Leveraging Big Data to Balance New Key Performance Indicators in Emergency Physician Management Networks

Managing emergency physicians is a complex task and has increasingly intensified with the recent consolidation of many emergency departments (EDs). Large‐scale physician groups are facing challenges in resource deployment and performance evaluation. To objectively evaluate physicians across facilities, we leverage big data from an emergency physician management network and propose data‐driven metrics using a large‐scale database consisting of 84 hospitals, 1,079 physicians, and 10,615,879 patient visits in 14 states over 600,000 clinical shifts from 2010 to 2014. To ensure physicians are fairly evaluated and compensated within diverse facilities, we propose an index system and use clustering to help identify factors which might impact physician performance. The proposed indices benchmark physicians from the perspectives of revenue potential, patient volume, patient complexity, and patient experience by controlling for exogenous factors at the facility level. We empirically show the volume and complexity indices are key elements of the revenue potential index, and use two‐stage least squares regression to relate volume and complexity and uncover their drivers. Revenue potential and patient experience are found to be positively correlated, which suggests productive physicians are often liked by their patients. Through implementing the proposed evaluation system, administrators can better manage and incentivize physicians and provide directions for performance improvement, while controlling for location idiosyncrasies. The proposed framework can also be adapted to non‐medical professional settings such as value chains, where employees often provide services in various profit‐ and cost‐centers.