A distributionally robust optimization approach for outpatient colonoscopy scheduling

Karmel S. Shehadeh, Amy E.M. Cohn, Ruiwei Jiang

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


We consider the outpatient colonoscopy scheduling problem, recognizing the impact of pre-procedure bowel preparation (prep) quality on the variability in colonoscopy duration. Data from a large academic medical center indicates that colonoscopy durations are bimodal, i.e., depending on the prep quality they can follow two different probability distributions, one for those with adequate prep and the other for those with inadequate prep. We therefore define a distributionally robust outpatient colonoscopy scheduling (DROCS) problem that seeks optimal appointment sequence and schedule to minimize the worst-case weighted expected sum of patient waiting, provider idling, and provider overtime, where the worst-case is taken over an ambiguity set (a family of distributions) characterized through the known mean and support of the prep quality and durations. We derive an equivalent mixed-integer linear programming formulation to solve DROCS. Finally, we present a case study based on extensive numerical experiments in which we draw several managerial insights into colonoscopy scheduling.

Original languageEnglish (US)
Pages (from-to)549-561
Number of pages13
JournalEuropean Journal of Operational Research
Issue number2
StatePublished - Jun 1 2020


  • Appointment scheduling
  • Bimodal service duration
  • Distributionally robust optimization
  • Mixed-integer non-linear and linear programming
  • OR in health services

ASJC Scopus subject areas

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


Dive into the research topics of 'A distributionally robust optimization approach for outpatient colonoscopy scheduling'. Together they form a unique fingerprint.

Cite this