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Abstract Number: 52

The Validity of the Diagnosis Inflammatory Arthritis in Primary Care

Markus M.J. Nielen1, Jennie Ursum1, François G. Schellevis2 and Joke C. Korevaar1, 1NIVEL (Netherlands Institute for Health Services Research), Utrecht, Netherlands, 2Department of General Practice and Elderly Care Medicine/EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, Netherlands

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Diagnosis and inflammatory arthritis

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Session Information

Title: Epidemiology and Health Services Research: Epidemiology and Outcomes of Rheumatic Disease I

Session Type: Abstract Submissions (ACR)

Background/Purpose: Large population-based databases, such as electronic medical records (EMRs) from patients in primary care, are useful data sources to investigate morbidity and health care utilization in patients with chronic diseases. These databases make it possible to study large groups of patients with the whole range of disease severity in a representative population, including control groups. In many countries, general practitioners (GPs) have a gatekeeper role for access to specialized care and therefore their EMRs include a complete record of all morbidity of their patients using a uniform methodology. Despite these advantages, EMRs include diagnoses which are usually not validated. In this study we investigated the validity of the diagnosis inflammatory arthritis (IA) in primary care based records.

Methods: Five general practices participating in the Netherlands Information Network of General Practice (LINH) were visited to collect diagnostic information. EMRs of 219 patients with a diagnostic code of IA (ICPC L88) in the LINH database were systematically reviewed on additional characteristics which are not routinely extracted for the LINH database: free text regarding contacts, prescriptions, medical history, referrals and correspondence with medical specialists. Based on coded and free text fields, all patient were categorized in one of the following groups: 1) IA, 2) osteoarthritis (OA), 3) gout, or 4) other diagnosis. These results were used to develop selection criteria to distinguish IA from non-IA in patients with all routinely available information in the LINH database.

Results: From the 219 patients diagnosed as IA in the database, the diagnosis IA was confirmed in 155 patients (70.8%), 18 patients were classified with OA (8.2%), 12 patients with gout (5.5%) and 34 patients with another diagnosis (15.5%). With these findings we developed selection criteria to include IA patients solely based on coded fields, starting with a first selection based on ICPC-code L88, followed by three sequential steps: 1) a repeat prescription for a disease-modifying antirheumatic drug (DMARD) or biological agent, 2) at least four contacts or one episode with a diagnostic code for IA, combined with at least two prescriptions (excluding DMARDs/biological agents) with the IA diagnostic code, and 3) age at diagnosis ≤ 61 years. With these criteria it was not possible to distinguish between IA and OA patients with probable IA. Applying the selection criteria, resulted in a group of 139 IA patients including 77,7% IA patients and 7,9% OA patients with probable IA.

Conclusion: Based on additional diagnostic information, the diagnosis IA from EMRs of patients in primary care is sufficiently valid when using the proposed selection criteria. Since the group of IA patients still contain some patients without an IA related diagnosis, effects from studies with IA patients in primary care could be underestimated.


Disclosure:

M. M. J. Nielen,
None;

J. Ursum,
None;

F. G. Schellevis,
None;

J. C. Korevaar,
None.

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