Data envelopment analysis (DEA) is a technique that evaluates the performance of decision making units (DMU's) by determining the efficiency of each DMU relative to other DMU's. The process of building and evaluating DEA models is complex and requires the use of specialized solvers. The process typically involves identifying relevant factors relevant to the DMUs and classifying them as inputs and outputs. For example, if CVS wanted to measure the performance of four pharmacies relative to each other, then each of the four pharmacies will be a DMU. Examples of relevant factors would be FTE employed, square footage of the location, salary expense, non-salary expense, prescriptions filled and profit margin as factors in the process. Of these factors, prescriptions filled and the profit margin would be outputs while FTE employed, square footage, salary expense and non-salary expense would be considered as inputs.

For this discussion, I want you to choose a healthcare system that has multiple DMU's. Examples of such systems could be hospital system with multiple hospital locations, a healthcare device manufacturer such as Guidant with multiple assembly plants, a mental healthcare provider such as Solutions with multiple counselling and psychological testing centers. For the chosen system identify at least six factors and classify these factors as inputs or outputs. Describe the reason(s) why you classified the factors the way you did.

P.s.

Please use United States references. Thank you.