Patient regional index: a new way to rank clinical specialties based on outpatient clinics big data.

Abstract

Background: Many existing healthcare ranking systems are notably intricate. The standards for peer review and evaluation often differ across specialties, leading to contradictory results among various ranking systems. There is a significant need for a comprehensible and consistent mode of specialty assessment.

Methods: This quantitative study aimed to assess the influence of clinical specialties on the regional distribution of patient origins based on 10,097,795 outpatient records of a large comprehensive hospital in South China. We proposed the patient regional index (PRI), a novel metric to quantify the regional influence of hospital specialties, using the principle of representative points of a statistical distribution. Additionally, a two-dimensional measure was constructed to gauge the significance of hospital specialties by integrating the PRI and outpatient volume.

Results: We calculated the PRI for each of the 16 specialties of interest over eight consecutive years. The longitudinal changes in the PRI accurately captured the impact of the 2017 Chinese healthcare reforms and the 2020 COVID-19 pandemic on hospital specialties. At last, the two-dimensional assessment model we devised effectively illustrates the distinct characteristics across hospital specialties.

Conclusion: We propose a novel, straightforward, and interpretable index for quantifying the influence of hospital specialties. This index, built on outpatient data, requires only the patients' origin, thereby facilitating its widespread adoption and comparison across specialties of varying backgrounds. This data-driven method offers a patient-centric view of specialty influence, diverging from the traditional reliance on expert opinions. As such, it serves as a valuable augmentation to existing ranking systems.