TY - JOUR
T1 - A distributionally robust optimization approach for outpatient colonoscopy scheduling
AU - Shehadeh, Karmel S.
AU - Cohn, Amy E.M.
AU - Jiang, Ruiwei
N1 - Funding Information:
We are grateful for the insights of our clinical collaborators Dr. Jacob Kurlander and Dr. Sameer Saini. This work is supported in part by the Agency for Healthcare Research and Quality ( P30HS024385 ), the National Science Foundation ( CMMI-1662774 ), and the University of Michigan Center for Healthcare Engineering and Patient Safety (CHEPS).
Funding Information:
We are grateful for the insights of our clinical collaborators Dr. Jacob Kurlander and Dr. Sameer Saini. This work is supported in part by the Agency for Healthcare Research and Quality (P30HS024385), the National Science Foundation (CMMI-1662774), and the University of Michigan Center for Healthcare Engineering and Patient Safety (CHEPS).
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
KW - Appointment scheduling
KW - Bimodal service duration
KW - Distributionally robust optimization
KW - Mixed-integer non-linear and linear programming
KW - OR in health services
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U2 - 10.1016/j.ejor.2019.11.039
DO - 10.1016/j.ejor.2019.11.039
M3 - Article
AN - SCOPUS:85076848588
SN - 0377-2217
VL - 283
SP - 549
EP - 561
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -