Fuzzy Decision Making
When uncertainty exists, how does one evaluate the universe of possible outcomes?
Unfortunately, there is no one steadfast rule on how to anticipate what a correct decision might be. However, there are a set of tools and practices that healthcare administration leaders can use to help make the best decision possible given data for a particular set of circumstances. One such example is that of fuzzy decision making, wherein a healthcare administration leader attempts to wrap human expertise around a set of guidelines to enhance workflow and performance. While not all circumstances may lend themselves to fuzzy decision making, understanding what these tools are is a useful practice when managing a health services organization.
For this Discussion, review the resources for this week. Reflect on the concept of fuzzy decision making for healthcare administration practice. Consider how you, as a current or future healthcare administration leader, may engage in fuzzy decision making for your health services organization
By Day 3
Post a description of how you would define fuzzy decision making for healthcare administration practice. Then, explain how you might implement fuzzy decision making to evaluate decisions when uncertainty exists. Provide an example where fuzzy decision making might be important for your work or life, and explain why. Be specific and provide examples.
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Fuzzy decision-making is a way to select the best answer or option in a scenario where this is missing or incomplete information. The environment or goals around the issue are not well defined and a leader must try to make the best decision they can given the information and scenario they have (Bellman & Zadeh, 1970). Decision making in healthcare can be especially difficult as it can be very complex and often has widespread effects that can impact patients and their wellbeing. Fuzzy decision making can be used in healthcare to help account for some of these uncertainties. Applied in a way that helps to account for unknowns, fuzzy decision making has been utilized to help in the healthcare industry through service quality, risk management, equipment selection, health services, and other areas (Ekin et al., 2015). A great example of this is when Tsai et al. (2012) used a fuzzy decision-making method to assist in create national healthcare performance indicators for hospitals in Taiwan when not all of the needed data metrics were available. They utilized the fuzzy analytic hierarchy process to create criteria weights and scores of alternatives that assisted the facility in helping make decisions when their comparison ratios were incomplete (Tsai et al., 2010).
Fuzzy decision making could be exceptionally useful in areas of decision support systems or complex treatment concerns. Since these systems are created to deal with uncertainty while still utilizing rational, thorough logic to come to a decision (Ekin et al, 2015). I think it would be well utilized in instances where you need to measure service quality in the facility, especially across multiple departments and locations.
Bellman, R. E., & Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment. Management Science, 17(4), B141–B164. http://www.jstor.org/stable/2629367
Ekin, T., Kocadagli, O., Bastian, N. D., Fulton, L. V., & Griffin, P. M. (2015). Fuzzy decision making in health systems: A resource allocation model. JEuro Journal on Decision Processes, 1–23. https://doi.org/10.1016/j.eswa.2019.07.002
Tsai, H, Chang, C, & Lin, H. (2010). Fuzzy hierarchy sensitive with Delphi method to evaluate hospital organization performance. Expert Systems with Applications 37 (2010).
Healthcare costs are growing exponentially and it will be up to the healthcare administrator to identify the optimal allocation of available resources to
maximize health and health systems. Decision makers realize budgetary constraints will not allow healthcare systems to make detection, prevention, and
treatment available to all persons. Some healthcare systems are applying formal health-economic analysis such as fuzzy decision making approach. Fuzzy
decision making is where given goals and constraints intersect, such as X should be in the vicinity of Z. Vicinity is the fuzzy area. ((Ekin et al. (2015). One
example would be to solve the long waiting times issue. Resource allocation must be addressed in a systematic way. Increasing demand and limited
funding make the efficient use of resources in health systems important.
Things that are not clear are fuzzy. Fuzzy decision making offers flexibility for reasoning. An example of fuzzy is the statement, ” of the patient is large,
give him 1 tablespoon of medicine”. Well, what is large? is it 200 pounds, is it 250 pounds? Fuzzy decision making may become important in my life for
instance ask myself, “when will I start my dissertation?” Now, soon, or later? Well, does that mean tomorrow or 2 months from now? Fuzzy decision
making is meant to deal with imperfect information which is incomplete or even unreliable. It provides a framework for dealing with quantifiers, such
as many, few, almost all, or infrequently. Fuzzy decision making is all about the relative importance of precision. ( Albright & Winston. 2017).
Ekin, T., Kocadagli, O., Bastian, N.D., Fulton, L.V., & Griffin, P.M ( 2015). Fuzzy Decision making in health systems: A resource allocation model. Jeuro Journal on Decision Processes. 1-23.
Albright S.C. & Winston, W.L. (2017). Business Analysis: Data analysis and decision making. (6th ed). Stamford, CT Cengage Learning.