Validation of ICD-9 codes with a high positive predictive value for incident strokes resulting in hospitalization using Medicaid health data

Authors

  • Christianne L. Roumie MD, MPH,

    Corresponding author
    1. Veterans Administration, Tennessee Valley Healthcare System, Tennessee Valley Geriatric Research Education Clinical Center (GRECC), Nashville, TN, USA
    2. HSR&D Targeted Research Enhancement Program (TREP) Center for Patient Healthcare Behavior, Nashville, TN, USA
    3. Tennessee Valley VA Clinical Research Training Center of Excellence (CRCoE), Nashville, TN, USA
    4. Departments of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
    • Nashville VA Medical Center, GRECC, 1310 24th Ave South, Nashville, TN 37212, USA.
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  • Edward Mitchel MS,

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

    1. Department of Preventive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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  • Cristina Varas-Lorenzo MD, MSc, PhD,

    1. Pfizer Global Epidemiology, Safety & Risk Management, Barcelona, Spain
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  • Jordi Castellsague MD, MPH,

    1. Pfizer Global Epidemiology, Safety & Risk Management, Barcelona, Spain
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  • Marie R. Griffin MD, MPH

    1. Veterans Administration, Tennessee Valley Healthcare System, Tennessee Valley Geriatric Research Education Clinical Center (GRECC), Nashville, TN, USA
    2. HSR&D Targeted Research Enhancement Program (TREP) Center for Patient Healthcare Behavior, Nashville, TN, USA
    3. Tennessee Valley VA Clinical Research Training Center of Excellence (CRCoE), Nashville, TN, USA
    4. Departments of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
    5. Department of Preventive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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  • Disclaimer: The funding agency, Pfizer, had no role in the conduct of the study, collection of data, data management, and analysis. Pfizer employees did review and comment on the study design, interpretation of data and the final manuscript.

  • Christianne L. Roumie had full access to all of the data in the study and takes responsibility for the integrity and the analysis of data.

Abstract

Purpose

To validate ICD 9 codes with a high positive predictive value (PPV) for incident strokes. The study population consisted of Tennessee Medicaid enrollees aged from 50 to 84 years.

Methods

We identified all patients who were hospitalized with a discharge diagnosis of stroke between 1999 and 2003 using highly specific codes (ischemic stroke ICD 9-CM codes 433.x1, 434 [excluding 434.x0], or 436; intracerebral hemorrhage [431]; and subarachnoid hemorrhage [430]). We reviewed medical records of a systematic sample of 250 cohort members. We randomly selected 10–30 eligible records for review from hospitals with at least 10 stroke hospitalizations.

Results

We reviewed 231 charts (93% of total sampled), and 205 (89%) met study criteria for new outpatient stroke. Of the 205 confirmed new outpatient strokes, 196 had stroke listed as the primary discharge diagnosis (PPV = 96%). However, 46 (23%) of the 196 patients identified by the primary diagnosis also had a remote stroke history (recurrent stroke not incident). Thus the PPV of the primary discharge diagnosis for identifying incident stroke decreased to 74%. When we applied an algorithm that restricted our population to those with stroke as the primary diagnosis and excluded patients with any prior outpatient diagnosis of stroke, we identified incident stroke events with more precision (PPV = 80%).

Conclusion

The PPV of incident strokes was 80% using our strategy of primary discharge diagnosis and excluding prior outpatient diagnoses of stroke. Although an unknown percentage of incident strokes are missed, this group of proven incident stroke patients can be used for etiologic studies of medication exposures. Copyright © 2007 John Wiley & Sons, Ltd.

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