Introduction
What is new?
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This is the first systematic review to be conducted to determine the validity of diagnostic algorithms for osteoporosis and fractures in administrative data.
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Findings from this systematic review suggest that administrative data can be used to identify hip fractures.
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However, existing diagnostic algorithms to identify osteoporosis and vertebral fractures in administrative data are suboptimal and require further development.
Osteoporosis is a disease characterized by decreased bone mass and increased fracture risk. It is associated with significant morbidity, including fractures, impaired health-related quality of life, and increased mortality [1], [2]. In addition, the burden of disease related to osteoporosis and fractures is projected to increase markedly as the population ages. As such, osteoporosis and fracture risk have become important public health problems warranting surveillance [2].
Health administrative data are defined as information passively collected, often by government and health care providers, for the purpose of managing health care delivery. Often, the databases exist primarily for reimbursement purposes [3]. In Canada (as in other countries), health administrative databases record population-level data (because almost all citizens are covered by the physician billing and hospital databases in each province). Different administrative databases contain information on important variables, including demographic characteristics, hospitalizations, in- and outpatient physician visits and services, filled prescriptions, and vital status. Health administrative data have thus been used to pursue population-level health outcomes research and disease surveillance. In the field of osteoporosis, health administrative data have been used to study the epidemiology of the disease and as a tool for disease surveillance [4], [5], [6], [7], [8], [9].
Because health administrative databases are generally not designed for the purposes of conducting health research per se, health researchers using these sources of data had to develop definitions and/or algorithms to identify the diagnoses of interest in the databases ad hoc. Not surprisingly, though, the results and interpretation of those studies may be affected by the validity of the given definitions and/or algorithms. Because administrative data have the potential to be a rich source of data to pursue population-based research in osteoporosis and fracture risk assessment, we wished to review the validity of existing algorithms to diagnose osteoporosis and fractures in administrative data. We formulated the following tentative question: How valid are diagnoses of osteoporosis and hip, vertebral, and other fractures in administrative databases?