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

Kristen Hassmiller Lich; Yuan Tian; Christopher A Beadles; Linda S Williams; Dawn M Bravata; Eric M Cheng; Hayden B Bosworth; Jack B Homer; David B Matchar

doi:10.1161/STROKEAHA.114.004694

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

Stroke. 2014 Jul;45(7):2078-84. doi: 10.1161/STROKEAHA.114.004694. Epub 2014 Jun 12.

Authors

Kristen Hassmiller Lich¹, Yuan Tian², Christopher A Beadles², Linda S Williams², Dawn M Bravata², Eric M Cheng², Hayden B Bosworth², Jack B Homer², David B Matchar²

Affiliations

¹ From the Department of Health Policy and Management, The University of North Carolina, Chapel Hill (K.H.L.); Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore (Y.T., D.B.M.); Center for Health Services Research in Primary Care, Durham VAMC, NC (C.A.B., H.B.B.); VHA Health Services Research and Development Stroke Quality Enhancement Research Initiative, Indianapolis, IN (L.S.W., D.M.B.); VHA Health Services Research and Development Center of Excellence on Implementing Evidence-Based Practice, Richard L. Roudebush VHA Medical Center, Indianapolis, IN (L.S.W. D.M.B.); Regenstrief Institute, Indianapolis, IN (L.S.W., D.M.B.); Department of Veterans Affairs, Veterans Engineering Resource Center, VA-Center for Applied Systems Engineering, Indianapolis, IN (L.S.W.); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis (D.M.B.); Department of Neurology, VA Greater Los Angeles Healthcare System, CA (E.M.C.); Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles (E.M.C.); Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC (H.B.B., D.B.M.); Homer Consulting, Voorhees, NJ (J.B.H.); and Duke Clinical Research Institute, Duke University, Durham, NC (D.B.M.). [email protected].
² From the Department of Health Policy and Management, The University of North Carolina, Chapel Hill (K.H.L.); Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore (Y.T., D.B.M.); Center for Health Services Research in Primary Care, Durham VAMC, NC (C.A.B., H.B.B.); VHA Health Services Research and Development Stroke Quality Enhancement Research Initiative, Indianapolis, IN (L.S.W., D.M.B.); VHA Health Services Research and Development Center of Excellence on Implementing Evidence-Based Practice, Richard L. Roudebush VHA Medical Center, Indianapolis, IN (L.S.W. D.M.B.); Regenstrief Institute, Indianapolis, IN (L.S.W., D.M.B.); Department of Veterans Affairs, Veterans Engineering Resource Center, VA-Center for Applied Systems Engineering, Indianapolis, IN (L.S.W.); Department of Internal Medicine, Indiana University School of Medicine, Indianapolis (D.M.B.); Department of Neurology, VA Greater Los Angeles Healthcare System, CA (E.M.C.); Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles (E.M.C.); Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC (H.B.B., D.B.M.); Homer Consulting, Voorhees, NJ (J.B.H.); and Duke Clinical Research Institute, Duke University, Durham, NC (D.B.M.).

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.

Keywords: Veterans; comparative effectiveness research; computer simulation; health planning; stroke.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Adult
Calibration
Computer Simulation*
Cost of Illness
Decision Making
Health Planning* / statistics & numerical data
Humans
Quality-Adjusted Life Years*
Risk Factors
Sensitivity and Specificity
Stroke Rehabilitation
Stroke* / epidemiology
Stroke* / prevention & control
Stroke* / therapy
Systems Theory
Uncertainty
United States
United States Department of Veterans Affairs
Veterans / statistics & numerical data*
Veterans Health* / statistics & numerical data

Abstract

Publication types

MeSH terms

Grants and funding