  Outpatient clinics often run behind schedule due to patients who arrive late
or appointments that run longer than expected. We sought to develop a
generalizable method that would allow healthcare providers to diagnose problems
in workflow that disrupt the schedule on any given provider clinic day. We use
a constraint optimization problem to identify the least number of appointment
modifications that make the rest of the schedule run on-time. We apply this
method to an outpatient clinic at Vanderbilt. For patient seen in this clinic
between March 27, 2017 and April 21, 2017, long cycle times tended to affect
the overall schedule more than late patients. Results from this workflow
diagnosis method could be used to inform interventions to help clinics run
smoothly, thus decreasing patient wait times and increasing provider
utilization.
