Innovations in Primary Care
Innovative Panel Management Strategy Benefits Patients Who Need More Intensive Primary Care
Primary care panel sizes are often determined without detailed data on patient complexity, which can strain access to care and contribute to clinician burnout. Geisinger Health System used Charlson Comorbidity Health Analytics (CCHA) and Needs-Based Segmentation (NBS) tools to support complexity-based panel management across 45 primary care clinics serving more than 350,000 patients. CCHA estimates the likelihood of high health care costs or unplanned utilization based on chronic conditions, while NBS groups patients by their level of ambulatory care need. These tools were integrated into the electronic health record to assign each patient a CCHA score and NBS category. Using this information, Geisinger clinicians first decided how long visits should be and how often patients with more complex conditions should be seen. Researchers from the University of Chicago then used optimization modeling to test how scheduling factors—such as visit duration, visit frequency, and appointment types—could inform panel size. Using these tools allowed the health system to shift from scheduling appointment length based on patient age to scheduling based on clinical complexity. This approach helped focus limited resources, reduce variability in care, and prioritize continuity and visit frequency for patients who may benefit from more intensive primary care.
Bobbie Johannes, PhD, MPH, et al
Department of Population Health Sciences, Geisinger College of Health Sciences, Danville, Pennsylvania
