A quantitative performance measurement framework for health care systems

Performance measurement has been widely used in the manufacturing industry for years; although health care systems share many similarities with manufacturing systems, little has been done to adapt the performance measurements used in manufacturing systems for health care systems. Productivity is of vital importance to a health care system's ability to compete and survive over time. A health care system that is not able to efficiently utilize its resources in creating value for its patients will not survive with the ever increasing costs of care. However, the development of fully functional and suitable performance measurement systems (i.e. set of measures) to measure productivity has proven to be a very challenging task. This research has focused on the adaptation of a performance measurement system used in manufacturing for application in health care systems.;This research proposed a quantitative performance measurement system to apply in the health care industry. The main objective and critical factors to the system were first established to be included in the framework. The main objective and the critical factors were then decomposed in a top-down fashion to identify clearly the requirements of the system and the means to achieving those requirements. After breaking down the main factors to sub-components, these sub-components were then connected based on their qualitative relationships. The components are integrated using incremental calculus to analyze the system components' relationship quantitatively. Based on the incremental calculus, a marginal analysis was conducted to measure the extent to which various criteria, the system as a whole, were affected by a given incremental change of each variable.;The proposed framework was applied to Green Meadows Clinic to measure the effects of changing ten percent of the physician and nursing manpower, the clinic's expenses, as well as patients' turnout to the operating margin of the clinic. Data obtained from the IDX data system and performance trend reports were analyzed using the proposed framework. The results showed that increasing ten percent of the physicians will bring about an increase in operating margin, while increasing ten percent of medical expenses and nursing staff reduces the operating margin. The analysis also showed that by improving patients 'no show' and the ratio of new and established patients resulted in an increase in operating margin for the clinic. The major accomplishments of this work included the incorporation of a system engineering tool to health care system performance measurement and the ability to show the overall effects to the system as a whole by making marginal changes to the inputs, thus helping health care managers to make better decisions.