Integrated scheduling of tasks and gynecologists to improve patient appointment scheduling: a case study

N.M. van de Vrugt (Corresponding Author), S.T. Luen-English, W.A.P. Bastiaansen, S. Kleinluchtenbeld, W.T.P. Lardinois, M.H. Pots, D.H. Schoonbergen, E.W. Hans, J.L. Hurink, R.J. Boucherie

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
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Like many hospital departments, the gynecology department of the Jeroen Bosch Hospital experienced difficulties with scheduling outpatient appointments at the medically preferred times. Despite the time invested in creating the schedule, the compliance of the achieved schedules with the preferences of gynecologists is low, and the number of scheduled outpatient clinic hours is unbalanced over the weeks. To overcome this unbalanced scheduling, we develop a scheduling methodology that, opposed to existing methods, simultaneously assigns task types and gynecologists to shifts. This enables us to (1) explore the complete solution space to obtain better schedules, and (2) take into account different specializations and working hours of the gynecologists. To this end, we first present a Mixed Integer Linear Programming (MIP) approach for this scheduling problem that has the objective to increase compliance of the soft constraints. Preliminary results achieved with this MIP model show the potential of the chosen approach and were the motivation to develop two heuristic approaches, which are better suited for practical purposes. Based on several realistic test instances, the scheduling approaches appear promising for the hospital to apply for gynecologist scheduling, as they improve patient access times, comply better with preferences of the gynecologists, significantly reduce the time spent on creating the schedules, and do not require MIP solvers.
Original languageEnglish
Pages (from-to)10-19
Number of pages10
JournalOperations research for health care
Early online date8 Dec 2017
Publication statusPublished - 1 Mar 2018


  • Heuristics
  • Health Care
  • Physician scheduling
  • Integer programming


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