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Strategic planning to reduce the burden of stroke among veterans: using simulation modeling to inform decision making.

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Date
2014-07
Authors
Lich, Kristen Hassmiller
Tian, Yuan
Beadles, Christopher A
Williams, Linda S
Bravata, Dawn M
Cheng, Eric M
Bosworth, Hayden B
Homer, Jack B
Matchar, David B
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Abstract
BACKGROUND AND PURPOSE: Reducing the burden of stroke is a priority for the Veterans Affairs Health System, reflected by the creation of the Veterans Affairs Stroke Quality Enhancement Research Initiative. To inform the initiative's strategic planning, we estimated the relative population-level impact and efficiency of distinct approaches to improving stroke care in the US Veteran population to inform policy and practice. METHODS: A System Dynamics stroke model of the Veteran population was constructed to evaluate the relative impact of 15 intervention scenarios including both broad and targeted primary and secondary prevention and acute care/rehabilitation on cumulative (20 years) outcomes including quality-adjusted life years (QALYs) gained, strokes prevented, stroke fatalities prevented, and the number-needed-to-treat per QALY gained. RESULTS: At the population level, a broad hypertension control effort yielded the largest increase in QALYs (35,517), followed by targeted prevention addressing hypertension and anticoagulation among Veterans with prior cardiovascular disease (27,856) and hypertension control among diabetics (23,100). Adjusting QALYs gained by the number of Veterans needed to treat, thrombolytic therapy with tissue-type plasminogen activator was most efficient, needing 3.1 Veterans to be treated per QALY gained. This was followed by rehabilitation (3.9) and targeted prevention addressing hypertension and anticoagulation among those with prior cardiovascular disease (5.1). Probabilistic sensitivity analysis showed that the ranking of interventions was robust to uncertainty in input parameter values. CONCLUSIONS: Prevention strategies tend to have larger population impacts, though interventions targeting specific high-risk groups tend to be more efficient in terms of number-needed-to-treat per QALY gained.
Type
Journal article
Subject
Veterans
comparative effectiveness research
computer simulation
health planning
stroke
Adult
Calibration
Computer Simulation
Cost of Illness
Decision Making
Health Planning
Humans
Quality-Adjusted Life Years
Risk Factors
Sensitivity and Specificity
Stroke
Stroke Rehabilitation
Systems Theory
Uncertainty
United States
United States Department of Veterans Affairs
Veterans
Veterans Health
Permalink
https://hdl.handle.net/10161/13105
Published Version (Please cite this version)
10.1161/STROKEAHA.114.004694
Publication Info
Lich, Kristen Hassmiller; Tian, Yuan; Beadles, Christopher A; Williams, Linda S; Bravata, Dawn M; Cheng, Eric M; ... Matchar, David B (2014). Strategic planning to reduce the burden of stroke among veterans: using simulation modeling to inform decision making. Stroke, 45(7). pp. 2078-2084. 10.1161/STROKEAHA.114.004694. Retrieved from https://hdl.handle.net/10161/13105.
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.
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Scholars@Duke

Bosworth

Hayden Barry Bosworth

Professor in Population Health Sciences
Dr. Bosworth is a health services researcher and Associate Director of the Center for Health Services Research in Primary Care at the Durham VA Medical Center. He is also a Professor of Medicine, Psychiatry, and Nursing at Duke University Medical Center and Adjunct Professor in Health Policy and Administration at the School of Public Health at the University of North Carolina at Chapel Hill. His research interests comprise three overarching areas of research: 1) clinical research that provide
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 analy
Alphabetical list of authors with Scholars@Duke profiles.
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Rights for Collection: Scholarly Articles

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