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ABSTRACT: Objective
To systematically review measures of data quality in electronic patient records (EPRs) in primary care.Design
Systematic review of English language publications, 1980-2001.Data sources
Bibliographic searches of medical databases, specialist medical informatics databases, conference proceedings, and institutional contacts.Study selection
Studies selected according to a predefined framework for categorising review papers.Data extraction
Reference standards and measurements used to judge quality.Results
Bibliographic searches identified 4589 publications. After primary exclusions 174 articles were classified, 52 of which met the inclusion criteria for review. Selected studies were primarily descriptive surveys. Variability in methods prevented meta-analysis of results. Forty eight publications were concerned with diagnostic data, 37 studies measured data quality, and 15 scoped EPR quality. Reliability of data was assessed with rate comparison. Measures of sensitivity were highly dependent on the element of EPR data being investigated, while the positive predictive value was consistently high, indicating good validity. Prescribing data were generally of better quality than diagnostic or lifestyle data.Conclusion
The lack of standardised methods for assessment of quality of data in electronic patient records makes it difficult to compare results between studies. Studies should present data quality measures with clear numerators, denominators, and confidence intervals. Ambiguous terms such as "accuracy" should be avoided unless precisely defined.
SUBMITTER: Thiru K
PROVIDER: S-EPMC155692 | biostudies-literature | 2003 May
REPOSITORIES: biostudies-literature
Thiru Krish K Hassey Alan A Sullivan Frank F
BMJ (Clinical research ed.) 20030501 7398
<h4>Objective</h4>To systematically review measures of data quality in electronic patient records (EPRs) in primary care.<h4>Design</h4>Systematic review of English language publications, 1980-2001.<h4>Data sources</h4>Bibliographic searches of medical databases, specialist medical informatics databases, conference proceedings, and institutional contacts.<h4>Study selection</h4>Studies selected according to a predefined framework for categorising review papers.<h4>Data extraction</h4>Reference s ...[more]