at selected ages. In general, expenditure in quarters preceding the final three average around £500 (although there is variation). In the final three quarters, and particularly the final quarter, we observe a large increase in expenditure. With the exception of 50 year olds, there is a clear gradient of health expen- ditures rising most dramatically in the final quarter of life with average increases over the penultimate quarter ranging from £460 for 55 year olds to £1099 for 90 year olds.

The relationship between HCE and TTD in levels is nonlinear.Fig. 5 shows that the relationship is approximately linear on the logarithmic scale and in the modelling that follows logarithms of both HCE and TTD are used throughout.

D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74 67

Fig. 4. Healthcare expenditures by age and proximity to death, females.

Fig. 5. Average health care expenditures according to quarters to death (log scale for x- and y-axes).

68 D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74

al ind


s t

w s u t s b a


information about a patient’s morbidities at the time of their hos- pital stay. We estimate each of these models with random effects, representing unobserved heterogeneity.

Fig. 6. Change in HCE according to time-to-death and age, hypothetic

. Econometric model

We follow the general strand of the red herring literature and pecify a baseline model of HCE, including only age as an explana- ory variable.

log(HCEit) = ̨ + ˇageageit + �it + �i + εit, i = 1, . . ., N, t = 1, . . ., Ti, (1)

here �it is a vector of control variables (year and season of admis- ion, and hospital provider dummies) �i is an individual-specific nobserved effect and εit is an idiosyncratic error term. Although his model is not estimated in existing papers, it is claimed that uch a model would not adequately explain HCE. TTD is claimed toe an omitted variable in these models, giving rise to models such s:

og(HCEit) = ̨ + ˇageageit + ˇTTD log(TTDit) + �it + �i + εit . (2)

ividual dying at 75 (top – men, bottom – women; log HCE on y-axis).

We argue that individual morbidity is an omitted variable in this type of model, where TTD functions as a proxy for such morbidity.13

Accordingly, we augment the model as follows:

log(HCEit) = ̨ + ˇageageit + ˇTTD log(TTDit)

+ 260∑

j=1 ˇCCSj CCSjit + �it + �i + εit, (3)

where CCSn represents a recorded morbidity of CCS type n (n = 1, . . ., 260). We exploit the available data in HES to include detailed

13 And, furthermore, that such a proxy relationship may change over time in the presence of a compression of morbidity.

Health Economics 57 (2018) 60–74 69

l o T H T t t t i e e u

u e i F a p T a l T u i h d s fi a e


l s m r T i i m a r t t m

e c d

a a o T

t w o c s t l

Table 5 Results, final wave sampling.

Model Missing observations treated as missing


Men Age −.01459** −.01274* −.00518

(.00654) (.00652) (.00526) Age2 .00010** .00009** .00003

(.00004) (.00004) (.00003) log(TTD) −.42375*** −.14454***

(.01467) (.01206) Morbidities Included

Women Age −.00068 .00081 −.00038

(.00588) (.00585) (.00474) Age2 .00004 .00003 .00001

(.00004) (.00004) (.00003) log(TTD) −.34305*** −.13276***

(.01458) (.01218) Morbidities Included

Model Missing observations treated as zeros

(1) (2) (3)

Age .00130 .00204 .00289*

(.00180) (.00181) (.00156) Age2 0.00000 −.00001 −.00002**

(.00001) (.00001) (.00001) log(TTD) −.33712*** −.10645***

(.00679) (.00560) Morbidities Included

Women Age .00983*** .01087*** .00559***

(.00189) (.00189) (.00154) Age2 −.00005*** −.00006*** −.00003***

(.00001) (.00001) (.00000) log(TTD) −.27927*** −.09789***

(.00604) (.00520) Morbidities Included


D. Howdon, N. Rice / Journal of

Modelling HCE as a function of TTD suffers from potential prob- ems of endogeneity. Existing literature suggests that conditional n other covariates, being further from death – i.e. having a high TD – in time period t is likely to lead to lower levels of HCE in t. igher levels of HCEit, however, are likely to lead to high levels of TDit: if the hospital activity that generates health care expendi- ures is effective in improving health then the individual is likely o enjoy a longer remaining lifespan as a result. We therefore posit hat actual TTD at time period t has been determined in part by HCE n that time period as well as other time periods. Consequently, if ndogeneity does pose problems in this analysis, the coefficient stimate on TTD (when treated as exogenous) is likely to be an nderestimate of the true ‘effect’ of TTD.

Other models in the red herring strand of literature model HCE, sing TTD and age as explanatory variables, but highlighting this ndogeneity problem. Various attempts are made to purge TTD of ts endogeneity in HCE (Zweifel et al., 2004; Werblow et al., 2007; elder et al., 2010). We propose the use of a component of the Health nd Disability Index of Multiple Deprivation by Lower Super Out- ut Area – years of potential life lost (YPLL) – as an instrument for TD under the assumption that such measures are exogenous in

model of HCE but highly correlated with TTD. That is, while the evel of YPLL at an LSOA level is a strong predictor of an individual’s TD, this YPLL level is not influenced by the HCE for a given individ- al. Accordingly, where possible, we reestimate models (2) and (3)

nstrumenting TTD by YPLL.14 Such an instrumented approach is, owever, possible only in the case of our second sampling proce- ure, where TTD is not pre-determined by the construction of the ample. In our former sampling procedure, all individuals die in the nal four quarters (i.e., final financial year) of the sample, and thus ny relevance of variation across areas in deprivation would not be xpected.

. Results

All versions of our different sampling and modelling strategies ead to qualitatively similar results. In short, a weak (and often tatistically insignificant) relationship is observed when costs are odelled as a function of age alone. Confirming the overall red her-

ing results, a strongly significant relationship is observed between TD and HCE, when TTD is added as an explanatory variable. This s in line with our descriptive diagrams (Figs. 3 and 4), demonstrat- ng that the naïvely-estimated relationship between age and HCE is

uted when conditioning on TTD. When morbidities are included s explanatory variables, the relationship between TTD and HCE is educed (in all cases, the coefficient is reduced by approximately wo-thirds). When, where possible, instrumenting TTD, the rela- ionship between TTD and age becomes larger, with the addition of

orbidities again reducing the size of the TTD coefficient.15

Table 5 presents the results of various specification of a randomffects panel data model of log(HCE) on age, log(TTD) and morbidity haracteristics for the sub-sample of decedents, when a sample is rawn from those who died in 2011/12. The first column of results

14 While HCE is a function of morbidity, morbidity itself will be a function of age, nd TTD is likely to be a function of morbidity. Indeed, our hypothesis is that TTD is

proxy for morbidity. Accordingly, we expect supplementing (3) with information n morbidity will temper the effect of both age (remaining after conditioning on TD) and TTD on HCE. 15 In the interests of consistency, all results presented here employ one wave of he YPLL instrument. Where both instruments appear as relevant at the first stage, e estimated the models using both YPLL waves in order to carry out a Hansen J test

f the validity of overidentifying restrictions. In all cases, we observe large p-values onsistent with failing to reject the null-hypothesis (between 0.3354 and 0.6317), uggesting evidence in favour of the exogeneity of our chosen instruments. Fur- hermore, our second stage results suggest very similar coefficients and confidence evels, such that none of our conclusions drawn below are affected.

p < 0.05. ** p < 0.01.

*** p < 1.

(model 1) shows a weak and generally non-significant relationship between age and inpatient costs. These results represent, as far as we are aware, the first reported results in the red herring strand of literature of whether hospital costs increase with age in the aggre- gate, even before control is made for other factors such as TTD and morbidities. Existing research broadly states that this is the case, but refer merely to population-level descriptive statistics. In a ran- dom effects model (2) including TTD and age, we observe a highly significant relationship with TTD. This result is in line with those in the red herring strand of existing research. As an individual gets 1% closer to death, HCE increases by between 0.34% and 0.42% for men (between 0.28% and 0.34% for women), depending on the modelling strategy adopted.16

Conditioning on morbidity markers, we find a reduced role for TTD in explaining HCE, using both sampling strategies. Our esti- mate of the TTD elasticity of HCE falls by approximately two-thirds in almost all (non-IV) cases when we condition on the individ- ual’s observed morbidity in the current time period (i.e., whenwe move from model 2 to model 3). In all models, in excess of 90% of the estimated coefficients for the morbidity indicators are significant at the 1% level, yielding a p-value of 0.0000. We inter-

16 Because we aggregate costs by quarter and consequently use discrete values of TTD for each individual in each wave, this elasticity can only be considered as an approximation.

70 D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74

Table 6 Results, first wave sampling.

Model Missing observations treated as missing

(1) (2) (3) (4) (5)


Age −.01800* −.00454 .00290 −.00953 −.01124 (.00932) (.00896) (.00746) (.02617) (.01087)

Age2 .00013** .00003 −.00002 .00007 .00007 (.00006) (0.00006) (.00005) (.00018) (.00008)

log(TTD) −.31565*** −.10098*** −.35626 −.13120 (.00655) (.00616) (.36994) (.30968)

Relevance F-statistic 16.38 13.24 Morbidities Included Included

Women Age −.00269 .01198 .00065 .08939 −.01118

(.00832) (.00813) (.00696) (.06773) (.01124) Age2 .00004 −.00005 −.00001 −.00059 .00007

(.00005) (.00005) (.00004) (.00047) (.00009) log(TTD) −.26423*** −.09307*** −1.82773 −.12894

(.00663) (.00612) (1.2711) (.3239383) Relevance F-statistic 66.95 11.67 Morbidities Included Included

Model Missing observations treated as zeros

(1) (2) (3) (4) (5)

Men Age −.06500*** .10191*** −.00691 .28057*** .03547

(.02465) (.02265) (.01462) (.09001) (.06062) Age2 .00049*** −.00088*** .00001 −.00363*** −.00036

(.00016) (.00015) (.00010) (.00113) (.00058) log(TTD) −1.19842*** −.18669*** −2.05176*** −.31020

(.01205) (.00745) (.38267) (.23856) Relevance F-statistic 80.44 71.30 Morbidities Included Included

Women Age .06863*** .08155*** .02635*** .61590 .05830

(.00928) (.00934) (.00806) (.40329) (.05937) Age2 −.00039*** −.00048*** −.00016*** −.00393 −.00038

(.00928) (.00006) (.00005) (.00261) (.00040) log(TTD) −.15705*** −.03723*** −6.43066 −.64920

(.00801) (.00716) (4.95179) (.8581702) Relevance F-statistic 13.09 11.81 Morbidities Included Included

p u m i o 7 r c s

d H f w t b t

a s

expected, first-stage regressions show a negative and significant relationship between YPLL and TTD and an F-test of these instru-

* p < 0.05. ** p < 0.01.

*** p < 1.

ret this as indicating that TTD does indeed serve as a proxy for nobserved morbidity. The estimated coefficients for age when orbidity markers are included see similar falls. This is illustrated

n Fig. 6 which shows the difference in log(HCE) from the quarter f death to preceding quarters for an individual who dies at age 5 for the alternative specifications of the model.17 The combined elationship of time-to-death and age is severely muted when we ondition on current morbidity markers as seen by the lines repre- enting RE AGE TTD MORBS and RE AGE TTD (Table 6).

We anticipate hospital costs to rise as individuals approach eath, and as such expect a negative relationship between TTD and CE. For the sampling strategy where this is possible – sampling

rom the first calendar year – we instrument for TTD in order to deal ith the potential endogeneity of TTD in HCE, which would mean

hat a naïve estimate of the ‘effect’ of TTD on HCE was likely to be iased towards zero (i.e. that naïve estimates would be expected o be less negative). In a further pair of models, we instrument

17 While our instrumented model including morbidity markers appears to show mildly negative relationship between age and HCE, this arises from the use of a mall and non-significant negative age coefficient in construction of this graph.

TTD with LSOA-level YPLL measures, our small-area measure of premature mortality.

When we instrument using YPLL measures – model (4) – the estimated coefficient of log(TTD) rises (in absolute terms) in all cases. While we confirm the findings of Zweifel et al. (2004) that ‘the proximity of death rather than age [being] a main determinant of HCE is fairly robust to endogeneity error,’ our results also suggest that failing to account for the endogeneity of TTD in these models may lead to a large underestimate of the true ‘effect’ of TTD in mod- els that do not include morbidity markers.18 This is also illustrated in Fig. 6, which shows the large divergence in estimated costs for these two models for an individual who dies at the age of 75. As

ments suggests their relevance as a predictor of TTD according to

18 While our point estimates rise, in most cases, however, the TTD coefficients are no longer significant when we carried out our instrumented regressions. We do not rely on these results in our conclusions regarding the relationship between TTD, morbidity, and HCE, and present these results to demonstrate its consistency with existing research.

D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74 71

by pr

t 1


p a o p t t m o l l o o t ( t m A f g

b i b ‘ t m i – i o a f a a p

Fig. 7. Healthcare expenditures

he commonly used Stock-Yogo ‘rule of thumb’ of an F-statistic of 0 in all cases.

. Conclusions

Ageing populations pose a substantial problem for public service rovision, particularly for health and social care. Estimates of how n ageing population will impact HCEs vary considerably. Devel- ping credible predictions is a core component of health systems lanning as is allocating resources efficiently and equitably to meet he health care needs of the population. Whilst it is undeniable hat health care costs will rise as the baby-boomers age, the impact

ight not be quite as large as models based on a simple extrap- lation of a crude age-expenditure curve suggests. As individuals ive longer, all other things equal, they may generate larger cumu- ative life-time costs. The extent to which this becomes a burden n the health care sector will depend on how morbidity profiles f cohorts change over time. Should a compression of morbidity hesis hold, Fries (1980), Freedman et al. (2002) and Romeu Gordo 2011), on average individuals can expect to live longer and delay he onset of morbidity into later years. This will have the effect of

oving the age-expenditure curve to the right as populations age. n expansion of morbidity would have more severe consequences

or HCEs with individuals living longer, but also experiencing a reater number of years in ill-health.

Our findings support other literature that it is not age per se, ut time-to-death (TTD), particularly the final year of life, that

s a strong driver of HCEs. Our results regarding the relationship etween age, TTD and HCE are in line with existing results in the

red herring’ strange of literature. We extend this existing literature o show that, in line with the economic implications of biological

odels of ageing as drawn out by Dalgaard and Strulik (2014), TTD n large part proxies for morbidity in explaining HCE. Our results

showing a weak relationship between HCE and age when TTD is ncluded – fall in line with existing research into the determinants f HCE for ageing populations. However, while TTD clearly plays n important role in explaining HCEs, it is unhelpful in forecastinguture expenditure needs. At an individual level TTD is unknown nd hence to forecast future expenditure growth assumptions bout the proportions of decedents and survivors together with rojections of populations within age groups is required. By extend-

oximity to death, males by age.

ing the modelling of HCE to include morbidity characteristics we show that the impact of TTD is diminished indicating that it acts as a proxy for underlying health status. This is important to allow the planning of future resource requirements and in developing appro- priate models for budgets to be allocated equitably across providers of care in response to population health care need. Our results are robust to problems of endogeneity that exist between HCE and TTD.

Our results strengthen the need to include measures of mor- bidity in models of HCE. Merely including TTD is insufficient in predicting future HCE. To accurately forecast future expenditure needs, information on changes to profiles of morbidity are required. The existence of a compression of morbidity, along with a tendency for increased life expectancy, suggests competing and opposing pressures on HCE. While increases in life expectancy suggests that a greater number of individuals will be alive at any given age, with associated upward pressure on HCE, a compression of morbidity will tend to, on average, provide downward pressure on HCE for any given individual at any given age.

This work has focused on determinants of the demand for inpatient health care services at an individual level via age, time- to-death and morbidity characteristics. Clearly there is also a substantial role for supply-side impacts on expenditure growth notably through technological advances in health care interven- tions and the way in which health care services are organized and delivered. We do not address these issues here, but are areas that warrant further investigation at an aggregate level. Inpatient hos- pital care is one of a number of services provided by the National Health Service in England and other expenditure should also be taken into account when assessing the overall impact of an ageing population, as should costs placed on the Government by long- term care services predominantly accessed by older age groups. The increasing ability to link administrative sources of data provides a potentially valuable resource for future research in this area.


This is an independent report commissioned and funded bythe Policy Research Programme in the Department of Health from the Economics of Social and Health Care Research Unit (ESHCRU). ESHCRU is a joint collaboration between the University of York, London School of Economics and University of Kent. The views

7 Health Economics 57 (2018) 60–74

e f n ( c



Table A1 (Continued)

CCS code Description

61 Sickle cell anemia 62 Coagulation and hemorrhagic disorders 63 Diseases of white blood cells 64 Other hematologic conditions 65 Mental retardation 66 Alcohol-related mental disorders 67 Substance-related mental disorders 68 Senility and organic mental disorders 69 Affective disorders 70 Schizophrenia and related disorders 71 Other psychoses 72 Anxiety; somatoform; dissociative; and personality disorders 73 Preadult disorders 74 Other mental conditions 75 Personal history of mental disorder; mental and behavioral

problems; observation and screening for mental condition 76 Meningitis (except that caused by tuberculosis or sexually

transmitted disease) 77 Encephalitis (except that caused by tuberculosis or sexually

transmitted disease) 78 Other CNS infection and poliomyelitis 79 Parkinson’s disease 80 Multiple sclerosis 81 Other hereditary and degenerative nervous system conditions 82 Paralysis 83 Epilepsy; convulsions 84 Headache; including migraine 85 Coma; stupor; and brain damage 86 Cataract 87 Retinal detachments; defects; vascular occlusion; and

retinopathy 88 Glaucoma 89 Blindness and vision defects 90 Inflammation; infection of eye (except that caused by

tuberculosis or sexually transmitted disease) 91 Other eye disorders 92 Otitis media and related conditions 93 Conditions associated with dizziness or vertigo 94 Other ear and sense organ disorders 95 Other nervous system disorders 96 Heart valve disorders 97 Peri-; endo-; and myocarditis; cardiomyopathy (except that

caused by tuberculosis or sexually transmitted disease) 98 Essential hypertension 99 Hypertension with complications and secondary hypertension 100 Acute myocardial infarction 101 Coronary atherosclerosis and other heart disease 102 Nonspecific chest pain 103 Pulmonary heart disease 104 Other and ill-defined heart disease 105 Conduction disorders 106 Cardiac dysrhythmias 107 Cardiac arrest and ventricular fibrillation 108 Congestive heart failure; nonhypertensive 109 Acute cerebrovascular disease 110 Occlusion or stenosis of precerebral arteries 111 Other and ill-defined cerebrovascular disease 112 Transient cerebral ischemia 113 Late effects of cerebrovascular disease 114 Peripheral and visceral atherosclerosis 115 Aortic; peripheral; and visceral artery aneurysms 116 Aortic and peripheral arterial embolism or thrombosis 117 Other circulatory disease 118 Phlebitis; thrombophlebitis and thromboembolism 119 Varicose veins of lower extremity 120 Hemorrhoids 121 Other diseases of veins and lymphatics 122 Pneumonia (except that caused by tuberculosis or sexually

transmitted disease) 123 Influenza 124 Acute and chronic tonsillitis 125 Acute bronchitis

2 D. Howdon, N. Rice / Journal of

xpressed are those of the authors and may not reflect those of the unders. Daniel Howdon acknowledges PhD funding from the Eco- omic and Social Research Council under the Large Grant Scheme RES-060-25-0045). The authors gratefully acknowledge the highly onstructive remarks of two anonymous peer reviewers.

ppendix A.

See Fig. 7 and Table A1.

able A1 linical classifications software (CCS) groupings.

CCS code Description

1 Tuberculosis 2 Septicemia (except in labor) 3 Bacterial infection; unspecified site 4 Mycoses 5 HIV infection 6 Hepatitis 7 Viral infection 8 Other infections; including parasitic 9 Sexually transmitted infections (not HIV or hepatitis) 10 Immunizations and screening for infectious disease 11 Cancer of head and neck 12 Cancer of esophagus 13 Cancer of stomach 14 Cancer of colon 15 Cancer of rectum and anus 16 Cancer of liver and intrahepatic bile duct 17 Cancer of pancreas 18 Cancer of other GI organs; peritoneum 19 Cancer of bronchus; lung 20 Cancer; other respiratory and intrathoracic 21 Cancer of bone and connective tissue 22 Melanomas of skin 23 Other non-epithelial cancer of skin 24 Cancer of breast 25 Cancer of uterus 26 Cancer of cervix 27 Cancer of ovary 28 Cancer of other female genital organs 29 Cancer of prostate 30 Cancer of testis 31 Cancer of other male genital organs 32 Cancer of bladder 33 Cancer of kidney and renal pelvis 34 Cancer of other urinary organs 35 Cancer of brain and nervous system 36 Cancer of thyroid 37 Hodgkin’s disease 38 Non-Hodgkin’s lymphoma 39 Leukemias 40 Multiple myeloma 41 Cancer; other and unspecified primary 42 Secondary malignancies 43 Malignant neoplasm without specification of site 44 Neoplasms of unspecified nature or uncertain behavior 45 Maintenance chemotherapy; radiotherapy 46 Benign neoplasm of uterus 47 Other and unspecified benign neoplasm 48 Thyroid disorders 49 Diabetes mellitus without complication 50 Diabetes mellitus with complications 51 Other endocrine disorders 52 Nutritional deficiencies 53 Disorders of lipid metabolism 54 Gout and other crystal arthropathies 55 Fluid and electrolyte disorders 56 Cystic fibrosis 57 Immunity disorders58 Other nutritional; endocrine; and metabolic disorders 59 Deficiency and other anemia 60 Acute posthemorrhagic anemia

126 Other upper respiratory infections 127 Chronic obstructive pulmonary disease and bronchiectasis 128 Asthma 129 Aspiration pneumonitis; food/vomitus 130 Pleurisy; pneumothorax; pulmonary collapse

D. Howdon, N. Rice / Journal of Health Economics 57 (2018) 60–74 73

Table A1 (Continued)

CCS code Description

131 Respiratory failure; insufficiency; arrest (adult) 132 Lung disease due to external agents 133 Other lower respiratory disease 134 Other upper respiratory disease 135 Intestinal infection 136 Disorders of teeth and jaw 137 Diseases of mouth; excluding dental 138 Esophageal disorders 139 Gastroduodenal ulcer (except hemorrhage) 140 Gastritis and duodenitis 141 Other disorders of stomach and duodenum 142 Appendicitis and other appendiceal conditions 143 Abdominal hernia 144 Regional enteritis and ulcerative colitis 145 Intestinal obstruction without hernia 146 Diverticulosis and diverticulitis 147 Anal and rectal conditions 148 Peritonitis and intestinal abscess 149 Biliary tract disease 150 Liver disease; alcohol-related 151 Other liver diseases 152 Pancreatic disorders (not diabetes) 153 Gastrointestinal hemorrhage 154 Noninfectious gastroenteritis 155 Other gastrointestinal disorders 156 Nephritis; nephrosis; renal sclerosis 157 Acute and unspecified renal failure 158 Chronic renal failure 159 Urinary tract infections 160 Calculus of urinary tract 161 Other diseases of kidney and ureters 162 Other diseases of bladder and urethra 163 Genitourinary symptoms and ill-defined conditions 164 Hyperplasia of prostate 165 Inflammatory conditions of male genital organs 166 Other male genital disorders 167 Nonmalignant breast conditions 168 Inflammatory diseases of female pelvic organs 169 Endometriosis 170 Prolapse of female genital organs 171 Menstrual disorders 172 Ovarian cyst 173 Menopausal disorders 174 Female infertility 175 Other female genital disorders 176 Contraceptive and procreative management 177 Spontaneous abortion 178 Induced abortion 179 Postabortion complications 180 Ectopic pregnancy 181 Other complications of pregnancy 182 Hemorrhage during pregnancy; abruptio placenta; placenta

previa 183 Hypertension complicating pregnancy; childbirth and the

puerperium 184 Early or threatened labor 185 Prolonged pregnancy 186 Diabetes or abnormal glucose tolerance complicating

pregnancy; childbirth; or the puerperium 187 Malposition; malpresentation 188 Fetopelvic disproportion; obstruction 189 Previous C-section 190 Fetal distress and abnormal forces of labor 191 Polyhydramnios and other problems of amniotic cavity 192 Umbilical cord complication 193 OB-related trauma to perineum and vulva 194 Forceps delivery 195 Other complications of birth; puerperium affecting

management of mother 196 Normal pregnancy and/or delivery 197 Skin and subcutaneous tissue infections 198 Other inflammatory condition of skin 199 Chronic ulcer of skin 200 Other skin disorders 201 Infective arthritis and osteomyelitis (except that caused by

tuberculosis or sexually transmitted disease)

Table A1 (Continued)

CCS code Description

202 Rheumatoid arthritis and related disease 203 Osteoarthritis 204 Other non-traumatic joint disorders 205 Spondylosis; intervertebral disc disorders; other back

problems 206 Osteoporosis 207 Pathological fracture 208 Acquired foot deformities 209 Other acquired deformities 210 Systemic lupus erythematosus and connective tissue disorders 211 Other connective tissue disease 212 Other bone disease and musculoskeletal deformities 213 Cardiac and circulatory congenital anomalies 214 Digestive congenital anomalies 215 Genitourinary congenital anomalies 216 Nervous system congenital anomalies 217 Other congenital anomalies 218 Liveborn 219 Short gestation; low birth weight; and fetal growth retardation 220 Intrauterine hypoxia and birth asphyxia 221 Respiratory distress syndrome 222 Hemolytic jaundice and perinatal jaundice 223 Birth trauma 224 Other perinatal conditions 225 Joint disorders and dislocations; trauma-related 226 Fracture of neck of femur (hip) 227 Spinal cord injury 228 Skull and face fractures 229 Fracture of upper limb 230 Fracture of lower limb 231 Other fractures 232 Sprains and strains 233 Intracranial injury 234 Crushing injury or internal injury 235 Open wounds of head; neck; and trunk 236 Open wounds of extremities 237 Complication of device; implant or graft 238 Complications of surgical procedures or medical care 239 Superficial injury; contusion 240 Burns 241 Poisoning by psychotropic agents 242 Poisoning by other medications and drugs 243 Poisoning by nonmedicinal substances 244 Other injuries and conditions due to external causes 245 Syncope 246 Fever of unknown origin 247 Lymphadenitis 248 Gangrene 249 Shock 250 Nausea and vomiting 251 Abdominal pain 252 Malaise and fatigue 253 Allergic reactions 254 Rehabilitation care; fitting of prostheses; and adjustment of

devices 255 Administrative/social admission 256 Medical examination/evaluation 257 Other aftercare 258 Other screening for suspected conditions (not mental

disorders or infectious disease)259 Residual codes; unclassified 260 E Codes: All (external causes of injury and poisoning)


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  • Health care expenditures, age, proximity to death and morbidity: Implications for an ageing population
    • 1 Introduction
    • 2 Literature review
      • 2.1 Compression of morbidity
      • 2.2 Age, time-to-death and healthcare expenditures
    • 3 Data
      • 3.1 Data sources
    • 4 Econometric model
    • 5 Results
    • 6 Conclusions
    • Acknowledgements
    • References
    • References

J Popul Econ (2013) 26:1285–1301 DOI 10.1007/s00148-012-0448-2


Population aging, health care, and growth: a comment on the effects of capital accumulation

Rosa Aisa · Fernando Pueyo

Received: 19 July 2011 / Accepted: 7 September 2012 / Published online: 13 October 2012 © Springer-Verlag Berlin Heidelberg 2012

Abstract In a recent paper, Hashimoto and Tabata (J Popul Econ 23:571– 593, 2010) present a theoretical model in which the increase in the rate of dependence due to aging of the population leads to a reallocation of labor from non-health to health production and, as a consequence, to a decline in economic growth. We argue that these results rely heavily on assumptions of a “small economy” and perfect capital mobility, which tie down the amount of capital. In this paper, we proceed by analyzing the case of an economy in which the availability of capital is endogenously determined by domestic savings. We find that the new “capital accumulation effect” is opposite to the previous “dependency rate effect,” leaving the effect on economic growth ambiguous. In particular, if the former prevailed, population aging would foster economic growth, a result that finds support in recent empirical work.

Keywords Longevity · Population aging · Health workforce · Growth

JEL Classification O41 · J14

1 Introduction

In a recent paper, Hashimoto and Tabata (2010) (H&T in what follows) build a two-sector (health care and non-health care) model that focuses on the role of health-care services as “consumption goods.”. The authors maintain that a

Responsible editor: Junsen Zhang

R. Aisa · F. Pueyo (B) Facultad de Economía y Empresa, Universidad de Zaragoza, Gran Vía, 2, 50005 Zaragoza, Spain e-mail: fpueyo@unizar.es

1286 R. Aisa, F. Pueyo

rise in the old-age survival probability increases health care demand by older agents and slows down labor supply growth. Both elements produce a shift in labor from the non-health-care sector to the health-care sector, lowering the labor productivity growth rate in the non-health-care sector (driven by a learning-by-doing mechanism) and, hence, long-run per capita income growth slows down. The authors make clear that they do not consider any positive link between health-care services and labor productivity and, consequently, the rise in the old-age dependency ratio caused by the rise in the old-age survival probability inevitably hampers economic growth.

Empirically, there is no consensus about whether an expansion of the life horizon has a positive or a negative effect on growth. For instance, Sala-i- Martin et al. (2004) find that life expectancy is a positive significant deter- minant of economic growth, in a sample of 98 countries, using a set of 32 variables and the growth rate of per capita GDP between 1960 and 1992. Their results coincide with much of the prior literature surveyed in Bloom et al. (2004) and Weil (2007), which observes that countries with better health attain higher rates of economic growth. However, Acemoglu and Johnson (2007) find that higher life expectancy is negatively correlated with economic growth in a cross-country panel analysis. This finding is responded to by Bloom et al. (2009), who claim a strong positive correlation between a country’s initial life expectancy and its subsequent economic growth. Acemoglu and Johnson (2009) reply with new regression results, showing no evidence of positive effects of life expectancy on income per capita at 40- or 60-year horizons. The debate remains open.

The paper by H&T provides support to the negative relationship between longevity and economic growth through population aging. They point out that population aging strengthens the competition for resources between sectors for two parallel reasons: shortages in the labor force and a higher demand for workers in the health sector. However, this subject also presents inconclusive empirical evidence. First, as the authors mention, Newhouse (1992) found that population aging is not a main determinant of health demand, since it explains only 4 % of the health-care expenditure rise in USA. Second, although Lindh and Malmberg (2009), replicating their OECD study of 1999, do confirm that increasing dependency rates have negative effects on per capita GDP growth, Bloom et al. (2011) estimate that the effect of population aging on the rate of labor force participation and the associated effect of changes in labor force participation on economic growth are of modest size for the majority of countries. Furthermore, Lindh and Malmberg (2009) point to a possible explanation of the negative link between dependency rates of the elderly and economic growth as stemming from a shift of labor towards services, with slower productivity growth, which also involves increasing relative prices for capital due to lower savings rates.

None of the empirical studies concerned with the effects of population dependency rates on aggregate savings present a consensus about the negative,

Population aging, health care, and growth 1287

insignificant, or positive sign.1 Among these studies, Li et al. (2007) captured our attention by providing new evidence of the effects of both longevity and dependency rates on growth. The key element of their study is the behavior of savings, distinguishing the different roles played by longevity, on one side, and dependency, on the other. Using the World Development Indicators panel data set, they find that the longevity effect on savings is positive, whereas the dependency effect is negative. Coincidentally, the same results apply in investment and growth regressions. In particular, they assess these two opposing forces, finding a positive net effect on economic growth.

In this paper, we argue that the lack of a good match between the results in H&T and the recent evidence provided by Li et al. (2007) lies in the omission of the role of savings as a consequence of the assumption of a small economy. Our contribution is to consider the high demand for health-care services and the connected high demand for health workers, together with the large savings required to finance a longer retirement. The joint consideration of these elements allows us to go one step further in examining the implications of population aging for economic growth. In particular, we extend the H&T framework to a general equilibrium context allowing us to analyze how the demand for health-care services, as well as savings behavior, are influenced by population aging. We find that, although greater numbers of the elderly strengthen the demand pressure for health-care goods, inducing a shift in labor from the non-health sector to the health sector, and hampering economic growth (ignoring the link between health and productivity), individuals simul- taneously modify their savings behavior in order to accommodate the greater needs of retirement. This adaptation favors the accumulation of capital and increases labor productivity in the non-health sector, promoting an opposite shift of labor towards this sector. The net effect of these opposing forces, which we identify as the “dependency rate effect” and the “capital accumulation effect,” depends on the degree of substitutability between labor and capital in the production of non-health-care goods. When this is high, the dependency rate effect prevails, there is a shift of labor to the health goods sector, and economic growth slows down. However, as capital and labor become less and less substitutable, the capital accumulation effect intensifies and population aging can be accompanied by an enhancement of economic growth.

The rest of the paper is organized as follows. In Section 2, we extend the H&T framework to a general equilibrium context, determining individual behavior and the market equilibrium. The short-run and long-run effects of population aging on the economy are analyzed in Section 3. Finally, Section 4 closes the paper with our main conclusions.

1For example, Edwards (1996) finds a significant negative effect of the old-age dependency rate on the aggregate saving rate, whereas Adams (1971), Gupta (1971), Goldberger (1973), and Ram (1982, 1984) show cases with an insignificant or even a positive effect.

1288 R. Aisa, F. Pueyo

2 The model

2.1 Households

H&T build the following framework. Individuals can live for three periods, corresponding to childhood, youth, and old age. Survival to old age is not assured, with p ∈ (0, 1] being the probability of surviving to the third period of life. An individual born in period t − 1 is endowed with one unit of time, from which a fraction ηt is supplied to the labor market in t. The remainder is devoted to rearing and educating ηt children (in amounts e and vt for every child). The effective labor supply is htηt, with ht being the level of human capital. Denoting the wage rate w, the labor income amounts to wthtηt. Some portion is spent on non-health-care goods and the remainder is saved.2

The surviving elderly agents obtain a capital income in period t + 1 of Rt+1p st, where Rt+1 is the (gross) rate of return on savings. As usual, a perfect annuity market is incorporated, in such a way that the capital income unexpectedly left by individuals who die is shared by the individuals who survive to old age, thus generating a premium 1−pp over the ordinary payoff R on savings. Old-age consumption again involves non-health goods but also health goods in amounts c2,t+1 and z2,t+1, respectively. The production sector provides both types of product, health-care, and non-health-care goods (denoted by H and N, respectively). The latter are considered as the numeraire good, and qt denotes the relative price of health-care goods.

On the other hand, the time devoted to education of children v contributes to their human capital, according to the education technology ht+1 = μνσt .

Every individual derives utility from youth consumption, old-age consump- tion conditional on survival, and offspring. The expected utility of an individual born in t − 1 is given by:

ut = ln c1,t + p ln (

cγ2,t+1z 1−γ 2,t+1

) + φ ln (ntht+1) , (1)

where nt denotes the number of children and ht+1, their level of human capital. Thus, the consumer’s problem is given by the maximization of the utility function 1 subject to the budget constraints

c1,t + st = wthtηt,

c2,t+1 + qt+1zt+1 = Rt+1p st,

the time constraint ηt + (et + νt) nt = 1 and the technology of education ht+1 = μνσt . From the solution of this problem, the optimal consumption profile is

2The costs of raising and educating children are exclusively in terms of time.

Population aging, health care, and growth 1289

characterized by the following expressions for consumption when young (non- health goods) and old (both non-health and health goods), respectively:

c1,t = 1 (1 + p + φ)wtht,

c2,t+1 = γ Rt+1 (1 + p + φ)wtht, (2)

zt+1 = (1 − γ ) Rt+1qt+1 (1 + p + φ)wtht, (3)

implying an associated individual savings function given by

st = p (1 + p + φ)wtht. (4)

At this point, two things are worth highlighting. First, a greater probability of surviving into the third period implies a higher probability of enjoying the consumption derived from the second period savings, which leads to individuals reserving a larger share of income for this last period (Reinhart 1999). In contrast, the yields on savings fall, since the premium 1−pp obtained through the annuity market from the cut-back set of non-survivors declines. The second force dominates and thus, other things being equal, a higher life expectancy reduces the planned expenditure of both health (Eq. 3) and non- health goods (Eq. 2) at the greater age.

Second, given the functional form of the utility function, the share of old age expenditure devoted to health and non-health goods depends exclusively on the preferences parameter γ : c2,t+1qt+1zt+1 = γ1−γ , implying that the distribution of old-age expenditure is not affected by a change in the probability of surviving.

The solution of the consumer’s problem also determines the optimal num- ber of children and the optimal fraction of time devoted to their education as

nt = n = φ (1 − σ)e (1 + p + φ), (5)

νt = ν = eσ 1 − σ ,

respectively, implying that both the human capital of individuals and the fraction of time supplied to the labor market are constant over time:

ht = h = μ (

eσ 1 − σ

)σ ,

ηt = η = 1+p1+p+φ . Observe that a rise in the probability of survival does not affect the time de- voted to education (and thus, the human capital) by each individual. However, it does induce a reduction in the number of children, which in turn reduces the

1290 R. Aisa, F. Pueyo

aggregate time required for their care and education and, as a result, working time expands.

The size of the working population in t is denoted by Nt. This is the population born in t − 1 from the previous generation, who had nt−1 children, thus implying Nt = nt−1 Nt−1. We assume in what follows that e ≤ φ(1−σ )1+p+φ , guaranteeing in Eq. 5 a nonnegative population growth (n ≥ 1).

2.2 Firms

The production of health-care goods YHt follows a linear technology

YHt = AHt LHt , where LHt and A

H t denote the amount of labor hired by firms and the labor

productivity index in the health-care sector, respectively. This sector does not require capital as an input.

Diverging from H&T, we assume that the production of non-health-care goods YNt requires labor (in an amount L

N t ) as well as capital (denoted by Kt)

in a constant returns to scale technology represented by the CES production function:

YNt = [ αK−θt + (1 − α)

( ANt L

N t

)−θ]−1/θ ,

with 0 < α < 1 and θ > −1. ANt denotes the labor productivity index of the non-health-care sector. Although our qualitative results would also apply for a generic technology with standard properties, as the one assumed by H&T, we consider the CES case since it makes the problem easier to solve and, above all, because it clearly highlights the key role played by the elasticity of substitution between inputs in the effects of the population aging process. The above CES production function presents an elasticity of substitution between capital and labor equal to 1

/ (1 + θ). When θ → −1, the inputs are perfect substitutes; as

θ increases, the inputs become less and less substitutable. The particular case θ = 0 corresponds to a Cobb–Douglas technology (in which the elasticity of substitution is equal to one).

Denoting by yN = YN/ (AN LN) and kN = K/ (AN LN) the output and capital per unit of effective labor, the technology can be expressed in intensive terms as

yNt = f (kt) = [ αk−θt + (1 − α)

]−1/θ .

Again following H&T, the labor productivity indices ANt and A H t are fostered

by the average human capital level of the workers and also, as a consequence of the assumption of a scale external effect at the level of the industry, by the relative hired labor share of the firms of the corresponding sector:

Ait+1 = λi ( lit, h

) Ait, for i = H, N (6)

where lN = LN/L and lH = LH/L denote the fractions of hired labor in the non-health and health sectors, respectively. The function λi () verifies the

Population aging, health care, and growth 1291

common conditions that imply the irreversibility of Ait : Ait+1 ≥ Ait for all t. Under this specification, it is clear that the distribution of labor between both sectors plays a key role in determining long-run economic growth.3

2.3 Equilibrium

In a context of perfect competition, wages (wH in the health sector, wN in the non-health sector) and the interest rate will be given by the value of the marginal productivities of labor and capital in the corresponding sector:

Rt = α (

f (kt) kt

)1+θ , (7)

wNt = ANt (1 − α) f (kt)1+θ , (8)

wHt = qt AHt . (9) In equilibrium, the wage rate is the same in both sectors wHt = wNt = wt and hence, from Eqs. 8 and 9, the relative price of health-care goods is given by

qt = w N t

AHt = A

N t

AHt (1 − α) f (kt)1+θ . (10)

Consequently, an increase in the labor productivity of the non-health sector, relative to that of the health sector, fosters the relative price of health-care goods. In parallel, an increase in the intensity of use of capital in non-health firms (pushing up the marginal productivity of labor in this sector) increases such relative price.

With zt being the individual demand for health goods of any of the pNt−1 survivors to old age in t, the market clearing condition for health-care goods is given by

AHt L H t = pNt−1zt,

which, from Eq. 3, can be rewritten as

AHt L H t =

p 1 + p + φ

1 − γ qt

Nt−1 Rtwt−1h. (11)

An individual supply of labor time η on a population Nt determines the aggregate effective labor Lt as

Lt = ηNth = 1 + p 1 + p + φ Nth, (12)

3This specification does not consider the effects of aging on R&D investments (Prettner 2012) nor does it assess the role of government as health-care goods provider (Varvarigos and Zakaria 2012).

1292 R. Aisa, F. Pueyo

Fig. 1 Equilibrium in t

l Ht


l H


Health market

k t


which is shared by both health goods and non-health goods sectors in propor- tions lHt and l

N t . Thus, in labor market equilibrium, the following constraint


lHt + lNt = 1. (13) Making use of Eqs. 6–10 and Eqs. 12–13, expression 11 can be rewritten as

lHt = p (1 − γ ) (1 + p) n

wt−1 Rt wt

= p (1 − γ ) (1 + p) n

α f (kt−1)1+θ

λN ( lNt−1, h

) k1+θt

. (14)

With respect to capital, used only by the non-health sector, the aggregate supply in period t is determined by the aggregate savings of the previous period: Kt = Nt−1st−1. According to Eq. 4, this implies

Kt = Nt−1 p 1 + p + φ wt−1h. (15)

In intensive terms, taking into account Eqs. 12 and 13, the capital per unit of effective labor is given by

kt = pn (1 + p) 1

lNt A N t

wt−1 = pn (1 + p) 1

λN ( lNt−1, h

) (1 − α) f (kt−1) 1+θ

( 1 − lHt

) . (16)

Given kt−1 > 0 and 0 < lNt−1 < 1, the equilibrium in t is determined by Eqs. 14 and 16, providing the new value of capital and the distribution of labor between both productive sectors. Figure 1 depicts both equations.4 Expression 14, capturing the equilibrium in the health goods market, defines implicitly one inverse relationship between capital and the share of labor in the health good sector. In turn, the equilibrium savings–investment in expression 16 involves both variables in a positive relationship. The general equilibrium corresponds to the point that fulfills both conditions.

4The function in Eq. 14 may be convex, concave, or linear, depending on the value of θ .

Population aging, health care, and growth 1293

3 The effects of population aging

3.1 Short-run effects of population aging

The effects of an increase in life expectancy on the short-run equilibrium are summarized in the following proposition:

Proposition 1 In the short run, a rise in the old-age survival probability p increases the capital per unit of ef fective labor, but has an indeterminate ef fect on the distribution of labor between sectors.

Proof An increase in p changes the two functions 14 and 16 that determine the equilibrium. On the one hand, the health goods market clearing condition moves upwards because of two effects present in the first fraction on the right-hand side of Eq. 14: the direct increase in p and the associated fall in n. On the other hand, the same elements cause the savings–investment Eq. 16 to move to the right. The new equilibrium corresponds to a larger amount of capital. However, the impact on the distribution of labor appears to be indeterminate, as Fig. 2 suggests. We will show in Proposition 2 that the direction of this impact depends on the elasticity of substitution between inputs in the production of non-health goods. ��

What are the reasons for such an ambiguous effect on the distribution of labor between health and non-health goods production? The answer requires us to identify the forces at work behind Eq. 14, with some of these having to do with the evolution in capital in Eq. 16.

Three forces (of a demographic nature) are at work after an increase in p. They appear in the first fraction in Eq. 14. First, an increase in individual life spans increases the number of older individuals, generating an increase in aggregate demand for health-care goods. Second, from Eq. 5, the increase in p drives a reduction in the fertility rate, increasing the populations of subsequent generations more slowly and, hence, slowing down the working population

Fig. 2 Short-run effects of an increase in p

l H



l Ht

Health market

k kt

1294 R. Aisa, F. Pueyo

growth. In parallel, the lower fertility rate also reduces the time devoted to children, increasing the time devoted to work. The net effect of these forces is that the aggregate effective labor force grows more slowly, combined with a greater pressure for the production of health goods, favoring a shift of labor towards the health-care sector. This is what we identify as the “dependence rate effect”.

The second fraction in Eq. 14 includes wages and interest rates. From Eqs. 7–9, these are affected by the evolution of the amount of capital and the labor productivity indices. Focusing on the effect of an increase in p on the evolution of capital, Eq. 15 shows that, for a given set of values for the variables in t − 1, the capital available in t is increasing in p. The reason is obvious from Eq. 4: as we noticed there, an expectation of longer life increases the rate of savings, allowing for a greater accumulation of capital. Other things being equal, this implies an increase in capital per effective labor in Eq. 16, leading to a higher wage as well as to a lower interest rate in t, thus reducing the value of the second fraction in Eq. 14. In this way, the greater accumulation of capital acts as a disincentive for labor to move to the health sector, which we can identify as the capital accumulation effect. Note that, on the one hand, a higher amount of capital boosts wages in the non-health sector, and consequently the relative price of health goods in Eq. 10 rises, thus reducing the demand for health goods. On the other hand, the increase in capital reduces the interest rate. Since much of the income in the third period of life comes from the return on savings, that income experiences a cut-back that reinforces the decline in the demand for health goods.

In summary, the extension of life expectancy involves two opposite effects. On one side, the dependency rate effect implies a greater pressure for the production of health goods that, in turn, produces a shift of labor towards the health sector. On the other side, the capital accumulation effect boosts wages in the non-health sector and in parallel reduces the income of older individuals and their demand for health, promoting a shift of labor towards the non-health sector. The net effect of these opposite forces, as shown in Fig. 2, is ambiguous. The analysis of H&T focuses on expression 11 under the assumption of a world with perfect mobility of capital, in which the state plays the role of a “small economy” and thus takes the interest rate in Eq. 7 as given; as a consequence, the capital intensity in the production of non-health goods, and the wage in both sectors, become exogenous. In terms of Fig. 2, the savings–investment function would be vertical. In such circumstances, the capital accumulation effect disappears. Then, Eq. 14 would unambiguously predict a reallocation of labor towards the production of health goods.

Our incorporation of a new capital accumulation effect, working in the opposite direction, is what makes the final effect ambiguous. In any case, the assumption of a CES production function of non-health-care goods allows us to be more precise about the circumstances in which the extension of life expectancy generates a shift of labor towards one sector or the other, with subsequent consequences for the growth of productivity in each sector and for the whole economy. The results are summarized in Proposition 2.

Population aging, health care, and growth 1295

Proposition 2 In the short run, an increase in the old-age survival probability p has the following consequences for growth:

1. If the elasticity of substitution between inputs is above the unit, the labor productivity growth rate of the health sector increases and that of the non- health-care sector decreases, thus decreasing the short-run per capita income growth rate.

2. If the elasticity of substitution between inputs is below the unit, these results reverse: the labor productivity growth rate of the health sector decreases and that of the non-health-care sector increases, thus increasing the short-run per capita income growth rate.

3. If the elasticity of substitution between inputs is the unit, there are no ef fects on the labor productivity growth rate of any of the sectors and thus none on the short-run per capita income growth rate.

Proof A noncontroversial result of the increase in survival probability p is the increase in the amount of capital available, k. From Eqs. 14 and 16, we have

lHt = 1

1 + 1−α (1−γ )α k

θ t . (17)

When the elasticity of substitution between capital and labor is above the unit (θ < 0), the expression 17 implies an increase in the fraction of labor hired in the health sector lH to the detriment of the non-health sector, since, given that in this case the inputs are easily substitutable, the accumulation of capital has a low positive impact on the wage paid by the non-health sector; thus, the dependency rate effect prevails, generating a shift in labor from the non- health sector to the health sector. The repercussions for economic growth are obvious. Since the fraction of labor in each sector has a positive scale effect on its productivity growth rate, the increase in the old-age survival probability p increases the labor productivity growth rate of the health-care sector and in parallel reduces that of the non-health sector, determining the per capita income growth rate.5 Hence, in this case, the increase in p hampers economic growth in the short run.

Conversely, when the elasticity of substitution between capital and labor is below the unit (0 > θ , that is to say, both inputs are relatively necessary to non- health goods production), lH decreases as k increases in Eq. 17. In this case, the capital accumulation effect is more intense and leads to a significant rise in the wage paid by the non-health sector. In this situation, labor reallocation takes place in the reverse direction: towards the non-health sector. Thus, the rise in k will be accompanied by an increase of the labor productivity growth rate of

5Note that the wage rate in Eq. 8 is related positively with labor productivity in the non-health sector. Although the relationship appears to also be positive with labor productivity in the health sector in Eq. 9, the parallel decline in the relative price of health goods (see Eq. 10) cancels the positive effect.

1296 R. Aisa, F. Pueyo

the non-health sector and, hence, by an acceleration of economic growth in the short run.

Finally, in the threshold case of unit elasticity of substitution, corresponding to the Cobb–Douglas function (θ = 0), the availability of capital k has no influence on lH in Eq. 17, indicating that the dependence rate effect and the capital accumulation effect offset each other in such a way that an extension of longevity provokes no labor reallocation between sectors. Therefore, the population aging process has no effect on economic growth. ��

3.2 Long-run effects of population aging

After analyzing the short-run equilibrium, this section goes a step further by paying attention to the dynamics of the economy after the shock in longevity and, mainly, on its long-run consequences.

The short-run changes in the allocation of labor and in the accumulation of capital described above are the beginning of a transition dynamics in which the increase in capital modifies the savings decisions as well as the wage in the non- health sector, generating new equilibria over time. Eventually, the economy could reach a new steady state. We will confirm that the short-run effects of the increase in longevity also prevail in the new long-run equilibrium.

The dynamics of capital accumulation can be obtained by substituting Eq. 17 into Eq. 16, which gives rise to the following expression, relating the value of capital of two consecutive periods:

kθ+1t (1 − γ ) α + (1 − α) kθt

= p n (1 + p)

f (kt−1)1+θ

λN (

(1−α)kθt−1 (1−γ )α+(1−α)kθt−1 , h

) . (18)

The dynamic behavior of the economy, whose motion law is given by Eq. 18, is summarized in Proposition 3:

Proposition 3 In the long run, when −1 < θ ≤ 0, the economy always converges asymptotically to a unique interior steady state, k*. When θ > 0, the economy also converges to a unique steady state provided that θ is close enough to 0.

Proof Let us rename as F(kt) and G(kt−1) the left-hand and the right-hand terms of Eq. 18, respectively, in such a way that the dynamics are given by F(kt) = G(kt−1). A steady state is a value of capital k* that verifies F(k∗) = G(k∗). For such equilibrium to be stable, dktdkt−1

∣∣∣ k=k∗

= G′(k∗)F′(k∗) < 1 must hold. By defining (k) = G (k)/F (k), the steady states can be identified as the values of capital that make this function equal to the unit (k∗) = 1, being stable when ′ (k∗) < 0, and unstable otherwise. ��

Population aging, health care, and growth 1297

From Eq. 18, the first derivative of function (k) is given by

′ (k) = p [ α + (1 − α) kθ ]−(1+θ)/θ

n (1 + p) λNk

× {[

α (1 − γ ) + (1 − α) kθ ] [

α (1 + θ) α + (1 − α) kθ − 1


+ α (−θ) (1 − γ ) [


λN (1 − α) kθ

(1 − γ ) α + (1 − α) kθ + 1 ]}


Let us begin with the case −1 < θ < 0. The function (k) verifies lim k→0

(k) = ∞ and lim

k→∞ (k) = p1+p (1−γ )α

−1/θ nλN(0,h) = a < 1. Moreover, the two addends inside

the brackets in Eq. 19 are of opposite sign: the first is negative and becomes lower as k becomes higher, whereas the second is always positive. We can check that for k small and for k large enough. That is to say, decreases with k at the beginning but eventually increases with k, as depicted in Fig. 1. The steady state corresponds to the amount of capital that makes (k∗) = 1, which always exists, is unique, and stable, as depicted in Fig. 3.

Let us now move to the case θ > 0. The extreme values of the function are now given by lim

k→0 (k) = a > 0 and lim

k→∞ (k) = 0. Moreover, the second

addend inside the brackets in Eq. 19 is now negative, with the first also being negative for k high enough. This means that (k) can increase or decrease with k at the origin but eventually decreases, tending to zero. Note that with θ > 0, the value of a can be either over or below the unit. The condition

θ < ln α

/ ln

( p

1 + p 1 − γ

nλN (0, h)

) (20)

does ensure that a > 1 and therefore guarantees that a steady state exists and that it is unique and stable (see Fig. 4). Otherwise, there could be no steady state or multiples of the same.

Fig. 3 Steady state when −1 < θ < 0



k* k

1298 R. Aisa, F. Pueyo

Fig. 4 Steady state when θ > 0 under condition 20



k* k

Finally, when θ = 0, that is to say, the elasticity of substitution between inputs is the unit, the dynamics of capital accumulation given by Eq. 18 can be rewritten as kt = pn(1+p) 1−αλN((1−α)/(1−αγ ),h) kαt−1, which is a standard dynamic equation in which the capital monotonically converges to the steady state.

Taking into account the above proposition, it is possible to analyze the effects of longevity on the capital per effective labor and the distribution of labor between sectors in the steady-state equilibrium.

Proposition 4 Provided that the conditions for a steady-state equilibrium, unique and stable, hold (Proposition 3), the long-run ef fects of an increase in the old-age survival probability p are the following:

1. The long-run capital per ef fective labor increases. 2. If the elasticity of substitution between inputs is above the unit, the labor

productivity growth rate of the health sector increases and that of the non- health-care sector decreases, and thus the long-run per capita income growth rate decreases.

3. If the elasticity of substitution between inputs is below the unit, these results reverse: the labor productivity growth rate of the health sector decreases and that of the non-health-care sector increases, and thus the long-run per capita income growth rate increases.

4. If the elasticity of substitution between inputs is the unit, there are no ef fects on the labor productivity growth rate of any of the sectors and thus none on the long-run per capita income growth rate.

Proof An increase in survival probability p positively affects the function G(kt−1) and thus moves (k) upwards. A simple evaluation of Figs. 3 and 4 reveals that after such a change, the steady-state level of capital per effective labor becomes higher. From expression 17, we can check that this extra accumulation of capital provokes an increase in the fraction of labor hired in the health sector lH to the detriment of the non-health sector when the elasticity of substitutions between capital and labor is above the unit (θ < 0).

Population aging, health care, and growth 1299

On the contrary, the extra accumulation of capital causes an increase in the fraction of labor hired in the non-health sector lH , to the detriment of the health sector, when the elasticity of substitutions between capital and labor is below the unit (θ > 0). Since the fraction of labor in each sector has a positive scale effect on its productivity growth rate, and the labor productivity growth rate of the non-health-care sector governs the per capita income growth rate of the whole economy, the repercussions for economic growth are obvious. The increase in p hampers economic growth in the long run when θ < 0, whereas the increase in p enhances economic growth in the long run when θ > 0. Note that, since the short-run increase in capital is followed by further increases over the transition to the new steady state, the effects of the increase in the old-age survival probability on both the distribution of labor between sectors and the economic growth rate in the steady-state equilibrium are more intense than those in the short run. Finally, when θ = 0, we have that lN∗ = (1−α)

(1−γ )α+(1−α)

and k∗ = [

p n(1+p)

1−α λN(lN∗ ,h)

] 1 1−α

, from where it is immediate that an increase in

survival probability p affects positively the steady-state level of capital per effective labor but does not affect the allocation of labor between sectors and, thus, neither does it affect the long-run economic growth rate. ��

Consequently, the results of H&T are maintained in our framework in the long run when −1 < θ < 0, that is to say, when the inputs are easily substitutable. In this case, the accumulation of capital in the steady state has a low positive impact on the wage paid by the non-health sector and the dependency rate effect prevails, generating a shift in labor from the non-health sector to the health sector, damaging economic growth.

The above analysis makes clear that the elasticity of substitution between inputs plays a key role in this framework, where individuals modify their savings behavior after an extension of life expectancy, thus determining the behavior of capital. Depending on the degree of input substitution, either the dependency rate effect or the capital accumulation effect will predominate, in both the short and the long run. This multiplicity of results appears to be in accordance with the empirical evidence on longevity and population aging presented by Li et al. (2007) and provides support to the open debate about the controversial effects of longevity and population aging on economic growth.

As a final remark, we want to call attention to a shortcoming of the above analysis that is shared with H&T, namely the assumption of no labor migration between countries (in our case, due to the closed-economy setting). Empirical evidence shows substantial immigration of physicians from developing to de- veloped countries. For instance, Mullan (2005) has estimated that international medical graduates constitute between 23 and 28 % of physicians in the USA, the UK, Canada, and Australia, and lower-income countries supply between 40 and 75 % of these international medical graduates. In the above framework, such migration movements would reduce the shortages of workers derived

1300 R. Aisa, F. Pueyo

from the aging process in the developed countries, thus lowering the relative importance of the dependency rate effect and making it more probable that the capital accumulation effect would prevail.

4 Conclusions

The relationship between population aging, demand for health-care goods, and economic growth is complex and controversial. Our contribution to the debate lies in the joint consideration of the demand for health-care services and the connected demand for health workers derived from the aging process, together with the more substantial savings required to finance a longer retirement. We find that, although an increase in the numbers of the elderly strengthens the demand pressure for health-care goods, inducing a shift in labor from the non-health sector to the health sector that could damage economic growth (ignoring the link between health and productivity), individuals simultaneously modify their savings behavior in order to accommodate to the greater needs of a longer period of retirement. This latter change favors the accumulation of capital and increases labor productivity in the non-health sector, promoting an opposite shift in labor towards this sector. The net effect of these oppos- ing forces, namely the dependency rate effect and the capital accumulation effect, depends on the degree of substitution between labor and capital in the production of non-health-care goods. Specifically, when these inputs are easily substitutable, the dependency rate effect prevails and economic growth slows down. However, when the inputs are less substitutable, the capital accumulation effect dominates, enhancing economic growth.

The assumption in H&T of a small economy, in a world with perfect mobility of capital, firmly ties the capital–labor ratio of the economy under analysis to the worldwide level, since the interest rate is given by the world rate. Thus, the possible effects through the accumulation of capital disappear when capital is disseminated globally and its contribution to the worldwide total is negligible. As a result, only the dependency rate effect is at work, and, thus, population aging is accompanied by a shift of labor towards the health goods sector and by a slowdown of growth.

Our paper supports the claim that, to the extent that the mobility of capital is not “so perfect” and/or the country is not “so small.” the negative influence of population aging on growth is reduced and can even be reversed. From this point of view, the consideration of a given amount of capital can bias conclusions about the consequences of the aging process. Indeed, Li et al. (2007) show that, on average, the relationship between longevity and growth is positive due to the prevalence of the effects of capital accumulation.

In any case, the overall message is that, even ignoring the connections between health, life expectancy, and productivity (healthier people are more productive and can work for longer), our simple (largely standard) framework gives support to the controversial relationship between population aging and economic growth reported by the existing empirical evidence.

Population aging, health care, and growth 1301


Acemoglu D, Johnson S (2007) Disease and development: the effect of life expectancy on eco- nomic growth. J Polit Econ 115(6):925–985

Acemoglu D, Johnson S (2009) Disease and development: a reply to Bloom, Canning, and Fink. Working paper, http://econ-www.mit.edu/files/4491

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function approach. World Dev 32(1):1–13 Bloom DE, Canning D, Fink G (2009) Disease and development revisited. NBER Working Paper

15137 Bloom DE, Canning D, Fink G (2011) Implications of population ageing for economic growth.

Oxf Rev Econ Policy 26(4):583–612 Edwards S (1996) Why are Latin America’s saving rates so low? An international comparative

analysis. J Dev Econ 51:5–44 Goldberger AS (1973) Dependency rates and saving rates: comment. Am Econ Rev 63:232–233 Gupta KL (1971) Dependency rates and saving rates: comment. Am Econ Rev 61:469–471 Hashimoto K, Tabata K (2010) Population aging, health care, and growth. J Popul Econ 23:

571–593 Li H, Zhang J, Zhang J (2007) Effects of longevity and dependency rates on saving and growth:

evidence from a panel of cross countries. J Dev Econ 84:138–154 Lindh T, Malmberg B (2009) European Union economic growth and the age structure of the

population. Econ Change Restruct 42:159–187 Mullan F (2005) The metrics of the physician brain drain. N Engl J Med 353:1810–1818 Newhouse JP (1992) Medical care costs: how much welfare loss? J Econ Perspect 6(3):3–21 Prettner K (2012) Population aging and endogenous economic growth. J Popul Econ. doi:10.1007/

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Am Econ Rev 72:537–544 Ram R (1984) Dependency rates and aggregate savings: reply. Am Econ Rev 74:234–237 Reinhart VR (1999) Death and taxes: their implications for endogenous growth. Econ Lett 92:

339–345 Sala-i-Martin X, Doppelhofer G, Miller R (2004) Determinants of long-term growth: a Bayesian

averaging of classical estimates (BACE) approach. Am Econ Rev 94:813–835 Varvarigos D, Zakaria IZ (2012) Endogenous fertility in a growth model with public and private

health expenditures. J Popul Econ. doi:10.1007/s00148-012-0412-1 Weil DN (2007) Accounting for the effect of health on economic growth. Q J Econ 122(3):1265–


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  • Population aging, health care, and growth: a comment on the effects of capital accumulation
    • Abstract
      • Introduction
      • The model
        • Households
        • Firms
        • Equilibrium
      • The effects of population aging
        • Short-run effects of population aging
        • Long-run effects of population aging
      • Conclusions
      • References

Age and Ageing 2018; 47: 638–640 doi: 10.1093/ageing/afy014 Published electronically 23 February 2018

© The Author(s) 2018. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com


Deprescribing: the emerging evidence for and the practice of the ‘geriatrician’s salute’


1Kolling Institute of Medical Research, Sydney Medical School, Sydney University and Royal North Shore Hospital, St Leonards, New South Wales 2065, Australia 2Faculty of Pharmacy and Charles Perkins Centre, University of Sydney, New South Wales 2006, Australia

Address correspondence to: S. N. Hilmer. Tel: +612 9926 4481; Fax: +612 9926 4053. Email: sarah.hilmer@sydney.edu.au


The process of a health professional withdrawing medicines for which the current risk may outweigh the benefit in the indi- vidual patient has been given a variety of names including the colloquial ‘geriatrician’s salute’, ‘de-intensification’ and increas- ingly ‘deprescribing’. The rise of deprescribing as a word with a definition, evidence base and implementation plan, reflects the changing environment in which we practice. In particular, the emphasis on evidence-based medicine and the need to care for our expanding ageing populations, which requires application of components of geriatric evaluation and manage- ment by a wider range of health care practitioners. However, there are still significant challenges related to research on the safety, efficacy and implementation of deprescribing. In this commentary, we discuss the current evidence on the effects of deprescribing, emergence of implementation tools to embed deprescribing into the clinical care of older adults, as well as efforts to develop guidelines to improve health care practitioners’ awareness and self-efficacy of deprescribing. Ultimately, judicious prescribing and deprescribing, across a wide range of health care settings, ought to enable older people to use medicines to support their achievable ageing goals.

Keywords: deprescribing, prescribing, geriatric evaluation and management, older people

Judicious, frequent, goal-oriented medication review is a core component of the practice of geriatric medicine. As geriatricians, we ensure that our patients are not denied treatments that may help them because they are considered ‘too old’, while minimising iatrogenesis, which includes adverse effects of medicines. One way to achieve this is by ceasing medicines for which the current risk is thought to outweigh the benefit in the individual patient. This process has been given a variety of names: the colloquial ‘geriatri- cian’s salute’, ‘de-intensification’ and increasingly ‘depre- scribing’, which is defined in the literature as, ‘the process of withdrawal of an inappropriate medication, supervised by a health care professional with the goal of managing polypharmacy and improving outcomes’ [1].

The rise of deprescribing as a word with a definition, evidence base and implementation plan, reflects the chan- ging environment in which we practice. Geriatricians cannot possibly evaluate and manage every older person in our ageing population. Therefore, we need to objectively define and describe some of our strategies, including medication

review, so that they can be performed by other health care practitioners, reserving our face to face clinical expertise for the most complex patients. Emergence of evidence-based medicine to guide prescribing has resulted in calls for comparable evidence to guide deprescribing. As evidence on the effects of deprescribing grows, tools of implementation science for behaviour change are simultaneously being applied to embed deprescribing into the routine clinical care of older adults.

In the era of evidence-based medicine, clinicians report that a lack of evidence of the safety and efficacy of deprescrib- ing is a major barrier to practicing deprescribing [2] and there are significant efforts to address this. Systematic reviews sug- gest that deprescribing certain medication classes may reduce adverse events and improve quality of life [3]. Deprescribing has been consistently shown to be safe: it appears to improve survival in non-randomised studies and does not reduce sur- vival in randomised studies [4]. While there is high-grade evidence that deprescribing of psychotropics reduces falls [4], there is limited evidence of the impact of deprescribing targeting polypharmacy in general on global health outcomes


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that are critical for successful ageing, such as physical and cognitive function. This is also the case for most prescribing interventions. While there is an absence of evidence at pre- sent, it is plausible that deprescribing, which tackles only one part of geriatric evaluation and management, may not have a big impact on multifactorial geriatric syndromes. However, since adverse effects of medications are one of the most reversible causes of geriatric syndromes, it is important that they are addressed.

Research on how to deprescribe is emerging concurrently with the evidence on its safety and efficacy. Enablers and bar- riers to deprescribing have been described for practitioners [2] and for patients [5]. For practitioners, in addition to lack of evidence, these include problem awareness, inertia because of lower perceived value of stopping than continuing medicines, self-efficacy and feasibility [2]. Key factors identified by patients are the appropriateness of cessation, the need for a process for cessation, previous experiences, influence of health care practitioners, family and friends, fear of cessation and dis- like of medications [5]. Researchers are striving to define and test a ‘deprescribing process’ for routine care to address polypharmacy, including the five step patient-centred depre- scribing process, the CEASE protocol (Current medications, Elevated risk, Assess, Sort, Eliminate), and the Good Palliative-Geriatric Practice algorithm [6]. A number of clin- ical trials have assessed the feasibility of deprescribing benzo- diazepines in older patients and have yielded success rates between 27% and 80% targeting patients and/or different health care practitioners in a range of settings [7]. While most studies demonstrate that benzodiazepine withdrawal is feasible and safe in the older population, the clinical impact and sus- tainability of various interventions is yet to be established. Similarly, a recent Cochrane review which assessed the benefits and harms of deprescribing long-term proton pump inhibitor therapy in adults reported a reduction in pill burden, an increase in gastro intestinal symptoms and insufficient evi- dence in relation to long-term benefits and harms [8].

Guidelines are being developed that aim to improve health care practitioners’ awareness and self-efficacy of deprescribing. However, while rigorous methodology has been developed and utilised to generate the guidelines [9], the recommenda- tions are rarely supported by a strong evidence base because of the limited evidence on safety and efficacy of deprescribing. The Deprescribing Guidelines in the Elderly group, based in Canada have developed evidence-based deprescribing guidelines for a range of medication classes including proton pump inhi- bitors (PPIs), benzodiazepines, antipsychotics, cholinesterase inhibitors and memantine, with tools to support implementa- tion. While preliminary evidence suggests the guidelines and tools may reduce the use and cost of certain medication such us proton pump inhibitors [10], no randomised trial to date has assessed impact of rolling out guidelines on a population level on prescribing, patient-centred or clinical outcomes.

Other tools have been developed to facilitate deprescrib- ing in practice. Implementation of deprescribing is greatly assisted by access to non-pharmacological therapies. Efforts

are being made internationally to consolidate the evidence for and improve the availability of these therapies, through projects such as the European Union funded SENATOR- ONTOP (Optimal Evidence-Based Non-drug Therapies in Older People) series. A wide range of tools to help identify medications that are likely to be candidates for deprescrib- ing have been developed and validated, such as the STOPP criteria, Beers criteria and Drug Burden Index [6]. Most recently computerised decision support systems have been developed to facilitate using these tools to identify medica- tions for which risk is likely to outweigh benefit and prompt deprescribing in practice [11]. Use of the tools, and collab- oration between medical practitioners, pharmacists and nurses [12] may enable wider deprescribing practice and reach a broader group of older people than those who can access geriatricians.

Deprescribing occurs most often in patients during their last year of life, as it becomes clearer that a person’s care goals focus on comfort, and the time to benefit from most pre- ventative medications is limited. For example, it has been demonstrated that withdrawal of statins in patients with life limiting illness is safe [13], and analysis of national data from New Zealand found that statins were discontinued in the last year of life in 70.4% of people with cancer [14]. There are also efforts to apply deprescribing to specific patient populations such as people with chronic kidney disease [15].

There are opportunities for deprescribing across all health care settings where a comprehensive and, where pos- sible, multidisciplinary review can be performed. These include on admission to hospital where a new diagnosis or change in prognosis may become apparent, on transition to a nursing home, and during regular review by a practitioner who knows the patient well in the community. Healthcare for older people is frequently fragmented between settings and practitioners, and rather than ‘passing the buck’ for the responsibility of medication review, a collaborative approach with excellent communication is required [12]. The patient’s goals and priorities are central to deprescribing, and the vast majority of patients report that they would like to stop a medicine if their doctor said that they could [5].

Despite increasing international efforts, clinicians and researchers still face significant challenges in relation to depre- scribing research to generate evidence on safety, efficacy and implementation. We need to move away from conducting pilot deprescribing studies, which test feasibility in relation to pre- scribing outcomes, but are not powered to evaluate clinical outcomes. In addition, the choice of study design and interven- tion needs to be carefully selected to ensure that outcomes of deprescribing trials are reproducible, beneficial to patients and cost effective. The optimal study design will depend on the study population, outcomes of interest (e.g. short versus long- term), setting and health care system. Improving the evidence base for deprescribing, educating health care practitioners, and increasing public awareness are essential for application of deprescribing to clinical care and translation to policy. The ultimate aim is that through careful, informed prescribing and

Deprescribing: the emerging evidence for and the practice of the ‘geriatrician’s salute’


Downloaded from https://academic.oup.com/ageing/article-abstract/47/5/638/4904413 by Adam Ellsworth, Adam Ellsworth on 27 August 2018

deprescribing, across a wide range of health care settings, older people will use medicines to support their achievable ageing goals.

Key points

• Judicious, frequent, goal-oriented medication review is a core component of the practice of geriatric medicine.

• Deprescribing is the process of supervised withdrawal of a medication that aims to improve patient outcomes.

• Research on how to deprescribe is emerging concurrently with the evidence on its safety and efficacy.

Conflict of interest

None declared.


D.G. is supported by the Australian National Health and Medical Research Council Dementia Leadership Fellowship (1136849).


1. Reeve E, Gnjidic D, Long J, Hilmer S. A systematic review of the emerging definition of ‘deprescribing’ with network analysis: implications for future research and clinical practice. Br J Clin Pharmacol 2015; 80: 1254–68.

2. Anderson K, Stowasser D, Freeman C, Scott I. Prescriber barriers and enablers to minimising potentially inappropriate medications in adults: a systematic review and thematic syn- thesis. BMJ Open 2014; 4: e006544.

3. van der Cammen TJ, Rajkumar C, Onder G, Sterke CS, Petrovic M. Drug cessation in complex older adults: time for action. Age Ageing 2014; 43: 20–5.

4. Page AT, Clifford RM, Potter K, Schwartz D, Etherton-Beer CD. The feasibility and effect of deprescribing in older adults

on mortality and health: a systematic review and meta-analysis. Br J Clin Pharmacol 2016; 82: 583–623.

5. Reeve E, To J, Hendrix I, Shakib S, Roberts MS, Wiese MD. Patient barriers to and enablers of deprescribing: a systematic review. Drugs Aging 2013; 30: 793–807.

6. Scott IA, Hilmer SN, Reeve E et al. Reducing inappropriate polypharmacy: the process of deprescribing. JAMA Intern Med 2015; 175: 827–34.

7. Reeve E, Ong M, Wu A, Jansen J, Petrovic M, Gnjidic D. A systematic review of interventions to deprescribe benzodiaze- pines and other hypnotics among older people. Eur J Clin Pharmacol 2017; 73: 927–35.

8. Boghossian TA, Rashid FJ, Thompson W et al. Deprescribing versus continuation of chronic proton pump inhibitor use in adults. Cochrane Database Syst Rev 2017; 3: CD011969.

9. Farrell B, Pottie K, Rojas-Fernandez CH, Bjerre LM, Thompson W, Welch V. Methodology for developing depre- scribing guidelines: using evidence and GRADE to guide recommendations for deprescribing. PLoS One 2016; 11: e0161248.

10. Thompson W, Hogel M, Li Y et al. Effect of a proton pump inhibitor deprescribing guideline on drug usage and costs in long-term care. J Am Med Dir Assoc 2016; 17: 673 e1–4.

11. Alagiakrishnan K, Wilson P, Sadowski CA et al. Physicians’ use of computerized clinical decision supports to improve medica- tion management in the elderly—the Seniors Medication Alert and Review Technology intervention. Clin Interv Aging 2016; 11: 73–81.

12. Gnjidic D, Le Couteur DG, Kouladjian L, Hilmer SN. Deprescribing trials: methods to reduce polypharmacy and the impact on prescribing and clinical outcomes. Clin Geriatr Med 2012; 28: 237–53.

13. Kutner JS, Blatchford PJ, Taylor DH Jr. et al. Safety and benefit of discontinuing statin therapy in the setting of advanced, life-limiting illness: a randomized clinical trial. JAMA Intern Med 2015; 175: 691–700.

14. Nishtala PS, Gnjidic D, Chyou T, Hilmer SN. Discontinuation of statins in a population of older New Zealanders with limited life expectancy. Intern Med J 2016; 46: 493–6.

15. Whittaker CF, Fink JC. Deprescribing in CKD: the proof is in the process. Am J Kidney Dis 2017; 70: 596–8.

Received 2 January 2018; editorial decision 4 January 2018

S. N. Hilmer and D. Gnjidic


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  • Deprescribing: the emerging evidence for and the practice of the ‘geriatrician’s salute’
    • Conflict of interest
    • Funding
    • References