The document discusses using discrete event simulation to model patient flow and reduce wait times in a surgery clinic. It describes: 1) Modeling current clinic processes and resource allocation using business process modeling notation to identify bottlenecks. 2) Collecting time data from patient records and fitting distributions to activity processing times. 3) Simulating clinic operations using actual schedules and time distributions to analyze wait times. 4) Applying a shifting bottleneck heuristic to generate improved schedules, reducing surgical wait times by up to 88.9% in simulations.

1. Process and scheduling improvements to reduce wait times in a surgery clinic
Christopher Parentela, Michael Murynowicz, Talha Hussain, Prof. Dionne Aleman (Supervising Professor)
Department of Mechanical and Industrial Engineering, University of Toronto
Introduction
Patients in the clinic experience long wait times for pre-operative,
surgery and post-operative appointments.
Deviations from the schedule may arise as the result of:
• demand exceeding capacity,
• late patient arrivals,
• variations in employee processing speeds,
• events that lead to re-assessments.
Use of discrete event simulation can lead to insight on system bottlenecks.
Objectives
Model the patient flow, business processes and resource allocation.
Determine the effect of changes to current scheduling methods on
patient wait times.
1. Model the clinic using Business Process Modeling Notation (BPMN) to
determine necessary resources and activities (Figure 1).
2. Data Collection of processing times of each activity. Data was extracted
from 70 Patient Tracking Sheets in which the start and end times of
each activity are recorded for each patient.
3. Distribution Fitting of the data to determine appropriate distributions
for each process.
4. Simulation of clinic operations using existing schedules as patient
arrival times and previously determined distributions for activity
processing times (Figure 2).
Figure 1: High level Business Process Modeling Notation (BPMN)
diagram of activities in a surgery appointment.
Analysis
Recommendations
The shifting bottleneck heuristic [1] with an objective to minimize total
completion times was applied to generate an improved solution to the
flexible job shop scheduling problem (Figure 3). An improved schedule
can be uniquely generated for each operating day based on the expected
number of each appointment type.
Wait times progressively increase in the above schedule. Modification of
the improved schedule to align the first two processes yields additional
improvement in patient wait times. (Figure 4).
Figure 2: Simulation model of the surgery clinic.
Results
Simul8 used to simulate 10 actual schedules and 10 corresponding
modified improved schedules.
Both actual and modified improved schedules used to represent patient
arrivals in the simulation model. Resulting wait times recorded for each.
Surgical wait times for the current schedule may be reduced by 88.9% by
applying the modified improved schedule (Figure 5).
Future Work
Application of the shifting bottleneck heuristic on schedules with various
types of demands.
Demand forecasting to enable the generation of custom schedules in
order to provide adequate capacity that meets demand.
Development of an electronic information system that more accurately
records process times and wait times.
Improved method of sending patient appointment reminders by
implementing a text message and email system to reduce missed
appointments.
Conclusions
The model can be used to approximate patient flows throughout the clinic
and demonstrate the improvements that an improved schedule can have.
Improvements in patient wait times may result from the application of
the shifting bottleneck heuristic to expected number of patients arrivals
in a particular day.
Pre-Op
Post-Op
Surgery
Employees
Time (Minutes)
Figure 3: Gantt Chart showing the results of the improvement algorithm.
Boxes of the same colour represent a unique patient.
Figure 4: Gantt Chart showing the results of modified improved schedule.
Reception
Clinical
Assistant
Technician1
Doctor
Clinic
Counselor
Surgery
Counselor
Surgeon
Technician2
Reception
Clinical
Assistant
Technician1
Doctor
Clinic
Counselor
Surgery
Counselor
Surgeon
Technician2
Figure 5: Reduction in wait
times, particularly in surgical
appointments, as a result of
implementing the proposed
scheduling techniques.
References
1. Michael L. Pinedo, Scheduling: Theory, Algorithms, and Systems, Springer
Publishing Company, Incorporated, 2008
Time (Minutes)