Abstract
Healthcare claims and survey data are increasingly used to assess the osteoporosis burden, but agreement and comparative validity of derived indicators are poorly documented. We show that no single data source can estimate the osteoporosis burden. Instead, coupling data sources allows assessing its burden and associated treatment and knowledge gaps. PURPOSE: Healthcare claims data are increasingly used to assess the burden of osteoporosis and fragility fractures, although comparative evidence with other sources and especially self-reported data remains limited. Using the linkage of the French National Health Data System (SNDS) and Health Care and Insurance Survey (ESPS 2010-2014), we evaluated the agreement and comparative validity (concurrent and predictive) of several osteoporosis and clinical fragility fracture indicators and provided comprehensive estimates of their prevalence. METHODS: Individual data from 5039 ESPS participants aged ≥ 25 years were linked to SNDS. Follow-up data included a health self-assessment in 2014 and 5-year occurrence of fractures and mortality. Prevalence was estimated for each indicator (self-reported in ESPS, diagnosis and treatment of osteoporosis, and clinical fragility fractures in SNDS) using several combinations and capture-recapture. Kappa statistics assessed agreement between indicators. Multivariate models evaluated determinants of disagreement between sources and associations of indicators with health outcomes and new fractures (concurrent and predictive validity). RESULTS: Prevalence estimated by capture-recapture was 7.6% versus 4.1% and 2.2% for self-reported and treated osteoporosis, respectively. Agreement between indicators was slight to moderate. Education, limitation in daily activities, and number of chronic conditions influenced agreement. SNDS indicators had better validity than self-reported osteoporosis, especially for predicting new fractures. CONCLUSION: The French healthcare claims database provides valid indicators, although it is insufficient to assess and monitor the burden of osteoporosis in the general population. Coupling these indicators with self-reported data may help overcome these limitations and assess the treatment and knowledge gaps associated with osteoporosis.