Using No-Show Modeling to Improve Clinic Performance

Laura P. Sands, Purdue University
Joanne Daggy, Purdue University
Deanna Willis, Purdue University
Debra Thayer, Richard L. Roudebush Veterans Affairs Medical Center
Christopher Suelzer, Richard L. Roudebush Veterans Affairs Medical Center
Po-Ching DeLaurentis, Purdue University
Ayten Turkan, Purdue University
Santanu Chakraborty, Purdue University

Was originally published in Health Informactics Journal through Sage Publications


‘No-shows’ or missed appointments result in under-utilized clinic capacity. We develop a logistic regression model using electronic medical records to estimate patients’ no-show probabilities and illustrate the use of the estimates in creating clinic schedules that maximize clinic capacity utilization while maintaining small patient waiting times and clinic overtime costs. This study used information on scheduled outpatient appointments collected over a three-year period at a Veterans Affairs medical center. The call-in process for 400 clinic days was simulated and for each day, two schedules were created: the traditional method that assigned one patient per appointment slot and the proposed method that scheduled patients according to their no-show probability to balance patient waiting, overtime and revenue. Patient no-show models together with advanced scheduling methods would allow more patients to be seen a day while improving clinic efficiency. Clinics should consider the benefits of implementing scheduling software that include these methods relative to the cost of no-shows.