Implications of long-term care capacity response policies for an aging population: a simulation analysis.
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2014-05
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Abstract
Introduction
The demand for long-term care (LTC) services is likely to increase as a population ages. Keeping pace with rising demand for LTC poses a key challenge for health systems and policymakers, who may be slow to scale up capacity. Given that Singapore is likely to face increasing demand for both acute and LTC services, this paper examines the dynamic impact of different LTC capacity response policies, which differ in the amount of time over which LTC capacity is increased, on acute care utilization and the demand for LTC and acute care professionals.Methods
The modeling methodology of System Dynamics (SD) was applied to create a simplified, aggregate, computer simulation model for policy exploration. This model stimulates the interaction between persons with LTC needs (i.e., elderly individuals aged 65 years and older who have functional limitations that require human assistance) and the capacity of the healthcare system (i.e., acute and LTC services, including community-based and institutional care) to provide care. Because the model is intended for policy exploration, stylized numbers were used as model inputs. To discern policy effects, the model was initialized in a steady state. The steady state was disturbed by doubling the number of people needing LTC over the 30-year simulation time. Under this demand change scenario, the effects of various LTC capacity response policies were studied and sensitivity analyses were performed.Results
Compared to proactive and quick adjustment LTC capacity response policies, slower adjustment LTC capacity response policies (i.e., those for which the time to change LTC capacity is longer) tend to shift care demands to the acute care sector and increase total care needs.Conclusions
Greater attention to demand in the acute care sector relative to demand for LTC may result in over-building acute care facilities and filling them with individuals whose needs are better suited for LTC. Policymakers must be equally proactive in expanding LTC capacity, lest unsustainable acute care utilization and significant deficits in the number of healthcare professionals arise. Delaying LTC expansion could, for example, lead to increased healthcare expenditure and longer wait lists for LTC and acute care patients.Type
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Ansah, John P, Robert L Eberlein, Sean R Love, Mary Ann Bautista, James P Thompson, Rahul Malhotra and David B Matchar (2014). Implications of long-term care capacity response policies for an aging population: a simulation analysis. Health policy (Amsterdam, Netherlands), 116(1). pp. 105–113. 10.1016/j.healthpol.2014.01.006 Retrieved from https://hdl.handle.net/10161/22886.
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David Bruce Matchar
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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