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What evidence is there for a delay in diagnostic coding of RA in UK general practice records? An observational study of free text

Ford, E; Carroll, J; Smith, H; Davies, K; Koeling, R; Petersen, I; Rait, G; (2016) What evidence is there for a delay in diagnostic coding of RA in UK general practice records? An observational study of free text. BMJ Open , 6 (6) , Article e010393. 10.1136/bmjopen-2015-010393. Green open access

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Abstract

OBJECTIVES: Much research with electronic health records (EHRs) uses coded or structured data only; important information captured in the free text remains unused. One dimension of EHR data quality assessment is ‘currency’ or timeliness, that is, data are representative of the patient state at the time of measurement. We explored the use of free text in UK general practice patient records to evaluate delays in recording of rheumatoid arthritis (RA) diagnosis. We also aimed to locate and quantify disease and diagnostic information recorded only in text. SETTING: UK general practice patient records from the Clinical Practice Research Datalink. PARTICIPANTS: 294 individuals with incident diagnosis of RA between 2005 and 2008; 204 women and 85 men, median age 63 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Assessment of (1) quantity and timing of text entries for disease-modifying antirheumatic drugs (DMARDs) as a proxy for the RA disease code, and (2) quantity, location and timing of free text information relating to RA onset and diagnosis. RESULTS: Inflammatory markers, pain and DMARDs were the most common categories of disease information in text prior to RA diagnostic code; 10–37% of patients had such information only in text. Read codes associated with RA-related text included correspondence, general consultation and arthritis codes. 64 patients (22%) had DMARD text entries >14 days prior to RA code; these patients had more and earlier referrals to rheumatology, tests, swelling, pain and DMARD prescriptions, suggestive of an earlier implicit diagnosis than was recorded by the diagnostic code. CONCLUSIONS: RA-related symptoms, tests, referrals and prescriptions were recorded in free text with 22% of patients showing strong evidence of delay in coding of diagnosis. Researchers using EHRs may need to mitigate for delayed codes by incorporating text into their case-ascertainment strategies. Natural language processing techniques have the capability to do this at scale.

Type: Article
Title: What evidence is there for a delay in diagnostic coding of RA in UK general practice records? An observational study of free text
Open access status: An open access version is available from UCL Discovery
DOI: 10.1136/bmjopen-2015-010393
Publisher version: http://dx.doi.org/10.1136/bmjopen-2015-010393
Language: English
Additional information: Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
Keywords: Science & Technology, Life Sciences & Biomedicine, Medicine, General & Internal, General & Internal Medicine, Rheumatoid Arthritis, Electronic Health Records, Data Quality, General Practice, Free Text, Practice Research Database, Electronic Health Records, Rheumatoid-Arthritis, Primary-Care, United-Kingdom, Disease, Risk, Classification, Management, Impact
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Primary Care and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/1502676
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