Dr. Bombardier has received honoraria (less than $10,000 each) from and/or has served as a member of the advisory boards of Abbott, AstraZeneca, BioGen, BMS, Pfizer, Pfizer/Wyeth, Merck (Schering), Janssen, and Takeda, and has received honoraria (more than $10,000) from Abbott International.
Accuracy of Canadian Health Administrative Databases in Identifying Patients With Rheumatoid Arthritis: A Validation Study Using the Medical Records of Rheumatologists†
Article first published online: 24 SEP 2013
Copyright © 2013 by the American College of Rheumatology
Arthritis Care & Research
Volume 65, Issue 10, pages 1582–1591, October 2013
How to Cite
Widdifield, J., Bernatsky, S., Paterson, J. M., Tu, K., Ng, R., Thorne, J. C., Pope, J. E. and Bombardier, C. (2013), Accuracy of Canadian Health Administrative Databases in Identifying Patients With Rheumatoid Arthritis: A Validation Study Using the Medical Records of Rheumatologists. Arthritis Care Res, 65: 1582–1591. doi: 10.1002/acr.22031
The opinions, results, and conclusions are those of the authors and are independent from the funding sources. No endorsement by the Institute for Clinical Evaluative Sciences or the Ontario Ministry of Health and Long-Term Care is intended or should be inferred.
- Issue published online: 24 SEP 2013
- Article first published online: 24 SEP 2013
- Accepted manuscript online: 16 APR 2013 08:54AM EST
- Manuscript Accepted: 29 MAR 2013
- Manuscript Received: 1 OCT 2012
- Institute for Clinical Evaluative Sciences, a nonprofit research corporation funded by the Ontario Ministry of Health and Long-Term Care
- Ontario Biologics Research Initiative/Ontario Best Practices Research Initiative
- Career award from the Fonds de la Recherche en Santé du Québec
- Canadian Institutes of Health Research fellowship award in the Area of Primary Care (2011–2013)
- Canada Research Chair in Knowledge Transfer for Musculoskeletal Care (2002–2016)
- Pfizer Research Chair in Rheumatology
Health administrative data can be a valuable tool for disease surveillance and research. Few studies have rigorously evaluated the accuracy of administrative databases for identifying rheumatoid arthritis (RA) patients. Our aim was to validate administrative data algorithms to identify RA patients in Ontario, Canada.
We performed a retrospective review of a random sample of 450 patients from 18 rheumatology clinics. Using rheumatologist-reported diagnosis as the reference standard, we tested and validated different combinations of physician billing, hospitalization, and pharmacy data.
One hundred forty-nine rheumatology patients were classified as having RA and 301 were classified as not having RA based on our reference standard definition (study RA prevalence 33%). Overall, algorithms that included physician billings had excellent sensitivity (range 94–100%). Specificity and positive predictive value (PPV) were modest to excellent and increased when algorithms included multiple physician claims or specialist claims. The addition of RA medications did not significantly improve algorithm performance. The algorithm of “(1 hospitalization RA code ever) OR (3 physician RA diagnosis codes [claims] with ≥1 by a specialist in a 2-year period)” had a sensitivity of 97%, specificity of 85%, PPV of 76%, and negative predictive value of 98%. Most RA patients (84%) had an RA diagnosis code present in the administrative data within ±1 year of a rheumatologist's documented diagnosis date.
We demonstrated that administrative data can be used to identify RA patients with a high degree of accuracy. RA diagnosis date and disease duration are fairly well estimated from administrative data in jurisdictions of universal health care insurance.