Emergency department performance assessment using administrative data: A managerial framework

Administrative data play an important role in performance monitoring of healthcare providers. Nonetheless, little attention has been given so far to the emergency department (ED) evaluation. In addition, most of existing research focuses on a single core ED function, such as treatment or triage, thus providing a limited picture of performance. The goal of this study is to harness the value of routinely produced records proposing a framework for multidimensional performance evaluation of EDs able to support internal decision stakeholders in managing operations. Starting with the overview of administrative data, and the definition of the desired framework’s characteristics from the perspective of decision stakeholders, a review of the academic literature on ED performance measures and indicators is conducted. A performance measurement framework is designed using 224 ED performance metrics (measures and indicators) satisfying established selection criteria. Real-world feedback on the framework is obtained through expert interviews. Metrics in the proposed ED performance measurement framework are arranged along three dimensions: performance (quality of care, time-efficiency, throughput), analysis unit (physician, disease etc.), and time-period (quarter, year, etc.). The framework has been judged as “clear and intuitive”, “useful for planning”, able to “reveal inefficiencies in care process” and “transform existing data into decision support information” by the key ED decision stakeholders of a teaching hospital. Administrative data can be a new cornerstone for health care operation management. A framework of ED-specific indicators based on administrative data enables multi-dimensional performance assessment in a timely and cost-effective manner, an essential requirement for nowadays resource-constrained hospitals. Moreover, such a framework can support different stakeholders’ decision making as it allows the creation of a customized metrics sets for performance analysis with the desired granularity.