The Potential of Claims Data to Support the Measurement of Health Care Quality

by Jennifer Hicks

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Annual health care expenditures in the United States currently exceed $1.5 trillion. However, information on the level of health care quality resulting from these expenditures suggests that millions of Americans fail to receive adequate care. The author examines whether the use of claims data for measuring health care quality is being fully realized and identifies the types of electronic data, if available, that could increase the potential for quality measurement. The strengths and limitations of quality measurement with claims data were assessed through two separate analyses. First, more than 550 quality-of-care indicators were analyzed to determine whether they could be assessed with claims data. A separate analysis compared claims data and medical records data to assess the accuracy of quality measurement with claims data. The author found that while widespread quality measurement relying extensively on medical records provides fuller and more-accurate information, the associated costs are prohibitively high for most organizations. She discusses four options for health care quality measurement: (1) the status quo; (2) expanded use of claims data, possibly augmented with certain types of information; (3) expanded use of medical records; and (4) expanded use of both claims data and medical records.

Table of Contents

  • Summary

  • All Prefatory Materials

  • Chapter One


  • Chapter Two

    Conceptualizing and Measuring Quality of Care

  • Chapter Three

    Assessing the Feasibility of Measuring Quality with Claims Data

  • Chapter Four

    The Accuracy of Quality Measurement with Claims Data

  • Chapter Five

    Moving Quality Measurement Forward

  • Appendix A

    Tabular Results: Increasing Capacity for Quality Measurement

  • Appendix B

    Indicators Used to Assess Agreement

  • Appendix C

    Claims Data Specifications

  • Appendix D

    Kappa Statistics

  • Appendix E

    Semi-Standardized Regression Coefficients

  • Supplementary Materials

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