Participants:
Faculty/Clinicians/Staff: Amy Cohn, Sameer Saini, Jacob Kurlander
Students: Hassan Abbas, Henry Ballout, Jackson Bennett, Sara Cahn, Daniel Cao, Ajaay Chandrasekaran, Palaniappan Chellappan, John Cima, Victoria Glunt, Heather Hawkins, Trevor Hoffman, Daniel Huang, Jakob Kiel-Locey, Federico Kulyckyj, Ryan Lentine, Abhilash Raa, Bassel Salka, Meng Sang, Stephanie See, Karmel Shehadeh, Pranjal Singh, Pushpendra (Ishu) Singh, Emily Snitchler, William Yang, Bill Zhang, Brittany Lopez, Chhavi Chaudhry
Project Contact: [email protected]
Project Synopsis:
Colorectal cancer is the most common cancer in both men and women nationwide and is the second leading cause of cancer death in the US. Colonoscopy is one of the methods used to detect this type of cancer and has been shown to reduce the mortality rate by more than 50%. When scheduling Colonoscopy appointment in Endoscopy Clinics, complexity is introduced by the many sources of variability within the system including the uncertainty of arrivals and patient attendance. If patients are scheduled for too short of an appointment, this delays the next appointment and increases patient waiting and provider overtime. If patients are scheduled for too long of an appointment, providers are left with idle time and the capacity of the clinic is underused. The tradeoffs between patient access, quality of care, resource management and utilization, and patient and provider satisfaction make the scheduling of colonoscopies challenging.
To address these operational challenges, the team has designed an optimization-based scheduling tool. Particular attention is paid to the competing schedule metrics, including patient delays, clinic overtime, procedure outcomes, and access time. We also developed an integrated simulation tool for scheduling colonoscopies, which evaluates the scheduling templates and policies concurrently with operational performance of the resulting schedules to understand the tradeoffs. The aim is to find the best ways to schedule colonoscopies while considering criteria such as patient satisfaction, clinic utilization, appointment lead time, appointment delay, staff overtime, and clinical outcomes.
Papers, Posters, & Presentations:
Papers:
- “Analysis of Models for the Stochastic Outpatient Procedure Scheduling Problem.” Shehadeh, K.S., Cohn, A., Epelman, M., European Journal of Operational Research, Volume 279, Issue 3, 16 December 2019, Pages 721-731.
- “Using Stochastic Programming to Solve the Outpatient Appointment Scheduling Problem with Random Service and Arrival Times.” Shehadeh, K.S., Cohn, A., Jiang, R. (Under review).
- “A Distributionally Robust Optimization Approach for Outpatient Colonoscopy Scheduling.” Shehadeh, K.S., Cohn, A., Jiang, R. (Under review).
Posters:
- “Analysis of Stochastic Mixed-Integer Linear Programming Models for the Outpatient Appointment Scheduling Problem.” INFORMS Annual Conference Minority Issues Forum, Phoenix AZ, November 2018.
- “From Big Data to Good Data: Analysis of the Variability in Colonoscopy Appointments.” CHEPS Symposium, Ann Arbor MI, September 2018.
- “Appointment Scheduling at an Outpatient Clinic.” SROP Symposium, Ann Arbor MI, July 2018.
- “Analyzing the Variability in Colonoscopy Appointments Using a VBA-Based Tool to Help in Improving the Schedule.” CHEPS Symposium, Ann Arbor MI, November 2017.
- “Optimization of Colonoscopy Appointment Scheduling Under Uncertainty.” CHEPS Healthcare Executive Summit, Ann Arbor MI, June 2017.
- “Scheduling Colonoscopy Patients in an Outpatient Endoscopy Clinic.” Healthcare Systems Process Improvement Conference, Orlando FL, March 2017.
- “Simulation of Patient Scheduling for Colonoscopy.” Engineering Graduate Symposium, Ann Arbor MI, October 2016.
- “Simulation of Patient Scheduling for Colonoscopy.” CHEPS Symposium, Ann Arbor MI, September 2016.
Presentations:
- “Using Stochastic Programming for Outpatient Appointment Scheduling with Random Service and Arrival Times.” INFORMS Healthcare Conference, Cambridge MA, July 2019.
- “Simulating and Evaluating Scheduling Policies for Colonoscopy Patients with Stochastic Procedure Durations.” INFORMS Healthcare Conference, Cambridge MA, July 2019.
- “A Data-driven Stochastic Optimization Approach to the Colonoscopy Scheduling Problem.” INFORMS Annual Conference, Phoenix AZ, November 2018.
- “Patient-centered and Personalized Scheduling of Colonoscopy Appointments.” INFORMS Annual Conference, Houston TX, October 2017.
- “A Monte Carlo Optimization Framework for Solving the Colonoscopy Scheduling Problem under Uncertainty.” IFORS, Quebec City Canada, July 2017.
- “Scheduling Colonoscopy Patients Under Uncertainty.” IISE Annual Conference. Pittsburg PA, May 2017.
- “Scheduling Colonoscopy Patients Under Uncertainty.” Production and Operations Management Society Conference, Seattle WA, May 2017
- “Scheduling Colonoscopy Patients in an Outpatient Endoscopy Clinic.” Healthcare Systems Process Improvement Conference, Orlando FL, March 2017.
- “Considering No-shows And Procedure Time Variability When Scheduling Endoscopy Patients.” INFORMS Annual Conference, Nashville TN, November 2016.