Health plan administrative databases can efficiently identify serious myopathy and rhabdomyolysis

Journal of Clinical Epidemiology

Volumn 58, Issue 2, 2005, Pages 171-174

  Andrade, Susan E ^a   Graham, David J ^b   Staffa, Judy A ^b   Schech, Stephanie D ^c   Shatin, Deborah ^c   La Grenade, Lois ^b   Goodman, Michael J ^d   Platt, Richard ^e,f,g   Gurwitz, Jerry H ^a   Chan, K Arnold ^e,h  

^a UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^b Center for Drug Evaluation and Research   (United States)

^c Ctr for Hlth Care Plcy and Eval   (United States)

^d HEALTHPARTNERS RESEARCH FOUNDATION   (United States)

^e BRIGHAM AND WOMEN S HOSPITAL   (United States)

^f HARVARD PILGRIM HEALTH CARE   (United States)

^g HARVARD MEDICAL SCHOOL   (United States)

^h HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Automated databases; Fibrates; Myopathy; Positive predictive value; Rhabdomyolysis; Statins

Indexed keywords

ACUTE KIDNEY FAILURE; DATA BASE; GEOGRAPHY; HEALTH CARE PLANNING; HOSPITAL MANAGEMENT; HOSPITALIZATION; HUMAN; MANAGED CARE; MYOPATHY; PRIORITY JOURNAL; RETROSPECTIVE STUDY; REVIEW; RHABDOMYOLYSIS;

EID: 19944432924     PISSN: 08954356     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2004.10.004     Document Type: Article

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