4 research outputs found

    Patients’ Response Toward an Automated Orthopedic Osteoporosis Intervention Program

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    Osteoporosis is overshadowed in an era of chronic illnesses, and a care gap exists between physicians and patients. The aim of this study was to determine the effectiveness of implementing an automated system for identifying and sending a letter to patients at high risk for osteoporosis. Patients 50 years of age and older were tagged with an International Classification of Diseases, Ninth Revision , diagnostic code upon initial visit to the emergency department (ED), identifying potential fragility fractures. Automatically generated letters were sent via our osteoporosis database system to each patient 3 months after the initial visit to the ED. The letter indicated that he or she was at risk for osteoporosis and suggested that the patient schedule a follow-up appointment with a physician. Patients were subsequently telephoned 3 months after receiving the letter and asked about their current plan for follow-up. The control group did not receive a letter after departure from the ED. In the control group, 84 (85.71%) individuals of the total 98 did not have any follow-up but the remaining 14 (14.29%) sought a follow-up. In the intervention group, 62 (60.19%) individuals of 103 did schedule a follow-up, while the remaining 41 (39.81%) did not seek a follow-up. Thus, the patient follow-up response rate after fracture treatment improved with intervention ( P < .0001). Current literature has demonstrated the low rate of follow-up care addressing osteoporosis in patients experiencing fragility fractures (1%-25% without intervention). Research has shown the effectiveness of various types of intervention programs for improving the continuum of care for these high-risk patients. Nonautomated intervention programs can have a multitude of human-related system failures in identifying these patients. Our study successfully implements an automated system that is able to be applied to most hospitals with minimal cost and resources
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