Document Type


Date of Award

Spring 5-31-2013

Degree Name

Doctor of Philosophy in Industrial Engineering - (Ph.D.)


Mechanical and Industrial Engineering

First Advisor

Sanchoy K. Das

Second Advisor

Athanassios K. Bladikas

Third Advisor

Reggie J. Caudill

Fourth Advisor

Shanthi Gopalakrishnan

Fifth Advisor

Kevin J. McDermott


Hospital performance can be evaluated in four categories: (i) quality of care, (ii) process of care (iii) financial and (iv) operations productivity. Of these, ‘quality of care’ is the most widely reported and studied measure of performance, and focuses primarily on the clinical outcomes of the patient. In contrast, operations productivity and efficiency is the least studied measure, and currently there is limited ability to evaluate how efficiently the hospital has used its resources to deliver healthcare services. Cost containment in the healthcare industry is a challenging problem, and there is a lack of models and methods to benchmark hospital operating costs. Every hospital claims they are unique, and hence comparative assessments across hospitals cannot be made effectively. This research presents a performance framework for hospital operations to be called HOSx: Hospital Operations Excellence Model, used to measure and evaluate the operations productivity of hospitals. A key part of this research is healthcare activity data extracted from Medicare Provider Analysis and Review (MedPAR) database and the Healthcare Provider Cost Reporting Information System (HCRIS), both of which are maintained by the Center for Medicare Services (CMS).

A key obstacle to hospital productivity measurement is defining a standard unit of output. Traditionally used units of output are inpatient day, adjusted patient day (APD) and adjusted discharge, which are reasonable estimators of patient volume, but are fundamentally limited in that they assume that all patients are equivalent. This research develops a standardized productivity output measure for a Hospital Unit of Care (HUC), which is defined as the resources required to provide one general medical/surgical inpatient day. The HUC model views patient care as a series of healthcare related activities that are designed to provide the needed quality of care for the specific disease. A healthcare activity is defined as a patient centric activity prescribed by physicians and requiring the direct use of hospital resources. These resources include (i) clinical staff (ii) non-clinical staff (iii) equipment (iv) supplies and (v) facilities plus other indirect resources. The approach followed here is to derive a roll-up equivalency parameter for each of the additional care/services activities that the hospital provides. Six HUC components are proposed: (i) case-mix adjusted inpatient days (ii) discharge disposition (iii) intensive care (iv) nursery (v) outpatient care and (vi) ancillary services. The HUC is compatible with the Medicare Cost Report data format. Model application is demonstrated on a set of 17 honor roll hospitals using data from MedPar 2011. An expanded application on 203 hospitals across multiple U.S. states shows that the HUC is significantly better correlated than the more traditional APD to hospital operating costs. The HUC measure will facilitate the development of an array of models and methods to benchmark hospital operating costs, productivity and efficiency.

This research develops two hospital operations metrics. The first is the Hospital Resource Efficiency (HRE), which is defined as operating cost per Hospital Unit of Care, and the second is the Hospital Productivity Index, which benchmarks performance across the reference set of hospitals. Productivity analysis of all 203 hospitals in our database was conducted using these two measures. Specific factors studied include (i) functional areas (ii) patient volume (iii) geographical location. The results provide for the first time a ranking of most productive hospitals in each state – New Jersey, Pennsylvania, Nebraska, South Dakota and Washington as well as an interstate ranking. This research also provides detailed analysis of all outlier hospitals and causes of productivity variance in hospitals. The final output, the Hospital Total Performance Matrix combines clinical performance with productivity to identify the leading U.S. hospitals.



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