Title

A systematic review of validated methods for identifying cerebrovascular accident or transient ischemic attack using administrative data

UMMS Affiliation

Meyers Primary Care Institute; Department of Medicine, Division of Rheumatology; Department of Medicine, Division of Geriatric Medicine; Department of Medicine, Division of Cardiovascular Medicine; Department of Quantitative Health Sciences

Date

1-19-2012

Document Type

Article

Medical Subject Headings

Ischemic Attack, Transient; Stroke; Diagnostic Techniques, Cardiovascular

Disciplines

Cardiovascular Diseases | Health Services Research | Primary Care

Abstract

PURPOSE: To perform a systematic review of the validity of algorithms for identifying cerebrovascular accidents (CVAs) or transient ischemic attacks (TIAs) using administrative and claims data.

METHODS: PubMed and Iowa Drug Information Service searches of the English language literature were performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for identifying CVAs (ischemic and hemorrhagic strokes, intracranial hemorrhage, and subarachnoid hemorrhage) and/or TIAs in administrative data. Two study investigators independently reviewed the abstracts and articles to determine relevant studies according to pre-specified criteria.

RESULTS: A total of 35 articles met the criteria for evaluation. Of these, 26 articles provided data to evaluate the validity of stroke, seven reported the validity of TIA, five reported the validity of intracranial bleeds (intracerebral hemorrhage and subarachnoid hemorrhage), and 10 studies reported the validity of algorithms to identify the composite endpoints of stroke/TIA or cerebrovascular disease. Positive predictive values (PPVs) varied depending on the specific outcomes and algorithms evaluated. Specific algorithms to evaluate the presence of stroke and intracranial bleeds were found to have high PPVs (80% or greater). Algorithms to evaluate TIAs in adult populations were generally found to have PPVs of 70% or greater.

CONCLUSIONS: The algorithms and definitions to identify CVAs and TIAs using administrative and claims data differ greatly in the published literature. The choice of the algorithm employed should be determined by the stroke subtype of interest. Copyright (c) 2012 John Wiley and Sons, Ltd.

Rights and Permissions

Citation: Pharmacoepidemiol Drug Saf. 2012 Jan;21 Suppl 1:100-28. doi: 10.1002/pds.2312. Link to article on publisher's site

Related Resources

Link to Article in PubMed

Keywords

UMCCTS funding