Integrated decision making in healthcare : an operations research and management science perspective

Hulshof, P.J.H.

doi:10.3990/1.9789036508582

Cited by 1 publication

(1 citation statement)

References 438 publications

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“…In many cases, it is also possible to approximate this behavior. For more complex processes (patients through several hospital units subject to several chained decisions; Patrick et al., ; Hulshof, ), Markov and semi‐Markov processes, or Bayesian networks and simulations give strong assistance in decision analysis and decision support. The strength of these techniques seems to be useful for monitoring flow and diagnosis of patients through different facilities, but also useful for outpatient care settings (Swisher et al., ; Côté and Stein, ; Salzarulo et al., ).…”

Section: Previous Researchmentioning

confidence: 99%

Waiting‐time estimation in walk‐in clinics

Montecinos

Ouhimmou

Chauhan

2016

Int Trans Operational Res

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Medical assistance is offered by walk-in clinics (WC). These clinics must keep track of patients' turn in line. Some private companies offer an extra follow-up service to WC patients, which notifies them when their consultation approaches, so patients can use their free time elsewhere than in the waiting room. This paper aims to develop an applied forecasting approach for consultation service time estimation and waiting-time estimation. A model based on particle filters and mixture models helps to estimate the waiting time for each consultation, using historical and new incoming data from patient consultations. The system considers two types of patients, namely, regular and follow-up. Our method gives an estimate of the waiting time for consultation better than simple statistics.

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