ArticleHealthcare (Basel, Switzerland)2022
Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System.
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Early health technology assessment of a primary care tool for the diagnosis and management of headaches in Alberta, Canada.International journal of technology assessment in health care · 2026Article
- A Next Available Appointment (NAA) Tool to Better Manage Patient Delay Risk and Patient Scheduling Expectations in Specialist Clinics.The International journal of health planning and management · 2025Article
- Does a GP service package matter in addressing the absence of health management by the occupational population? A modelling study.BMC health services research · 2024Article
- Analysis of Patient Satisfaction through the Effect of Healthcare Spending on Waiting Times for Consultations and Operations.Healthcare (Basel, Switzerland) · 2022Article
- Time Matters: A Review of Current Radiotherapy Practices and Efficiency Strategies.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Long wait times and crowding are major issues affecting outpatient service delivery, but it is unclear how these affect patients in dual practice settings. This study aims to evaluate the effects of changing consultation start time and patient arrival on wait times and crowding in an outpatient clinic with a dual practice system. A discrete event simulation (DES) model was developed based on real-world data from an Obstetrics and Gynaecology (O&G) clinic in a public hospital. Data on patient flow, resource availability, and time taken for registration and clinic processes for public and private patients were sourced from stakeholder discussion and time-motion study (TMS), while arrival times were sourced from the hospital's information system database. Probability distributions were used to fit these input data in the model. Scenario analyses involved configurations on consultation start time/staggered patient arrival. The median registration and clinic turnaround times (TT) were significantly different between public and private patients (
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Registered trials
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