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Automated system could efficiently identify high-risk osteoporosis patients
Date:1/28/2014

An automated system that identifies high-risk osteoporosis patients being treated for fractures and can generate letters encouraging follow-up is an effective way to promote osteoporosis intervention and prevent future fractures, according to Penn State College of Medicine researchers.

The researchers identified patients at least 50 years old with fractures who were seeking medical help at the emergency department of Penn State Milton S. Hershey Medical Center. They then analyzed treatment codes to find fractures that seemed to be from bone fragility -- a broken bone caused by a fall from standing height or less. In all, 103 patients were identified.

To do this, researchers received data monthly from the hospital's finance department, which was used to autopopulate a spreadsheet created specifically to screen for osteoporosis. This database was then screened further to remove patients whose injuries were not consistent with fragility fractures. Letters were then computer-generated and mailed to the final list.

Evidence suggests that less than 30 percent of postmenopausal women and less than 10 percent of men with a prior fragility fracture are treated for osteoporosis.

"Our almost fully automated osteoporosis system identifies these patients, requires minimal resources -- many of which are already currently in U.S. hospitals, but just need to be tapped -- and delivers substantially improved osteoporosis intervention results," said Edward Fox, professor of orthopedics.

Patients were sent a letter within three months of their emergency room visit that explained that they may be at risk for osteoporosis and encouraged them to schedule an appointment with their doctor or the hospital's bone health clinic. A follow-up phone call was placed three months after the letter, asking if follow-up treatment had occurred.

For comparison, a group of 98 patients who did not receive letters were also contacted by phone six months after being treat
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Contact: Matthew Solovey
msolovey@hmc.psu.edu
717-531-8606
Penn State
Source:Eurekalert

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