Modeling Patient No-Show History and Predicting Future Outpatient Appointment Behavior in the Veterans Health Administration

ABSTRACT Background: Missed appointments reduce the efficiency of the health care system and negatively impact access to care for all patients. Identifying patientsat risk for missing an appointment could help health care systems and providers better target interventions to reduce patient no-shows. Objectives: Our aim was to develop and test a predictive model that identifies patientsthat have a high probability of missing their outpatient appointments. Methods: Demographic information, appointment characteristics, and attendance history were drawn from the existing data sets from four Veterans Affairshealth care facilities within six separate service areas. Past attendance behavior was modeled using an empirical Markov model based on up to 10 previous appointments. Using logistic regression, we developed 24 unique predictive models. We implemented the models and tested an intervention strategy using live reminder calls placed 24, 48, and 72 hours ahead of time. The pilot study targeted 1,754 high-risk...