Medical Service Utilization with Osteoporosis

ABSTRACT

BACKGROUND: Although osteoporosis is increasing in the elderly population, attempts to analyze the patterns of medical service utilization for osteoporosis are currently not sufficient. The medical services and treatment patterns were investigated using Korea's National Health Insurance claims data, which includes all of the Korean population. METHODS: Through the patient identification algorithm developed by using the administrative claims data in 2007, the adult patients (between 50-100 years) with osteoporosis were identified. The age and gender of the patients who used medical service for osteoporosis were described, in relation with six dichotomous variables. The medical service use patterns such as the type of medical institution and conducting bone mineral density measurement were investigated. RESULTS: The number of patients who used medical service were 1,230,580 (females 89.9%). Sixty one point six percent of the patients were prescribed osteoporosis medicine (indicated for osteoporosis only), and 12.9% of the patients had experienced osteoporotic fracture. The primary medical institutions for treatment were clinics (54.3%), while hospitals were mainly used among the patients with a history of fracture and disease or drug use that may induce secondary osteoporosis. The number of visited medical institutions was 6.4 (as an outpatient) and 0.2 (as admissions) during 6 months. The proportion of patients who conducted bone mineral density measurements within one year before and after the diagnosis of osteoporosis was 66.7% and DXA was the most frequently used densitometry (46.3%). The average number of days for the prescriptions for osteoporosis medicine was 70 days. CONCLUSION: In order to prevent further osteoporotic fractures, appropriate management and treatment should be implemented for osteoporosis patients. To do this, we need to understand the current state of medical service utilization and the treatment of osteoporosis using the National Health Insurance claims data.