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Comparative Study
. 2012 Mar;163(3):392-8, 398.e1.
doi: 10.1016/j.ahj.2011.12.012.

Data quality in the American Heart Association Get With The Guidelines-Stroke (GWTG-Stroke): results from a national data validation audit

Affiliations
Comparative Study

Data quality in the American Heart Association Get With The Guidelines-Stroke (GWTG-Stroke): results from a national data validation audit

Ying Xian et al. Am Heart J. 2012 Mar.

Abstract

Background: Get With The Guidelines (GWTG)-Stroke is a national stroke registry and quality improvement program. We examined the accuracy and reliability of data entered in GWTG-Stroke.

Methods: Data entered by sites in the GWTG-Stroke database were compared with that abstracted from de-identified medical records by trained auditors. Accuracy for each individual data element and a composite accuracy measure were calculated. Reliability was assessed using kappa (κ) statistics for categorical variables and intraclass correlation (ICC) for continuous variables.

Results: A random selection of 438 medical records from 147 GWTG-Stroke hospitals was obtained. Overall accuracy was above 90% for all variables abstracted except for weight (84.9%), serum creatinine (88.1%), deep venous thrombosis prophylaxis (79.0%), and date/time last known well (85.3%). Intermediate to good (κ or ICC 0.40-0.75) or excellent agreement (κ or ICC ≥0.75) was observed for nearly all audited variables, including time-related performance measures such as arrival within 2 hours of symptom onset (κ = 0.90) and door-to-needle time ≤60 minutes (κ = 0.72). The overall composite accuracy rate was 96.1%. The composite measure varied slightly by region and hospital academic status, but there were no significant differences in composite accuracy by bed size, ischemic stroke volume, primary stroke center certification, or Coverdell Registry participation.

Conclusions: This audit establishes the reliability of GWTG-Stroke registry data. Individual data elements with suboptimal accuracy should be targeted for further data quality improvement.

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