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Ann Intern Med. 2003 May 6;138(9):751-60.

Competency in interpretation of 12-lead electrocardiograms: a summary and appraisal of published evidence.

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  • 1Tripler Army Medical Center, Honolulu, Hawaii, USA.

Abstract

BACKGROUND:

There have been many proposals for objective standards designed to optimize training, testing, and maintaining competency in interpretation of electrocardiograms (ECGs). However, most of these recommendations are consensus based and are not derived from clinical trials that include patient outcomes.

PURPOSE:

To critically review the available data on training, accuracy, and outcomes of computer and physician interpretation of 12-lead resting ECGs.

DATA SOURCES:

English-language articles were retrieved by searching MEDLINE (1966 to 2002), EMBASE (1974 to 2002), and the Cochrane Controlled Trials Register (1975-2002). The references in articles selected for analysis were also reviewed for relevance.

STUDY SELECTION:

All articles on training, accuracy, and outcomes of ECG interpretations were analyzed.

DATA EXTRACTION:

Study design and results were summarized in evidence tables. Information on physician interpretation compared to a "gold standard," typically a consensus panel of expert electrocardiographers, was extracted. The clinical context of and outcomes related to the ECG interpretation were obtained whenever possible.

DATA SYNTHESIS:

Physicians of all specialties and levels of training, as well as computer software for interpreting ECGs, frequently made errors in interpreting ECGs when compared to expert electrocardiographers. There was also substantial disagreement on interpretations among cardiologists. Adverse patient outcomes occurred infrequently when ECGs were incorrectly interpreted.

CONCLUSIONS:

There is no evidence-based minimum number of ECG interpretations that is ideal for attaining or maintaining competency in ECG interpretation skills. Further research is needed to clarify the optimal way to build and maintain ECG interpretation skills based on patient outcomes.

PMID:
12729431
[PubMed - indexed for MEDLINE]
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