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Review and Evaluation of the VA Enrollee Health Care Projection Model

by Katherine M. Harris, James P. Galasso, Christine Eibner

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The U.S. Department of Veterans Affairs (VA) relies on the Enrollee Health Care Projection Model (EHCPM) to project veteran enrollment, enrolled veterans' use of health care services, and the cost of providing those services. Senior VA leadership and regional leadership of the VA's Veterans Integrated Service Networks (VISNs) use projections produced by the model to understand the dynamics of demand for health care services in the VISN service delivery areas and to plan the VA's appropriation request. There is also interest in using the model as a platform for a variety of strategic planning and policy analysis activities. This evaluation of the EHCPM examines its accuracy and validity, identifies potential model enhancements, and assesses the risks and benefits posed by the VA's reliance on the model for budgeting and planning.

Table of Contents

  • Chapter One

    Introduction and Background

  • Chapter Two

    Evaluation Methodology

  • Chapter Three

    Model Overview

  • Chapter Four

    Findings on Model Structure and Validity

  • Chapter Five

    Findings on Model Accuracy

  • Chapter Six

    Findings on Tractability and Transparency

  • Chapter Seven

    Benefits and Risks of the EHCPM

  • Chapter Eight

    Conclusions

  • Appendix A

    Results of Validation Studies

  • Appendix B

    Priority-Level Definitions

  • Appendix C

    Model Uses Described in “VA Enrollee Health Care Projection Model Training Companion Manual,” June 2006

Research conducted by

The research described in this report was sponsored by the Department of Veterans Affairs. The research was conducted in the RAND National Defense Research Institute, a federally funded research and development center sponsored by the Office of the Secretary of Defense, the Joint Staff, the Unified Combatant Commands, the Department of the Navy, the Marine Corps, the defense agencies, and the defense Intelligence Community.

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