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| File Size | 44.8 KiB |
|---|---|
| Date | September 16, 2015 |
| Downloads | 2 |
| Author | Deborah A Marshall, Sonia Vanderby, Cheryl Barnabe, Karen V MacDonald, Colleen Maxwell, Dianne Mosher, Tracy Wasylak, Lisa Lix, Ed Enns, Cy Frank, Tom Noseworthy |
Abstract
Background: With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) are expected to rise in Canada, increasing the demand for health resources. Resource planning to meet this increasing need requires estimates of the anticipated number of OA patients. Using administrative data from Alberta, we estimated OA incidence and prevalence rates and examined their sensitivity to alternative case definitions.
Methods: We identified cases in a linked dataset spanning 1993 to 2010 (Population Registry, Discharge Abstract Database, Physician Claims, Ambulatory Care Classification System and prescription drug data) using diagnostic codes and drug identification numbers. In the base case, incident cases were captured for patients with an OA diagnostic code for at least two physician visits within two years or any hospital admission. Seven alternative case definitions were applied and compared.
Results: Age-sex standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases/1000 population, respectively, in the base case. Physician Claims data alone captured 88% of OA cases. Prevalence rate estimates required 15 years of longitudinal data to plateau. Compared to base case, estimates are sensitive to alternative case definitions.
Conclusion: Administrative databases are a key source for estimating the burden and epidemiological trends of chronic diseases such as OA in Canada. Despite their limitations, these data provide valuable information for estimating disease burden and planning health services. Estimates of OA are mostly defined through Physician Claims data and require a long period of longitudinal data.
Background: With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) are expected to rise in Canada, increasing the demand for health resources. Resource planning to meet this increasing need requires estimates of the anticipated number of OA patients. Using administrative data from Alberta, we estimated OA incidence and prevalence rates and examined their sensitivity to alternative case definitions.
Methods: We identified cases in a linked dataset spanning 1993 to 2010 (Population Registry, Discharge Abstract Database, Physician Claims, Ambulatory Care Classification System and prescription drug data) using diagnostic codes and drug identification numbers. In the base case, incident cases were captured for patients with an OA diagnostic code for at least two physician visits within two years or any hospital admission. Seven alternative case definitions were applied and compared.
Results: Age-sex standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases/1000 population, respectively, in the base case. Physician Claims data alone captured 88% of OA cases. Prevalence rate estimates required 15 years of longitudinal data to plateau. Compared to base case, estimates are sensitive to alternative case definitions.
Conclusion: Administrative databases are a key source for estimating the burden and epidemiological trends of chronic diseases such as OA in Canada. Despite their limitations, these data provide valuable information for estimating disease burden and planning health services. Estimates of OA are mostly defined through Physician Claims data and require a long period of longitudinal data.