Patient-centric surgeons’ case mix problem

Abstract

This paper studies a single-period tactical planning problem to find the surgeons’ case mix of a hospital surgical unit such that the total patient value per dollar spent on healthcare resources (the TPV) is maximized. We represent the relationship between the surgeons’ volume and patient outcomes using the learning curve. We formulate the problem as a nonlinear integer programming model. The problem belongs to the class of nonquadratic transportation problems in which it is proven that no algorithm solving the problem in strongly polynomial time exists. We develop a Lagrangian-based heuristic solution approach that exploits the special structure of the problem. Using simulated and real data, we show that the diversity in surgeons’ experience complements a surgical unit in a way that good patient outcomes of experienced surgeons counterbalance the average but improving patient outcomes of less experienced surgeons while the less experienced surgeons gain more experience.