Validation and validity of diagnoses in the General Practice Research Database: a systematic review
Open accessAbstract
AIMS To investigate the range of methods used to validate diagnoses in the General Practice Research Database (GPRD), to summarize findings and to assess the quality of these validations. METHODS A systematic literature review was performed by searching PubMed and Embase for publications using GPRD data published between 1987 and April 2008. Additional publications were identified from conference proceedings, back issues of relevant journals, bibliographies of retrieved publications and relevant websites. Publications that reported attempts to validate disease diagnoses recorded in the GPRD were included. RESULTS We identified 212 publications, often validating more than one diagnosis. In total, 357 validations investigating 183 different diagnoses met our inclusion criteria. Of these, 303 (85%) utilized data from outside the GPRD to validate diagnoses. The remainder utilized only data recorded in the database. The median proportion of cases with a confirmed diagnosis was 89% (range 24–100%). Details of validation methods and results were often incomplete. CONCLUSIONS A number of methods have been used to assess validity. Overall, estimates of validity were high. However, the quality of reporting of the validations was often inadequate to permit a clear interpretation. Not all methods provided a quantitative estimate of validity and most methods considered only the positive predictive value of a set of diagnostic codes in a highly selected group of cases. We make recommendations for methodology and reporting to strengthen further the use of the GPRD in research.
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Two recent systematic reviews document poor reporting of studies undertaken to validate data from routine data sources.
“Two recent systematic reviews also document poor reporting of studies undertaken to validate data from routine data sources [5,6], which can obscure sources of bias, hamper efforts to undertake meta-analyses, and lead to erroneous conclusions.”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [6]
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- Authors
- Herrett, E., Thomas, S. L., Schoonen, W. M., Smeeth, L., & Hall, A. J.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- Amgen (United Kingdom) (GB)
- Corresponding author
- Herrett, Emily
- Venue
- British Journal of Clinical Pharmacology
- Publisher
- Wiley
- Published
- 2009-12-23
- Volume
- 69
- Issue
- 1
- Pages
- 4-14
- ISSN
- 0306-5251 (ISSN-L)
- 1365-2125
- PMC
- PMC2805870
- OpenAlex
- W2163589808
- Cited by
- 1,109
- References
- 28
- Citations by year
- 2026: 28 · 2025: 37 · 2024: 55 · 2023: 45 · 2022: 59 · 2021: 68 · 2020: 74 · 2019: 96 · 2018: 89 · 2017: 88 · 2016: 104 · 2015: 83 · 2014: 92 · 2013: 83 · 2012: 52
- FWCI
- 5.49
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal of Clinical Pharmacology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Funders
- Wellcome Trust (082178)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Keywords
- Clinical Practice Research Datalink, diagnosis validation, validity, electronic health records, primary care data, positive predictive value, diagnosis codes, reporting quality
- MeSH terms
- Algorithms, Clinical Competence, Diagnostic Errors, Family Practice, Humans, Surveys and Questionnaires, Research, Reproducibility of Results, Databases, Factual
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