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Objective: The MediPlus database collects anonymized information from general practice computer systems in the United Kingdom, for research purposes. Data quality markers are collated and fed back to the participating general practitioners. The authors examined whether this feedback had a significant effect on data quality. Methods: The data quality markers used since 1992 were examined. The authors determined whether the feedback of "useful" data quality markers led to a statistically significant improvement in these markers. Environmental influences on data quality from outside the scheme were controlled for by examination of the data quality scores of new entrants. Results: Three quality markers improved significantly over the period of the study. These were the use of highly specific "lower-level" Read Codes (p = 0.004) and the linkage of repeat prescriptions (p = 0.03) and acute prescriptions (p = 0.04) to diagnosis. Clinicians who fall below the target level for linkage of repeat prescriptions to diagnosis receive more detailed feedback; the effect of this was also statistically significant (p < 0.01.) Conclusions: The feedback of four of the ten markers had a significant effect on data quality. The effect of more detailed feedback appears to have had a greater effect. The lessons learned from this approach may help improve the quality of electronic medical records in the United Kingdom and elsewhere.

Original publication

DOI

10.1197/jamia.M1023

Type

Journal article

Journal

Journal of the American Medical Informatics Association

Publication Date

30/07/2002

Volume

9

Pages

395 - 401