An Agile Systems Modeling Framework for Bed Resource Planning During COVID-19 Pandemic in Singapore.

Abstract

Background

The COVID-19 pandemic has had a major impact on health systems globally. The sufficiency of hospitals' bed resource is a cornerstone for access to care which can significantly impact the public health outcomes.

Objective

We describe the development of a dynamic simulation framework to support agile resource planning during the COVID-19 pandemic in Singapore.

Materials and methods

The study data were derived from the Singapore General Hospital and public domain sources over the period from 1 January 2020 till 31 May 2020 covering the period when the initial outbreak and surge of COVID-19 cases in Singapore happened. The simulation models and its variants take into consideration the dynamic evolution of the pandemic and the rapidly evolving policies and processes in Singapore.

Results

The models were calibrated against historical data for the Singapore COVID-19 situation. Several variants of the resource planning model were rapidly developed to adapt to the fast-changing COVID-19 situation in Singapore.

Conclusion

The agility in adaptable models and robust collaborative management structure enabled the quick deployment of human and capital resources to sustain the high level of health services delivery during the COVID-19 surge.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.3389/fpubh.2022.714092

Publication Info

Lam, Sean Shao Wei, Ahmad Reza Pourghaderi, Hairil Rizal Abdullah, Francis Ngoc Hoang Long Nguyen, Fahad Javaid Siddiqui, John Pastor Ansah, Jenny G Low, David Bruce Matchar, et al. (2022). An Agile Systems Modeling Framework for Bed Resource Planning During COVID-19 Pandemic in Singapore. Frontiers in public health, 10. p. 714092. 10.3389/fpubh.2022.714092 Retrieved from https://hdl.handle.net/10161/25449.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Matchar

David Bruce Matchar

Professor of Medicine

My research relates to clinical practice improvement - from the development of clinical policies to their implementation in real world clinical settings. Most recently my major content focus has been cerebrovascular disease. Other major clinical areas in which I work include the range of disabling neurological conditions, cardiovascular disease, and cancer prevention.
Notable features of my work are: (1) reliance on analytic strategies such as meta-analysis, simulation, decision analysis and cost-effectiveness analysis; (2) a balancing of methodological rigor the needs of medical professionals; and (3) dependence on interdisciplinary groups of experts.
This approach is best illustrated by the Stroke Prevention Patient Outcome Research Team (PORT), for which I served as principal investigator. Funded by the AHCPR, the PORT involved 35 investigators at 13 institutions. The Stroke PORT has been highly productive and has led to a stroke prevention project funded as a public/private partnership by the AHCPR and DuPont Pharma, the Managing Anticoagulation Services Trial (MAST). MAST is a practice improvement trial in 6 managed care organizations, focussing on optimizing anticoagulation for individuals with atrial fibrillation.
I serve as consultant in the general area of analytic strategies for clinical policy development, as well as for specific projects related to stroke (e.g., acute stroke treatment, management of atrial fibrillation, and use of carotid endarterectomy.) I have worked with AHCPR (now AHRQ), ACP, AHA, AAN, Robert Wood Johnson Foundation, NSA, WHO, and several pharmaceutical companies.
Key Words: clinical policy, disease management, stroke, decision analysis, clinical guidelines


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