Quality of recording of diabetes in the UK: how does the GP’s method of coding clinical data affect incidence estimates? Cross-sectional study using the CPRD database
- Submitting institution
-
University of Sussex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 109401_67388
- Type
- D - Journal article
- DOI
-
10.1136/bmjopen-2016-012905
- Title of journal
- British Medical Journal Open
- Article number
- e012905
- First page
- -
- Volume
- 7
- Issue
- 1
- ISSN
- 2044-6055
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
http://dx.doi.org/10.1136/bmjopen-2016-012905
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This was the first study in the UK to investigate the effects of GP coding practices on the incidence of diabetes since 1995. In contrast to several previous UK reports, we demonstrate that diabetes incidence (using diagnostic codes) has not increased since 2004. This study led to an overhaul of record verification practices in UK CPRD-Gold, the world’s largest primary care database. Our recommendations also contributed to EU eHealth policies via design and evaluation of the Learning Health System in Europe (FP7 TRANSFoRm project [1]). Field-weighted citation impact 2.05 (Scopus).
[1] http://www.i-hd.eu/index.cfm/resources/ec-projects-results/transform/"
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
