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Accuracy of coding for possible warfarin complications in hospital discharge abstracts

Affiliations

• ¹ Ottawa Health Research Institute-Clinical Epidemiology Program, Canada.

• PMID: 16081144
• DOI: 10.1016/j.thromres.2005.06.015

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T Arnason et al. Thromb Res. 2006.

• ¹ Ottawa Health Research Institute-Clinical Epidemiology Program, Canada.

• PMID: 16081144
• DOI: 10.1016/j.thromres.2005.06.015

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Background: Hospital discharge abstracts could be used to identify complications of warfarin if coding for bleeding and thromboembolic events are accurate.

Objectives: To measure the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9CM) codes for bleeding and thromboembolic diagnoses.

Setting: University affiliated, tertiary care hospital in Ottawa, Canada.

Patients: A random sample of patients discharged between September 1999 and September 2000 with an ICD-9-CM code indicating a bleeding or thromboembolic diagnosis.

Methods: Gold-standard coding was determined by a trained chart abstractor using explicit standard diagnostic criteria for bleeding, major bleeding, and acute thromboembolism. The abstractor was blinded to the original coding. We calculated the sensitivity, specificity, positive, and negative predictive values of the original ICD-9CM codes for bleeding or thromboembolism diagnoses.

Results: We reviewed 616 medical records. 361 patients (59%) had a code indicating a bleeding diagnosis, 291 patients (47%) had a code indicating a thromboembolic diagnosis and 36 patients (6%) had a code indicating both. According to the gold standard criteria, 352 patients experienced bleeding, 333 experienced major bleeding, and 188 experienced an acute thromboembolism. For bleeding, the ICD-9CM codes had the following sensitivity, specificity, positive and negative predictive values [95% CI]: 93% [90-96], 88% [83-91], 91% [88-94], and 91% [87-94], respectively. For major bleeding, the ICD-9CM codes had the following sensitivity, specificity, positive and negative predictive values: 94% [91-96], 83% [78-87], 87% [83-90], and 92% [88-95], respectively. For thromboembolism, the ICD-9CM codes had the following sensitivity, specificity, positive and negative predictive values: 97% [94-99], 74% [70-79], 62% [57-68], and 98% [96-99], respectively. By selecting a sub-group of ICD-9CM codes for thromboembolism, the positive predictive value increased to 87%.

Conclusion: In our centre, the discharge abstract could be used to identify and exclude patients hospitalized with a major bleed or thromboembolism. If coding quality for bleeding is similar in other hospitals, these ICD-9-CM diagnostic codes could be used to study population-based warfarin-associated hemorrhagic complications using administrative databases.

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