Browsing by Author "Koh, V"

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    Mapping the Dynamic Complexity of Chronic Disease Care in Singapore: Using Group Model Building in Knowledge Elicitation
    (Systems Research and Behavioral Science, 2018-11-01) Ansah, JP; Matchar, DB; Koh, V; Schoenenberger, L
    This study describes a group model building exercise that aims to develop a deeper understanding of the dynamic complexity of chronic disease care delivery within a primary care setting in Singapore, leveraging on the insights of stakeholders with personal and institutional knowledge of the health care system. A group model building exercise, which included 50 stakeholders, was used to develop the qualitative model. The qualitative model helped to bring a feedback perspective to understanding the dynamic complexity of chronic disease care delivery. The feedback perspective helped in identifying the systemic issues within chronic disease care delivery, which has the potential to inform system-wide interventions and policies to improve health. Enhancing chronic care in Singapore will require an enhancement of both the capacity and capability of the primary care sector. © 2018 John Wiley & Sons, Ltd.
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    Modeling manpower requirement for a changing population health needs: The case of ophthalmic nurses and allied health ophthalmic professionals
    (Health Policy and Technology, 2019-09-01) Ansah, JP; Koh, V; De Korne, D; Jayabaskar, T; Matchar, DB; Quek, D
    Background: Prevalence of chronic eye conditions has been shown to increase with age. As the global population continues to age rapidly, the demand for eye care services is expected to increase significantly in the near future, requiring effective health workforce planning in order to provide for the needs of the population. The aim of this paper is to synthesize data from a variety of sources to develop a simulation model based on the systems modelling methodology of system dynamics that links population health needs to workforce requirements to generate evidence-based projections for ophthalmic nurses, and allied health ophthalmic professionals in Singapore. Methods: A system dynamics simulation model was developed with active engagement of key stakeholders—such as ophthalmologists, senior nurses, healthcare planners and managers, and senior technicians—to verify the model structure and assumptions. The model project the future requirement of ophthalmic nurses, technicians and patient service assistants. Results: The number of Singaporeans with eye diseases is projected to more than double by 2040. As a result, the demand for eye care services and eye care workforce is expected to increase significantly under all the plausible scenarios. The increase in eye disease burden is due mainly to population aging—given that the prevalence of eye disease increases with age. Conclusion: This research provides a future demand outlook for ophthalmic nurses, technicians and patient service assistants in Singapore and has implications for recruitment and training of ophthalmic nurses and allied health professionals in Singapore.
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    Modeling to inform long-term care policy and planning for an aging society
    (2017-01-01) Ansah, JP; Koh, V; Qureshi, MA; Matchar, DB
    Demographic changes such as increasing longevity, declining family sizes, and increasing female participation in the labor market have implications for long-term care (LTC) planning for the elderly. As the population in both developed and developing world ages, the prevalence of health conditions such as chronic diseases and disabilities increases. Consequently, the proportion of elderly adults who require assistance with their daily activities rises. Further, the potential decrease in family members available as caregivers implies an increase in the demand for alternative LTC arrangements. Planning of LTC services is fraught with dynamic complexities. Various issues, such as projecting future need, cost, capacity, and quality of care and caregivers—formal and informal—can influence the effectiveness and efficiency of LTC services. The trends outlined point to the need for a comprehensive LTC planning that accounts for all these dynamics changes. This chapter aims to demonstrate the use of simulation modeling as a communication tool that allows for the LTC complexity to be reduced to its essential elements to inform policy for an aging society. The forms of simulation techniques used in the planning of LTC policy and services and real-world applications across different institutional contexts are discussed. Of particular focus is the application of the system dynamics methodology in LTC planning. Three LTC projects using system dynamics methodology are presented. Specifically, these LTC projects comprise the methodological process in the projection of the number of disabled elderly in Singapore accounting for changing educational attainment, the impact of various LTC policies on informal eldercare hours and labor force participation of informal caregivers, and the impact of LTC capacity expansion policies on acute care.
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    Projecting the Number of Elderly with Cognitive Impairment in China Using a Multi-State Dynamic Population Model
    (System Dynamics Review, 2017-04-01) Ansah, JP; Koh, V; Chiu, CT; Chei, CL; Zeng, Y; Yin, ZX; Shi, XM; Matchar, DB
    China is aging rapidly, and the number of Chinese elderly with dementia is expected to rise. This paper projects, up to year 2060, the number of Chinese elderly within four distinct cognitive states. A multi-state population model was developed using system dynamics and parametrized with age–gender-specific transition rates (between intact, mild, moderate and severe cognitive impairment and death) estimated from two waves (2012 and 2014) of a community-based cohort of elderly in China aged ≥65 years (N = 1824). Probabilistic sensitivity analysis and the bootstrap method was used to obtain the 95% confidence interval of the transition rates. The number of elderly with any degree of cognitive impairment increases; with severe cognitive impairment increasing the most, at 698%. Among elderly with cognitive impairment, the proportion of very old elderly (age ≥ 80) is expected to rise from 53% to 78% by 2060. This will affect the demand for social and health services China. Copyright © 2017 System Dynamics Society.