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.
Article first published online: 2 NOV 2007
Copyright © 2007 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Volume 17, Issue 1, pages 20–26, January 2008
How to Cite
Roumie, C. L., Mitchel, E., Gideon, P. S., Varas-Lorenzo, C., Castellsague, J. and Griffin, M. R. (2008), Validation of ICD-9 codes with a high positive predictive value for incident strokes resulting in hospitalization using Medicaid health data. Pharmacoepidem. Drug Safe., 17: 20–26. doi: 10.1002/pds.1518
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.
- Issue published online: 18 DEC 2007
- Article first published online: 2 NOV 2007
- Manuscript Accepted: 19 SEP 2007
- Manuscript Revised: 10 SEP 2007
- Manuscript Received: 7 FEB 2007
- stroke classification;
- anti-inflammatory agents;
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.
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 ; and subarachnoid hemorrhage ). 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.
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%).
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.