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Article

Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System

1
Institute for Health Systems Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam 40170, Malaysia
2
Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, Sintok 06010, Malaysia
3
Hospital Pakar Sultanah Fatimah, Muar 84000, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editor: Daniele Giansanti
Healthcare 2022, 10(2), 189; https://doi.org/10.3390/healthcare10020189
Received: 17 December 2021 / Revised: 7 January 2022 / Accepted: 7 January 2022 / Published: 19 January 2022
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 (p < 0.01). Public patients have longer wait times than private patients in this study’s dual practice setting. Scenario analyses showed that early consultation start time that matches patient arrival time and staggered arrival could reduce the overall TT for public and private patients by 40% and 21%, respectively. Similarly, the number of patients waiting at the clinic per hour could be reduced by 10–21% during clinic peak hours. Matching consultation start time with staggered patient arrival can potentially reduce wait times and crowding, especially for public patients, without incurring additional resource needs and help narrow the wait time gap between public and private patients. Healthcare managers and policymakers can consider simulation approaches for the monitoring and improvement of healthcare operational efficiency to meet rising healthcare demand and costs. View Full-Text
Keywords: wait times; discrete event simulation; dual practice; outpatient; arrival pattern; crowding wait times; discrete event simulation; dual practice; outpatient; arrival pattern; crowding
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MDPI and ACS Style

Fun, W.H.; Tan, E.H.; Khalid, R.; Sararaks, S.; Tang, K.F.; Ab Rahim, I.; Md. Sharif, S.; Jawahir, S.; Sibert, R.M.Y.; Nawawi, M.K.M. Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System. Healthcare 2022, 10, 189. https://doi.org/10.3390/healthcare10020189

AMA Style

Fun WH, Tan EH, Khalid R, Sararaks S, Tang KF, Ab Rahim I, Md. Sharif S, Jawahir S, Sibert RMY, Nawawi MKM. Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System. Healthcare. 2022; 10(2):189. https://doi.org/10.3390/healthcare10020189

Chicago/Turabian Style

Fun, Weng H., Ee H. Tan, Ruzelan Khalid, Sondi Sararaks, Kar F. Tang, Iqbal Ab Rahim, Shakirah Md. Sharif, Suhana Jawahir, Raoul M.Y. Sibert, and Mohd K.M. Nawawi. 2022. "Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System" Healthcare 10, no. 2: 189. https://doi.org/10.3390/healthcare10020189

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