Data-Driven Decision Making for Health Care Administration

Week 3: Data-Driven Decision Making for Health Care Administration
 
 
Decision Making Under Uncertainty and Sampling Distributions
 
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.
 
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 weeks 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.,

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