| Title: |
An algorithm to identify rheumatoid arthritis in primary care: a Clinical Practice Research Datalink study. |
| Authors: |
Muller, S; Hider, SL; Raza, K; Stack, RJ; Hayward, RA; Mallen, CD |
| Publisher Information: |
BMJ Publishing Group |
| Publication Year: |
2015 |
| Collection: |
Keele University: Keele Research Repository |
| Subject Terms: |
RA Public aspects of medicine |
| Description: |
OBJECTIVE: Rheumatoid arthritis (RA) is a multisystem, inflammatory disorder associated with increased levels of morbidity and mortality. While much research into the condition is conducted in the secondary care setting, routinely collected primary care databases provide an important source of research data. This study aimed to update an algorithm to define RA that was previously developed and validated in the General Practice Research Database (GPRD). METHODS: The original algorithm consisted of two criteria. Individuals meeting at least one were considered to have RA. Criterion 1: ≥1 RA Read code and a disease modifying antirheumatic drug (DMARD) without an alternative indication. Criterion 2: ≥2 RA Read codes, with at least one 'strong' code and no alternative diagnoses. Lists of codes for consultations and prescriptions were obtained from the authors of the original algorithm where these were available, or compiled based on the original description and clinical knowledge. 4161 people with a first Read code for RA between 1 January 2010 and 31 December 2012 were selected from the Clinical Practice Research Datalink (CPRD, successor to the GPRD), and the criteria applied. RESULTS: Code lists were updated for the introduction of new Read codes and biological DMARDs. 3577/4161 (86%) of people met the updated algorithm for RA, compared to 61% in the original development study. 62.8% of people fulfilled both Criterion 1 and Criterion 2. CONCLUSIONS: Those wishing to define RA in the CPRD, should consider using this updated algorithm, rather than a single RA code, if they wish to identify only those who are most likely to have RA. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text |
| Language: |
English |
| Relation: |
https://eprints.keele.ac.uk/id/eprint/1409/1/An%20algorithm%20to%20identify%20rheumatoid%20arthritis%20in%20primary%20care%3A%20a%20Clinical%20Practice%20Research%20Datalink%20study.pdf; Muller, S, Hider, SL, Raza, K, Stack, RJ, Hayward, RA and Mallen, CD (2015) An algorithm to identify rheumatoid arthritis in primary care: a Clinical Practice Research Datalink study. BMJ Open, 5 (12). e009309 - ?. |
| DOI: |
10.1136/bmjopen-2015-009309 |
| Availability: |
https://eprints.keele.ac.uk/id/eprint/1409/; https://eprints.keele.ac.uk/id/eprint/1409/1/An%20algorithm%20to%20identify%20rheumatoid%20arthritis%20in%20primary%20care%3A%20a%20Clinical%20Practice%20Research%20Datalink%20study.pdf; http://bmjopen.bmj.com/content/5/12/e009309; https://doi.org/10.1136/bmjopen-2015-009309 |
| Rights: |
cc_by_4 |
| Accession Number: |
edsbas.23F331B7 |
| Database: |
BASE |