| Autor: |
Varacallo, Matthew A., Fox, Edward J., Paul, Emmanuel M., Hassenbein, Susan E., Warlow, Pamela M. |
| Zdroj: |
Geriatric Orthopaedic Surgery & Rehabilitation; September 2013, Vol. 4 Issue: 3 p89-98, 10p |
| Abstrakt: |
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. |
| Databáze: |
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