Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Marshall DA

PROVIDER: S-EPMC7368140 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

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

Marshall Deborah A DA Pham Tram T Faris Peter P Chen Guanmin G O'Donnell Siobhan S Barber Claire E H CEH LeClercq Sharon S Katz Steven S Homik Joanne J Patel Jatin N JN Lopatina Elena E Roberts Jill J Mosher Dianne D

ACR open rheumatology 20200622 7

<h4>Objective</h4>The objective of the study was to estimate the incidence and prevalence of rheumatoid arthritis (RA) in Alberta using administrative health data.<h4>Methods</h4>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 ...[more]

PMID: 32567816

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Project description:IntroductionThe incidence and prevalence of diabetes within a population are important public health metrics. Pharmaceutical administrative data may offer a resource that can contribute to quantifying these measures using the recorded signals derived from the drugs used to treat people with diabetes.ObjectiveTo estimate the longitudinal incidence and prevalence of drug treated (DT) diabetes in Australia utilising an Australian Pharmaceutical Benefits Scheme (PBS) dataset and compare estimates with community survey data for all diabetes reported in the Australian National Health Survey (NHS).MethodsPersons with DT diabetes were identified within the PBS dataset using assigned Anatomic Therapeutic Chemical codes for 'Drugs used in diabetes'. Prevalent persons with DT diabetes were determined by a single annual treatment, and incident cases from the earliest treatment with diabetes medications. Counts were aggregated by age group and utilised Australian national census data as a denominator to calculate diabetes disease frequencies for the period 2004-14. Comparison of PBS prevalence data was made with NHS surveys over equivalent years.ResultsThe age adjusted incidence of DT diabetes was 3.4/1000 in 2006 and increased to 3.8/1000 in 2011 and 5.1/1000 in 2014. Age adjusted prevalence of DT diabetes in Australia also rose from 26.7/1000 in 2006 to 32.1/1000 in 2011 and 42.1/1000 in 2014. DT diabetes prevalence estimates correlated with NHS estimates of self-reported diabetes prevalence across age groups and in 2014 was r = 0.987. However, PBS estimates of DT diabetes prevalence generally underestimated NHS values of self-reported diabetes in older age groups with mean percentage differences of -22% to -3%. In contrast, PBS data captured more younger persons with diabetes in comparison to NHS data. These differences were then used to adjust DT diabetes incidence rates to provide age specific estimates that could potentially reflect diabetes incidence estimates acquired by community survey.ConclusionsPBS data representing dispensed medications prescribed to persons with diabetes offers a perspective for the assessment of diabetes incidence and prevalence. PBS derived DT diabetes prevalence estimates correlate well with community survey estimates of self-reported diabetes, but underestimate NHS data in older age groups. Calibrated DT incidence estimates may potentially reflect community survey derived diabetes incidence estimates and may offer a method for longitudinal monitoring.

Project description:BackgroundConfounding by disease severity is an issue in pharmacoepidemiology studies of rheumatoid arthritis (RA), due to channeling of sicker patients to certain therapies. To address the issue of limited clinical data for confounder adjustment, a patient-level prediction model to differentiate between patients prescribed and not prescribed advanced therapies was developed as a surrogate for disease severity, using all available data from a US claims database.MethodsData from adult RA patients were used to build regularized logistic regression models to predict current and future disease severity using a biologic or tofacitinib prescription claim as a surrogate for moderate-to-severe disease. Model discrimination was assessed using the area under the receiver (AUC) operating characteristic curve, tested and trained in Optum Clinformatics® Extended DataMart (Optum) and additionally validated in three external IBM MarketScan® databases. The model was further validated in the Optum database across a range of patient cohorts.ResultsIn the Optum database (n = 68,608), the AUC for discriminating RA patients with a prescription claim for a biologic or tofacitinib versus those without in the 90 days following index diagnosis was 0.80. Model AUCs were 0.77 in IBM CCAE (n = 75,579) and IBM MDCD (n = 7,537) and 0.75 in IBM MDCR (n = 36,090). There was little change in the prediction model assessing discrimination 730 days following index diagnosis (prediction model AUC in Optum was 0.79).ConclusionsA prediction model demonstrated good discrimination across multiple claims databases to identify RA patients with a prescription claim for advanced therapies during different time-at-risk periods as proxy for current and future moderate-to-severe disease. This work provides a robust model-derived risk score that can be used as a potential covariate and proxy measure to adjust for confounding by severity in multivariable models in the RA population. An R package to develop the prediction model and risk score are available in an open source platform for researchers.

Dataset Information

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

Objective

Methods

Results

Conclusion

Publications

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

Similar Datasets

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