Data-Driven Decision Making for Health Care Administration
Data-Driven Decision Making for Health Care Administration essay assignment
Data-Driven Decision Making for Health Care Administration essay assignment
Most managerial decisions have some elements of uncertainty. For instance, what will actual demand for our services be? Healthcare administration leaders must make appropriate decisions to fulfill the needs of the “would-be of tomorrow” in order to ensure smooth process flows, effective healthcare delivery, and ensure patient quality and safety. While uncertainty enters into the realm of our everyday, it is often difficult to ascribe a clear definition of how it may affect decision making. As it applies to the practice of healthcare administration, uncertainty can introduce unforeseen and unexpected consequences that may negatively affect healthcare delivery. As a current or future healthcare administration leader, understanding and appreciating uncertainty for decision making will contribute to those decisions important for your health services organization.
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1. This week, you examine the concept of fuzzy decision making for healthcare administration practice. You also explore implementation of fuzzy decision making when uncertainty exists and practically apply decision making using sampling distribution analyses.
Learning Objectives
Students will:
· Analyze fuzzy decision making for healthcare administration practice
· Evaluate implementation of fuzzy decision making when uncertainty exists
· Apply decision making using sampling distribution analyses
Learning Resources
Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.
Required Readings
Albright, S. C., & Winston, W. L. (2017). Business analytics: Data analysis and decision making (6th ed.). Stamford, CT: Cengage Learning.
Chapter 6, “Decision Making Under Uncertainty”
Chapter 7, “Sampling and Sampling Distributions”
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. Note: Retrieved from the Walden Library databases.
Required Media
Palisade [PalisadeCorp]. (2014b, January 29). Introduction to Precision Tree—Palisade webcast [Video file]. Retrieved from https://www.youtube.com/watch?v=p2NQ5aEJSUQ&feature=youtu.be.
Discussion Part
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.
1. 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
2. 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.
By Day 5
Continue the Discussion and respond to your colleagues in one or more of the following ways:
· Ask a probing question, substantiated with additional background information, evidence, or research.
· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
· Offer and support an alternative perspective, using readings from the classroom or from your own research in the Walden Library.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.
· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
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