Predictors of Clinic and Appointment Duration in a First-Come-First-Served, Student-Run, Free Medical Veterinary Clinic

Background: The Midwestern University College of Veterinary Medicine hosts student-run clinics that offer free veterinary services to underserved populations. This study sought to determine predictors of clinic and appointment durations and the feasibility of a capacity-based scheduling system using factors identified prior to physical examination. Methods: Medical records, appointment duration, clinic duration, number of patients and number of owners were collected for 20 clinics over 21 months. Detailed patient signalment, history, and physical examination findings were coded for all clinics. Clinic duration was analyzed via linear regression.  Appointment duration was analyzed via multiple multilevel mixed-effects linear regression clustered on date. Results: There were 385 appointments, with 301 (78%) having complete start and end times. Median clinic duration was 8 hours (interquartile range [IQR] 2.7-3.5), with number of patients (B=5.4, p=0.001) being predictive, and estimated optimum number of patients being 16-17 in order to maximize patients seen while minimizing the chance of exceeding 2.5 hours for the clinic. Median appointment duration was 20 minutes (IQR 13-30), with the number of current concerns expressed by owner (B=1.8, p=0.005), number of abnormal findings on physical examination (B=1.9, p<0.001), number of procedures (B=3.0, p<0.001), number of tests (B=4.3, p=0.015) and appointment position (B=-0.8, p<0.001) being significant. Conclusions: No variable available at check-in was found to explain more than 3% of the variation in appointment duration, and no variable available after the comprehensive history-taking process was found to explain more than 14% of variation. Even models that incorporated multiple variables from all stages were only able to explain one-fourth to one-third of the observed variation for either appointment or clinic duration. It is unlikely that a rubric constructed from information available prior to physical examination would be more helpful than number of patients, which explained 61% of clinic duration, for capacity-based scheduling.