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J Clin Epidemiol. 2005 Feb;58(2):171-4.

Health plan administrative databases can efficiently identify serious myopathy and rhabdomyolysis.

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  • 1Meyers Primary Care Institute-Fallon Foundation and University of Massachusetts Medical School, 630 Plantation Street, Worcester, MA 01605, USA. sandrade@meyersprimary.org

Abstract

OBJECTIVE:

We evaluated the positive predictive values (PPVs) of specific criteria based upon International Classification of Diseases, 9th revision (ICD-9-CM) codes documented in health plan administrative databases for identification of cases of serious myopathy and rhabdomyolysis.

STUDY DESIGN AND SETTING:

We conducted a retrospective study among patients enrolled in 11 geographically dispersed managed care organizations. Cohorts of new users of specific statins and fibrates were identified by selecting patients with an initial dispensing of the drug during the period 1 January 1998 to 30 June 2001. Potential cases of serious myopathy or rhabdomyolysis were identified using specific criteria based upon ICD-9-CM codes suggesting a muscle disorder or acute renal failure.

RESULTS:

A total of 194 hospitalizations meeting the criteria for chart review selection were identified among 206,732 new users of statins and 15,485 new users of fibrates. Overall, 31 cases of serious, clinically important myopathy or rhabdomyolysis (18%) were confirmed through chart review. Of these, 26 (84%) had a claim including codes for myoglobinuria (ICD-9-CM 791.3) or other disorders of muscle, ligament, and fascia (ICD-9-CM 728.89). A PPV of 74% (26 of 35 patients meeting criteria) was found for a composite definition that included (1) a primary or secondary discharge code for myoglobinuria, (2) a primary code for "other disorders of muscle," or (3) a secondary code for "other disorders of muscle" accompanied by a claim for a CK test within 7 days of hospitalization or a discharge code for acute renal failure.

CONCLUSION:

For rare adverse events such as serious myopathy or rhabdomyolysis, large population-based databases that include diagnosis and laboratory test claims data can facilitate epidemiologic research.

PMID:
15680751
DOI:
10.1016/j.jclinepi.2004.10.004
[PubMed - indexed for MEDLINE]
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