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. Issue 1 (25th January 2017)
- Record Type:
- Journal Article
- Title:
- 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. Issue 1 (25th January 2017)
- Main Title:
- 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
- Authors:
- Tate, A Rosemary
Dungey, Sheena
Glew, Simon
Beloff, Natalia
Williams, Rachael
Williams, Tim - Abstract:
- Abstract : Objective: To assess the effect of coding quality on estimates of the incidence of diabetes in the UK between 1995 and 2014. Design: A cross-sectional analysis examining diabetes coding from 1995 to 2014 and how the choice of codes (diagnosis codes vs codes which suggest diagnosis) and quality of coding affect estimated incidence. Setting: Routine primary care data from 684 practices contributing to the UK Clinical Practice Research Datalink (data contributed from Vision (INPS) practices). Main outcome measure: Incidence rates of diabetes and how they are affected by (1) GP coding and (2) excluding 'poor' quality practices with at least 10% incident patients inaccurately coded between 2004 and 2014. Results: Incidence rates and accuracy of coding varied widely between practices and the trends differed according to selected category of code. If diagnosis codes were used, the incidence of type 2 increased sharply until 2004 (when the UK Quality Outcomes Framework was introduced), and then flattened off, until 2009, after which they decreased. If non-diagnosis codes were included, the numbers continued to increase until 2012. Although coding quality improved over time, 15% of the 666 practices that contributed data between 2004 and 2014 were labelled 'poor' quality. When these practices were dropped from the analyses, the downward trend in the incidence of type 2 after 2009 became less marked and incidence rates were higher. Conclusions: In contrast to some previousAbstract : Objective: To assess the effect of coding quality on estimates of the incidence of diabetes in the UK between 1995 and 2014. Design: A cross-sectional analysis examining diabetes coding from 1995 to 2014 and how the choice of codes (diagnosis codes vs codes which suggest diagnosis) and quality of coding affect estimated incidence. Setting: Routine primary care data from 684 practices contributing to the UK Clinical Practice Research Datalink (data contributed from Vision (INPS) practices). Main outcome measure: Incidence rates of diabetes and how they are affected by (1) GP coding and (2) excluding 'poor' quality practices with at least 10% incident patients inaccurately coded between 2004 and 2014. Results: Incidence rates and accuracy of coding varied widely between practices and the trends differed according to selected category of code. If diagnosis codes were used, the incidence of type 2 increased sharply until 2004 (when the UK Quality Outcomes Framework was introduced), and then flattened off, until 2009, after which they decreased. If non-diagnosis codes were included, the numbers continued to increase until 2012. Although coding quality improved over time, 15% of the 666 practices that contributed data between 2004 and 2014 were labelled 'poor' quality. When these practices were dropped from the analyses, the downward trend in the incidence of type 2 after 2009 became less marked and incidence rates were higher. Conclusions: In contrast to some previous reports, diabetes incidence (based on diagnostic codes) appears not to have increased since 2004 in the UK. Choice of codes can make a significant difference to incidence estimates, as can quality of recording. Codes and data quality should be checked when assessing incidence rates using GP data. … (more)
- Is Part Of:
- BMJ open. Volume 7:Issue 1(2017)
- Journal:
- BMJ open
- Issue:
- Volume 7:Issue 1(2017)
- Issue Display:
- Volume 7, Issue 1 (2017)
- Year:
- 2017
- Volume:
- 7
- Issue:
- 1
- Issue Sort Value:
- 2017-0007-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-01-25
- Subjects:
- PRIMARY CARE -- Data quality -- Misclassification
Medicine -- Research -- Periodicals
610.72 - Journal URLs:
- http://www.bmj.com/archive ↗
http://bmjopen.bmj.com/ ↗ - DOI:
- 10.1136/bmjopen-2016-012905 ↗
- Languages:
- English
- ISSNs:
- 2044-6055
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18821.xml