Appointment Pathways: Yield Management via Cause-and-Effect Modeling in the Outpatient Setting at Mayo Clinic.

Abstract

Patients have multiple outpatient appointments for various reasons. Analyzing patients' related appointments provides insight into referral patterns, leading to recommendations for ideal care and more efficient planning. We model these appointments with causal graphs via Judea Pearl's causal graph approach. Once we define the causal relationships in the appointment data, we leverage a graph database and visualization software to investigate valuable patterns and relationships in patient care over time. The Pathways tool allows yield management at specialty, provider, or appointment levels. Leaders use this tool to anticipate a patient's downstream appointments; the tool provides insights into staffing and the impact of growing demand.