Estimating the Burden of Osteoarthritis to Plan for the Future.
OBJECTIVE
With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) is 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 data set 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 2 physician visits within 2 years or any hospital admission. Seven alternative case definitions were applied and compared.


RESULTS
Age- and sex-standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases per 1,000 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 the base case, estimates are sensitive to alternative case definitions.


CONCLUSIONS
Administrative databases are a key source for estimating the burden and epidemiologic 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.
University of Calgary, Calgary, Alberta, Canada.
Deborah A
DA
Marshall
University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Sonia
S
Vanderby
University of Calgary, Calgary, Alberta, Canada.
Cheryl
C
Barnabe
University of Calgary, Calgary, Alberta, Canada.
Karen V
KV
MacDonald
University of Waterloo, Waterloo, Ontario, Canada.
Colleen
C
Maxwell
University of Calgary, Calgary, Alberta, Canada.
Dianne
D
Mosher
Alberta Health Services, Calgary, Alberta, Canada.
Tracy
T
Wasylak
University of Manitoba, Winnipeg, Manitoba, Canada.
Lisa
L
Lix
Alberta Bone and Joint Health Institute, Calgary, Alberta, Canada.
Ed
E
Enns
Alberta Innovates-Health Solutions and University of Calgary, Calgary, Alberta, Canada.
Cy
C
Frank
Alberta Health Services and University of Calgary, Calgary, Alberta, Canada.
Tom
T
Noseworthy
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology; D000416:Alberta; D002170:Canada; D015331:Cohort Studies; D016001:Confidence Intervals; D016208:Databases, Factual; D005260:Female; D005544:Forecasting; D015577:Geriatric Assessment / Q000379:methods; D017048:Health Care Costs; D006295:Health Resources / Q000191:economics* / Q000639:trends; D006801:Humans; D008297:Male; D008875:Middle Aged; D010003:Osteoarthritis / Q000175:diagnosis / Q000191:economics* / Q000453:epidemiology* / Q000628:therapy; D010347:Patient Care Planning / Q000191:economics* / Q000639:trends; D012737:Sex Factors