A constraint programming-based solution approach for medical resident scheduling problems


Topaloglu Ş. A., Ozkarahan I.

COMPUTERS & OPERATIONS RESEARCH, cilt.38, sa.1, ss.246-255, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 1
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.cor.2010.04.018
  • Dergi Adı: COMPUTERS & OPERATIONS RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.246-255
  • Anahtar Kelimeler: Medical resident scheduling, Mixed-integer programming, Constraint programming, Accreditation Council for Graduate Medical Education, Duty hours, COLUMN GENERATION, SLEEP-DEPRIVATION, MODEL, SAFETY
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Persistent calls come from within the graduate medical education community and from external sources for regulating the resident duty hours in order to meet the obligations about the quality of resident education, the well-being of residents themselves, and the quality of patient care services. The report of the Accreditation Council for Graduate Medical Education (ACGME) proposes common program requirements for resident hours. In this paper, we first develop a mixed-integer programming model for scheduling residents' duty hours considering the on-call night, day-off, rest period, and total work-hour ACGME regulations as well as the demand coverage requirements of the residency program. Subsequently, we propose a column generation model that consists of a master problem and an auxiliary problem. The master problem finds a configuration of individual schedules that minimizes the sum of deviations from the desired service levels for the day and night periods. The formulation of this problem is possible by representing the feasible schedules using column variables, whereas the auxiliary problem finds the whole set of feasible schedules using constraint programming. The proposed approach has been tested on a series of problems using real data obtained from a hospital. The results indicate that high-quality schedules can be obtained within a few seconds. (C) 2010 Elsevier Ltd. All rights reserved.