Personalized Healthcare Outcome Analysis of Cardiovascular Surgical Procedures.

Wang, Guihua; Li, Jun; Hopp, Wallace J.

Problem definition: This study addresses three important questions concerning personalized healthcare: (1) Are outcome differences between hospitals heterogeneous across patients with different features? (2) If they are, how do the best quality hospitals identified using patient-centric information differ from those identified using population-average information? (3) How much will hospitals' pay-for-performance reimbursements change if their performance is measured based on patient-centric information? Methodology/results: Using patient-level data from 35 hospitals for six cardiovascular surgeries in New York State, we identify patient groups that exhibit significant differences in outcomes with a recently developed instrumental variable tree approach. We find outcome differences between hospitals are heterogeneous not only across procedure types, but also along other dimensions such as patient age and comorbidities. For around 80% of patients, the best quality hospitals indicated by patient-centric information are different from those indicated as best according to population-average information. Managerial implications: We compare potential outcomes when patients are treated at the best quality hospitals based on the two types of information and find complications could be reduced by using patient-centric information instead of population-average information. We also use our model to illustrate how patient-centric information can enhance pay-for-performance programs offered by payers and guide hospitals in targeting quality-improvement efforts. History: This paper was a finalist in the 2017 MSOM Student Paper Competition. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1227.

NEW York (State); OPERATIVE surgery; SCHOOL contests; PATIENT education; MEDICAL care; CARDIOVASCULAR surgery; PREOPERATIVE education; HOSPITAL utilization; DIAGNOSIS related groups

Manufacturing & Service Operations Management (M&SOM), 2023, Vol 25, Issue 4, p1567

1526-5498

Academic Journal

10.1287/msom.2023.1227