Comparative Logic Modeling for Policy Analysis: The Case of HIV Testing Policy Change at the Department of Veterans Affairs

Authors

  • Erika M. Langer,

    1. Boston University School of Medicine, Boston, MA
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  • Allen L. Gifford,

    1. Boston University School of Medicine, Boston, MA
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  • Kee Chan

    1. Boston University School of Medicine, Boston, MA
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    • Address correspondence to Kee Chan, Ph.D., Assistant Professor, Department of Health Sciences, Boston University College of Health and Rehabilitation Sciences: Sargent College, 635 Commonwealth Avenue, Boston, MA 02215; e-mail: keechan@bu.edu. Erika M. Langer, M.S., and Allen L. Gifford, M.D., are with the Department of Health Policy and Management, Boston University School of Public Health, Boston, MA. Erika M. Langer, M.S., is also with Department of Health Sciences, Boston University College of Health and Rehabilitation Sciences: Sargent College, Boston, MA. Allen L. Gifford, M.D., is also with the Section of General Internal Medicine, Boston University School of Medicine, Boston, MA. Allen L. Gifford, M.D., and Kee Chan, Ph.D., are with the Center for Health Quality, Outcomes and Economic Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA. Kee Chan, Ph.D., is also with the Department of Epidemiology, Boston University School of Medicine, Boston, MA.


Abstract

Objective. Logic models have been used to evaluate policy programs, plan projects, and allocate resources. Logic Modeling for policy analysis has been used rarely in health services research but can be helpful in evaluating the content and rationale of health policies. Comparative Logic Modeling is used here on human immunodeficiency virus (HIV) policy statements from the Department of Veterans Affairs (VA) and Centers for Disease Control and Prevention (CDC). We created visual representations of proposed HIV screening policy components in order to evaluate their structural logic and research-based justifications.

Data Sources and Study Design. We performed content analysis of VA and CDC HIV testing policy documents in a retrospective case study.

Data Collection. Using comparative Logic Modeling, we examined the content and primary sources of policy statements by the VA and CDC. We then quantified evidence-based causal inferences within each statement.

Principal Findings. VA HIV testing policy structure largely replicated that of the CDC guidelines. Despite similar design choices, chosen research citations did not overlap. The agencies used evidence to emphasize different components of the policies.

Conclusion. Comparative Logic Modeling can be used by health services researchers and policy analysts more generally to evaluate structural differences in health policies and to analyze research-based rationales used by policy makers.

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