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Development of a model for finding unlabeled cases of rheumatoid arthritis in UK primary care patient records

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posted on 2023-06-09, 12:38 authored by Elizabeth FordElizabeth Ford, Grace Lupton, Philip Rooney, Seb OliverSeb Oliver, Jackie Cassell
When 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 2018

Event location

Gothenburg, Sweden

Event type

conference

Event date

24th-26th April 2018

ISBN

9781614998518

Department 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

2018-03-26

First Compliant Deposit (FCD) Date

2018-03-26

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