ArticleJournal of medical systems2022
A Simulation Modelling Study of Referral Distribution Policies in a Centralized Intake System for Surgical Consultation.
Article in Journal of medical systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Effect of single-entry referral models and team-based care on wait times for hip and knee joint replacement in Ontario: a simulation study.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2025Article
- COVID-related delays in non-urgent adult surgeries: comparing population-based results from two Canadian provinces.Frontiers in surgery · 2025Article
- Streamlining lung cancer management in Nova Scotia amid COVID-19: pooled triaging for expedited curative-intent oncologic surgery.Canadian journal of surgery. Journal canadien de chirurgieArticle
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Delays beyond recommended wait times, especially for specialist services, are associated with adverse health outcomes. The Alberta Surgical Initiative aims to improve the referral wait time-the time between a referral is received at the central intake to the time a specialist sees the patient. Using the discrete event simulation modelling approach, we evaluated and compared the impact of four referral distribution policies in a central intake system on three system performance measures (number of consultations, referral wait time and surgeon utilization). The model was co-designed with clinicians and clinic staff to represent the flow of patients through the system. We used data from the Facilitated Access to Surgical Treatment (FAST) centralized intake referral program for General Surgery to parameterize the model. Four distribution policies were evaluated - next-available-surgeon, sequential, "blackjack," and "kanban." A sequential distribution of referrals for surgical consultation among the surgeons resulted in the worst performance in terms of the number of consultations, referral wait time and surgeon utilization. The three other distribution policies are comparable in performance. The "next available surgeon" model provided the most efficient and robust model, with approximately 1,000 more consultations, 100 days shorter referral time and a 14% increase in surgeon utilization. Discrete event simulation (DES) modelling can be an effective tool to illustrate and communicate the impact of the referral distribution policy on system performance in terms of the number of consultations, referral wait time and surgeon utilization.
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Registered trials
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