Abstract
BackgroundPopulation-based administrative data have been used to study osteoporosis-related fracture risk factors and outcomes, but there has been limited research about the validity of these data for ascertaining fracture cases. The objectives of this study were to: (a) compare fracture incidence estimates from administrative data with estimates from population-based clinically-validated data, and (b) test for differences in incidence estimates from multiple administrative data case definitions.MethodsThirty-five case definitions for incident fractures of the hip, wrist, humerus, and clinical vertebrae were constructed using diagnosis codes in hospital data and diagnosis and service codes in physician billing data from Manitoba, Canada. Clinically-validated fractures were identified from the Canadian Multicentre Osteoporosis Study (CaMos). Generalized linear models were used to test for differences in incidence estimates.ResultsFor hip fracture, sex-specific differences were observed in the magnitude of under- and over-ascertainment of administrative data case definitions when compared with CaMos data. The length of the fracture-free period to ascertain incident cases had a variable effect on over-ascertainment across fracture sites, as did the use of imaging, fixation, or repair service codes. Case definitions based on hospital data resulted in under-ascertainment of incident clinical vertebral fractures. There were no significant differences in trend estimates for wrist, humerus, and clinical vertebral case definitions.ConclusionsThe validity of administrative data for estimating fracture incidence depends on the site and features of the case definition.
Highlights
Population-based administrative data have been used to study osteoporosis-related fracture risk factors and outcomes, but there has been limited research about the validity of these data for ascertaining fracture cases
Curtis et al [14] reported that an incident clinical vertebral fracture case definition based on hospital diagnoses had a positive predictive value (PPV) of 91%
Diagnosis codes in hospital and physician data have been validated and used extensively in Manitoba [21,22,23] and in other Canadian jurisdictions [24] for research about chronic conditions, and they have been used in multiple studies about osteoporosis-related fractures [9,11,25]
Summary
Population-based administrative data have been used to study osteoporosis-related fracture risk factors and outcomes, but there has been limited research about the validity of these data for ascertaining fracture cases. Administrative data, routinely collected records used for health system management and physician remuneration, are a common tool for population-based studies about infectious and chronic conditions because these data contain diagnosis codes for ascertaining disease cases. A case definition based on diagnoses in a broad set of administrative databases, including hospital, physician billing, and emergency room data, had a PPV of only 46%. Case definition characteristics that have varied across studies include the administrative data source, diagnosis codes, use of codes for fracturerelated services or procedures, and the length of the fracture-free period to ascertain incident cases [17,18,19]
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