Developing Key Performance Indicators for Dynamic Efficiency Evaluation of Healthcare Service Centers

Abstract

Evaluating the efficiency of Healthcare Service Centers (HSCs) requires moving beyond conventional static approaches toward dynamic modeling due to the complex nature of healthcare service production and the temporal effects of managerial decisions. One of the fundamental challenges in this field is the lack of a coherent and validated set of input, output, and, particularly, Carry-Over Variables (COVs) capable of accurately modeling the linkage between consecutive time periods. This study aims to identify, screen, and finalize the key performance indicators for the Dynamic Efficiency Evaluation (DEE) of HSCs. From the perspective of its objective, this research is applied in nature, while methodologically it adopts a mixed-methods approach. In the first stage, a comprehensive list of potential variables was extracted through a systematic review of the relevant literature. In the second stage, the Delphi Technique (DT) was employed to screen the identified variables and achieve expert consensus, with the participation of specialists in health economics and healthcare management. The final set of variables was determined and refined through several rounds of expert consultation and statistical analysis of the panelists' responses. The findings led to the identification and validation of a standardized set of key performance indicators. The input variables included the number of specialist physicians and annual patient expenditures. The COVs, which link consecutive time periods, comprised the number of active beds and occupied bed-days. The output variables consisted of the number of surgical procedures, number of discharged patients, and bed turnover interval. These indicators are consistent with the operational characteristics of HSCs and are suitable for application in Dynamic Data Envelopment Analysis (DDEA) models. The primary contribution of this study is the development of an operational framework that not only assists researchers in constructing more robust dynamic efficiency assessment models but also provides healthcare managers with an effective tool for analyzing performance trajectories over time and identifying sustainability bottlenecks within HSCs.