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Development of a model for finding unlabeled cases of rheumatoid arthritis in UK primary care patient records
presentation
posted on 2023-06-09, 12:38 authored by Elizabeth FordElizabeth Ford, Grace Lupton, Philip Rooney, Seb OliverSeb Oliver, Jackie CassellWhen using electronic patient records (EPR) from UK primary care for research, it is not possible to tell the difference between “negative” and “positive, but unlabeled” cases. Using the exemplar of rheumatoid arthritis (RA), we developed a logistic regression model which could be used to identify cases of RA which are unlabeled. Combining symptom, referral and test information from codes and free text, our model discriminated between RA cases and controls with an AUROC of 0.923. This method for identifying “positive, unlabeled” cases in patient records has the potential to improve case ascertainment for a range of EPR studies.
Funding
The ergonomics of electric patient records: an interdisciplinary development of methodologies for understanding and exploiting free text to enhance the utility of primary care electronic patient records; G0011; WELLCOME TRUST; 086105/Z/08/Z
History
Publication status
- Published
File Version
- Accepted version
Presentation Type
- paper
Event name
Medical Informatics Europe 2018Event location
Gothenburg, SwedenEvent type
conferenceEvent date
24th-26th April 2018ISBN
9781614998518Department affiliated with
- Primary Care and Public Health Publications
Research groups affiliated with
- Astronomy Centre Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2018-03-26First Compliant Deposit (FCD) Date
2018-03-26Usage metrics
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