Improving primary care access using simulation optimization

Primary care providers (PCPs) provide the majority of care patients receive during their lifetime. We consider the problem of determining the size and composition of physician panels in primary care. A physician´s panel consists of a set of patients and each patient belongs to one of many different health-related categories. Using real data collected at the Mayo Clinic at Rochester, we propose a multi-period metaheuristic simulation optimization model for determining the panel design of a set of physicians working in a primary care environment. The model seeks to maximize patient visits to their own providers, reduce waiting times, and minimize overage.