9. Modelling the Dynamics of Familial Hypercholesterolemia (FH) Screening and Treatment: Insights from Singapore’s Emerging Genomic Testing Initiatives
Invited abstract in session MB-13: Medical services and applications, stream OR in Healthcare (ORAHS).
Monday, 10:30-12:00Room: Clarendon SR 1.01
Authors (first author is the speaker)
| 1. | Alec Morton
|
| Management Science, University of Strathclyde | |
| 2. | Len Malczynski
|
| Mind's Eye Computing | |
| 3. | Jamaica Briones
|
| National University of Singapore | |
| 4. | Jing Lou
|
| National University of Singapore | |
| 5. | Hwee Lin Wee
|
| National University of Singapore | |
| 6. | David Matchar
|
| HSSR, Duke-NUS Medical School |
Abstract
Familial hypercholesterolemia (FH) is a genetic condition that raises cholesterol and increases cardiovascular risk. In Singapore, an estimated 25,000 people have FH, though fewer than 10% are diagnosed. Early screening and statin treatment can prevent severe complications, but a nationwide FH screening program faces significant challenges in capacity and resources. This study presents a dynamic simulation model to explore strategies for FH screening, diagnosis, and management, informed by stakeholder insights.
The model simulates FH screening and treatment dynamics in Singapore, identifying strategies to meet rising demand within limited healthcare capacity. Through Group Model Building (GMB), we engaged clinicians, administrators, and policymakers to pinpoint key factors affecting FH screening and capacity constraints. These elements were integrated into a system dynamics model, highlighting interactions between referral flows, screening limits, and workforce shortages.
Cascade testing, which screens family members, may overwhelm primary and specialty care without resource expansion. Triaging by LDL levels and expanding primary care roles in initial screenings could alleviate some pressure on specialty clinics. Decentralizing testing and increasing genetic counseling capacity are also crucial for scalability. This model provides a tool for policymakers to balance screening demand with healthcare capacity, supporting large-scale genomic testing initiatives.
Keywords
- Health Care
Status: accepted
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