ACR Open Rheumatology (Jul 2020)

Determination of Rheumatoid Arthritis Incidence and Prevalence in Alberta Using Administrative Health Data

  • Deborah A. Marshall,
  • Tram Pham,
  • Peter Faris,
  • Guanmin Chen,
  • Siobhan O’Donnell,
  • Claire E. H. Barber,
  • Sharon LeClercq,
  • Steven Katz,
  • Joanne Homik,
  • Jatin N. Patel,
  • Elena Lopatina,
  • Jill Roberts,
  • Dianne Mosher

DOI
https://doi.org/10.1002/acr2.11158
Journal volume & issue
Vol. 2, no. 7
pp. 424 – 429

Abstract

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Objective The objective of the study was to estimate the incidence and prevalence of rheumatoid arthritis (RA) in Alberta using administrative health data. Methods We identified RA cases in patients 16 years and older by applying a national case definition to linked administrative health data (ie, hospital discharge abstract records, physician claims, and health insurance registry records) using a unique personal identifier. Incidence and prevalence are reported for the 2015‐2016 fiscal year and a trend analysis from 2011‐2012 to 2015‐2016. Incidence and prevalence estimates were standardized using the 2011 Canadian census population. Results In 2015‐2016, the overall crude incidence was 0.74 [95% confidence interval (CI): 0.71‐0.77] per 1000 and crude prevalence was 1.08% (95% CI: 1.07‐1.09). The women‐to‐men crude incidence and prevalence sex ratios were 2.04 and 2.19, respectively. People aged 65 to 79 years had the highest incidence of RA, and the highest prevalence was observed among those 80 years and older. From 2011‐2012 to 2015‐2016, the overall age‐standardized incidence decreased [0.97 (95% CI: 0.94‐1.01) to 0.79 (95% CI: 0.76‐0.82) per 1000], whereas age‐standardized prevalence remained constant [1.17 (95% CI: 1.15‐1.18) to 1.18 (95% CI: 1.17‐1.19)]. Conclusion In Alberta, there was a decreasing trend in RA incidence over the study period, whereas prevalence was stable. These estimates, combined with clinical data, will be used to measure system performance for quality improvement and to inform simulation modeling for planning the expected demand for health services for patients living with RA.