Key result
Medical record abstraction yields highest database error rate at ~7% vs. electronic methods.
Why the study?
A new surveillance approach for myocardial infarction using primarily enzyme data was developed to improve reproducibility, cost efficiency, and robustness across hospital systems and diagnostic changes.
Meta-Analysis (n=84)
Medical record abstraction may compromise data integrity in surveillance studies; leaves open whether automated alternatives improve accuracy in pilot algorithms.
McKinlay S M (New England Research Institute, Inc, 9 Galen Street, Watertown, MA 02172, USA), Carleton R A, McKenney J L and Assaf A R. A new approach to surveillance for acute myocardial infarction: reproducibility and cost efficiency. International Journal of Epidemiology 1989, 18: 67–75. A new approach to surveillance of myocardial infarction, the major cardiovascular endpoint is described using an algorithm which depends primarily on enzyme data, using evidence of chest pain and positive electrocardiogram findings as supplemental information only. This approach is evaluated with respect to reproducibility by minimally trained abstractors, cost, and robustness with respect to different hospital systems as well as changes in diagnostic techniques and/or labelling over time. Two pilot studies demonstrate that, in comparison to more traditional approaches, the new surveillance system provides at least a 50% reduction in cost, is highly reproducible over different hospital systems, and potentially, is resilient to changes in diagnostic procedures or coding. The more general applicability of such an innovative surveillance approach to other disease endpoints, in which one reliable procedure contains most of the diagnostic information, is discussed with particular reference to cancer.
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McKinlay et al. (1989) conducted a meta-analysis in Data accuracy in clinical research and registries (n=84). Medical record abstraction vs. Optical scanning, single-data entry, and double-data entry was evaluated on Pooled database error rate (95% CI 5.51-7.72). Medical record abstraction was associated with the highest pooled database error rate at 6.57%, compared to optical scanning (0.74%), single-data entry (0.29%), and double-data entry (0.14%).
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