Evaluation of Booking Systems for Elective Surgery Using Simulation Experiments

“…In general, pooling referrals reduces the amount of time needed to schedule the surgery, but it can dramatically increase the amount of time the patient spends waiting for the surgery for nonurgent patients. Sobolev et al [31] conducted a simulation study to compare two methods for booking elective surgery: booking from waiting lists and the direct booking of the surgery dates at the time of the decision. They evaluated cancellations and the patient waiting time and demonstrated that booking from a waiting list can reduce cancellations among urgent patients but that it can increase the waiting time for non-urgent patients.…”

Section: Literature Reviewmentioning

confidence: 99%

“…First, the priority given to a patient at the beginning is not affected by his or her waiting time. Simulation studies proposed by Vasilakis et al [35] and Sobolev et al [31] demonstrated that the patient priority should change over time by showing that the time-evolving priority prevents the waiting time for non-urgent patients from increasing tremendously. Second, because they ignored waiting costs when patients wait less than the maximum recommended waiting time, low-priority patients face delayed access to their treatment until the recommended waiting time.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This work is motivated mainly by previous empirical research suggesting that the waiting time for urgent patients is significantly shorter than that for nonurgent patients [30,31,35]. The delayed access to surgery causes the deterioration of the patient's condition, which can increase the likelihood of adverse events such as emergency admission, death or a change of the attending physician.…”

Section: Introductionmentioning

confidence: 99%

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Managing a patient waiting list with time-dependent priority and adverse events

Min

Yih

2013

RAIRO-Oper. Res.

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This paper addresses the problem of managing a waiting list for elective surgery to decide the number of patients selected from the waiting list and to schedule them in accordance with the operating room capacity in the next period. The waiting list prioritizes patients not only by their initial urgency level but also by their waiting time. Selecting elective surgery patients requires a balance between the waiting time for urgent patients and that for less urgent patients. The problem is formulated as an infinite horizon Markov Decision Process. Further, the study proposes a scheduling procedure based on structural properties of an optimal policy by taking a sampling-based finite horizon approximation approach. Finally, we examine the performance of the policy under various conditions.Article published by EDP Sciences c EDP Sciences, ROADEF, SMAI 2013Theorem 4.1. If v N +1 (s) = 0 for all s, then, J n (s, a) is jointly convex in s and u and v n (s) is convex in s for all n = 1, 2, . . . , N.Proof. The proof is given by induction on n.Here v N +1 (s) and J N (s, u) are convex by assumption and Proposition 4.3. Assuming that the results hold for n, v n (s) and J n (s, u) are convex. We now show that the results hold also for n − 1. Because both v n (s) and c (s, u) are convex, J n−1 (s, u) is also convex. The convexity of J n−1 (s, u) supports that v n−1 (s) is convex.

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“…The bulk of the existing literature on the interaction between emergency and elective activities consists of simulation‐based studies reported in the health operations management literature. These studies predict how, given a capacity constraint and scheduling principle, the admission of emergency patients affects waiting times and cancellations of elective surgery patients (Vassilacopoulos, ; Bagust et al ., ; Harper, ; VanBerkel and Blake, ; Sobolev et al ., ). Other studies are qualitative, discussing the competing uses of hospital beds (Richardson and Mountain, ).…”

Section: Introductionmentioning

confidence: 99%

Emergency Admissions and Elective Surgery Waiting Times

2012

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An average patient waits between 2 and 3 months for an elective procedure in Australian public hospitals. Approximately 60% of all admissions occur through an emergency department, and bed competition from emergency admission provides one path by which waiting times for elective procedures may be lengthened. In this article, we investigated the extent to which public hospital waiting times are affected by the volume of emergency admissions and whether there is a differential impact by elective patient payment status. The latter has equity implications if the potential health cost associated with delayed treatment falls on public patients with lower ability to pay. Using annual data from public hospitals in the state of New South Wales, we found that, for a given available bed capacity, a one standard deviation increase in a hospital's emergency admissions lengthens waiting times by 19 days on average. However, paying (private) patients experience no delay overall. In fact, for some procedures, higher levels of emergency admissions are associated with lower private patient waiting times. Copyright © 2012 John Wiley & Sons, Ltd.

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Evaluation of Booking Systems for Elective Surgery Using Simulation Experiments

Cited by 10 publications

References 23 publications

An integrative review of a preoperative nursing care structure

An integrative review of a preoperative nursing care structure

Managing a patient waiting list with time-dependent priority and adverse events

Emergency Admissions and Elective Surgery Waiting Times

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