An algorithm to identify rheumatoid arthritis in primary care: a Clinical Practice Research Datalink study

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.

[1]  C. Werning [Rheumatoid arthritis]. , 1983, Medizinische Monatsschrift fur Pharmazeuten.

[2]  A. Silman,et al.  UvA-DARE (Digital Academic Repository) 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative Aletaha, , 2010 .

[3]  L. Smeeth,et al.  Validation and validity of diagnoses in the General Practice Research Database: a systematic review , 2010, British journal of clinical pharmacology.

[4]  Santiago G. Moreno,et al.  BMC Medical Research Methodology , 2009 .

[5]  Greta Rait,et al.  Optimising Use of Electronic Health Records to Describe the Presentation of Rheumatoid Arthritis in Primary Care: A Strategy for Developing Code Lists , 2013, PloS one.

[6]  S. Hider,et al.  Cardiovascular screening in rheumatoid arthritis: a cross-sectional primary care database study , 2013, BMC Family Practice.

[7]  P. Rose,et al.  Validity of diagnostic coding within the General Practice Research Database: a systematic review. , 2010, The British journal of general practice : the journal of the Royal College of General Practitioners.

[8]  A. Silman,et al.  Rheumatoid arthritis classifi cation criteria : an American College of Rheumatology / European League Against Rheumatism collaborative initiative , 2010 .

[9]  L. Smeeth,et al.  How accurate are diagnoses for rheumatoid arthritis and juvenile idiopathic arthritis in the general practice research database? , 2008, Arthritis and rheumatism.