Fawcett, N;
Young, B;
Peto, L;
Quan, TP;
Gillot, R;
Wu, J;
Middlemass, C;
... Sandoe, JAT; + view all
(2019)
‘Caveat emptor’: the cautionary tale of endocarditis and the potential pitfalls of clinical coding 1 data: an electronic health records study.
BMC Medicine
, 17
(169)
10.1186/s12916-019-1390-x.
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Abstract
Background: 30 Diagnostic codes from electronic health records are widely used to assess patterns of disease. Infective endocarditis is an uncommon but serious infection, with objective diagnostic criteria. Electronic health records have been used to explore the impact of changing guidance on antibiotic prophylaxis for dental procedures on incidence, but limited data on the accuracy of the diagnostic codes exists. Endocarditis was used as a clinically relevant case study to investigate the relationship between clinical cases and diagnostic codes, understand discrepancies, to improve design of future studies. // Methods: Electronic health record data from two UK tertiary care centres were linked with data from a prospectively collected clinical endocarditis service database (Leeds Teaching Hospital) or retrospective clinical audit and microbiology laboratory blood culture results (Oxford University Hospitals Trust). The relationship between diagnostic codes for endocarditis and confirmed clinical cases according to objective Duke criteria was assessed, and impact on estimations of disease incidence and trends. // Results: In Leeds 2006-2016, 738/1681(44%) admissions containing any endocarditis code represented a definite/possible case, while 263/1001(24%) definite/possible endocarditis cases had no endocarditis code assigned. In Oxford 2010-2016, 307/552(56%) reviewed endocarditis-coded admissions represented a clinical case. Diagnostic codes used by most endocarditis studies had good positive predictive value (PPV) but low sensitivity (e.g. I33-primary 82% and 43% respectively); one (I38-secondary) had PPV under 6%. Estimating endocarditis incidence using raw admissions data overestimated incidence trends twofold. Removing records with non-specific codes, very short stays and readmissions improved predictive ability. Estimating incidence of streptococcal endocarditis 4 using secondary codes also overestimated increases in incidence over time. Reasons for discrepancies included changes in coding behaviour over time, and coding guidance allowing assignment of a code mentioning ‘endocarditis’ where endocarditis was never mentioned in the clinical notes. // Conclusions: Commonly-used diagnostic codes in studies of endocarditis had good predictive ability. Other apparently-plausible codes were poorly predictive. Use of diagnostic codes without examining sensitivity and predictive ability can give inaccurate estimations of incidence and trends. Similar considerations may apply to other diseases. Health records studies require validation of diagnostic codes and careful data curation to minimise risk of serious errors.
| Type: | Article |
|---|---|
| Title: | ‘Caveat emptor’: the cautionary tale of endocarditis and the potential pitfalls of clinical coding 1 data: an electronic health records study |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s12916-019-1390-x |
| Publisher version: | https://doi.org/10.1186/s12916-019-1390-x |
| Language: | English |
| Additional information: | © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| Keywords: | Electronic health records, coding, big data, endocarditis, ICD-10 |
| 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 > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10078894 |
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