Computerized definitions showed high positive predictive values for identifying hospitalizations for congestive heart failure and selected infections in Medicaid enrollees with rheumatoid arthritis

Authors

  • Carlos G. Grijalva MD MPH,

    Corresponding author
    1. Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
    • Department of Preventive Medicine, Vanderbilt University School of Medicine, 1500 21st Avenue, 2600 VAV, Nashville, TN 37212, USA.
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  • Cecilia P. Chung MD MPH,

    1. Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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  • C. Michael Stein MD,

    1. Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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  • Patricia S. Gideon RN,

    1. Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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  • Shannon M. Dyer B.S.,

    1. Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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  • Edward F. Mitchel Jr MS,

    1. Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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  • Marie R. Griffin MD MPH

    1. Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
    2. Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
    3. The Mid-South Geriatric Research Education and Clinical Center and Clinical Research Center of Excellence, VA TN Valley Health Care System, Nashville, TN, USA
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  • None of the authors have conflicts of interest to disclose.

Abstract

Purpose

Computerized definitions are used to identify serious infections and congestive heart failure leading to hospitalizations in studies of medication safety. However, information on their accuracy is limited. We evaluated the ability of computerized definitions to identify these conditions as the reason for admission among patients diagnosed with rheumatoid arthritis (RA).

Methods

Medical charts were randomly selected from a systematic sample of hospitalizations for selected conditions in a cohort of Medicaid patients with RA. We calculated positive predictive values (PPVs) for computerized definitions for community-acquired pneumonia, invasive pneumococcal disease, sepsis, opportunistic mycoses, and congestive heart failure using charts reviews as gold standard and computed inter-reviewer agreement statistics.

Results

From 2667 hospitalizations, 336 (13%) records were selected for review. A total of 277 charts (82%) were available. Based on any discharge diagnosis, PPVs for hospitalizations due to community-acquired pneumonia, invasive pneumococcal disease, sepsis, and opportunistic mycoses were 84, 100, 80, and 62%, respectively. Restricting definitions to principal diagnoses yielded higher PPVs, 95% for pneumonia and 100% for other diagnoses. The PPV of a principal diagnosis for congestive heart failure was 100%. Inter-reviewer agreement was at least 77% for all outcomes.

Conclusion

These findings suggest that computerized definitions can identify congestive heart failure and selected infections leading to hospitalization in Medicaid patients with RA. Copyright © 2008 John Wiley & Sons, Ltd.

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