SUMMARY: A performance algorithm can be successfully used by bone density technologists at the time of a bone density test to identify patients with an indication for vertebral fracture assessment (VFA). Doing so appropriately increases physician prescription of fracture prevention medication. INTRODUCTION: Densitometric spine imaging (vertebral fracture assessment, VFA) can identify prevalent vertebral fracture but is underutilized. We developed an algorithm by which DXA technologists identify patients for whom VFA should be performed. Following this algorithm, VFA was performed in patients whose lowest T-score (lumbar spine, total hip, or femoral neck) was between -1.5 and -2.4 inclusive and with one of the following: age, ≥ 65 years; height loss, ≥ 1.5 in.; or current systemic glucocorticoid therapy. Our main objectives were to assess change in VFA utilization at two other healthcare organizations after algorithm implementation, and to estimate the association of VFA results with prescription of fracture prevention medication. METHODS: The proportions of patients with an indication for VFA who had one performed before and after algorithm implementation were compared. Logistic regression was used to estimate the multivariable-adjusted association of VFA results with subsequent prescription of fracture prevention medication adjusted for healthcare organization (study site). RESULTS: After algorithm introduction, appropriate VFA use rose significantly Patients with a VFA positive for vertebral fracture had an odds ratio of 3.2 (95 % C.I., 2.1- 5.1) for being prescribed new fracture prevention medication, adjusted for age, sex, prior clinical fracture, use of glucocorticoid medication, femoral neck bone mineral density T-score, and study site. CONCLUSIONS: An algorithm to identify those for whom VFA is indicated can successfully be implemented by DXA technologists. Documentation of vertebral fracture increases prescription of fracture prevention medication for patients who otherwise lack an apparent indication for such therapy.
SUMMARY: A performance algorithm can be successfully used by bone density technologists at the time of a bone density test to identify patients with an indication for vertebral fracture assessment (VFA). Doing so appropriately increases physician prescription of fracture prevention medication. INTRODUCTION: Densitometric spine imaging (vertebral fracture assessment, VFA) can identify prevalent vertebral fracture but is underutilized. We developed an algorithm by which DXA technologists identify patients for whom VFA should be performed. Following this algorithm, VFA was performed in patients whose lowest T-score (lumbar spine, total hip, or femoral neck) was between -1.5 and -2.4 inclusive and with one of the following: age, ≥ 65 years; height loss, ≥ 1.5 in.; or current systemic glucocorticoid therapy. Our main objectives were to assess change in VFA utilization at two other healthcare organizations after algorithm implementation, and to estimate the association of VFA results with prescription of fracture prevention medication. METHODS: The proportions of patients with an indication for VFA who had one performed before and after algorithm implementation were compared. Logistic regression was used to estimate the multivariable-adjusted association of VFA results with subsequent prescription of fracture prevention medication adjusted for healthcare organization (study site). RESULTS: After algorithm introduction, appropriate VFA use rose significantly Patients with a VFA positive for vertebral fracture had an odds ratio of 3.2 (95 % C.I., 2.1- 5.1) for being prescribed new fracture prevention medication, adjusted for age, sex, prior clinical fracture, use of glucocorticoid medication, femoral neck bone mineral density T-score, and study site. CONCLUSIONS: An algorithm to identify those for whom VFA is indicated can successfully be implemented by DXA technologists. Documentation of vertebral fracture increases prescription of fracture prevention medication for patients who otherwise lack an apparent indication for such therapy.
Authors: John T Schousboe; Mark L Davison; Bryan Dowd; Kathleen Thiede Call; Paul Johnson; Robert L Kane Journal: Med Care Date: 2011-03 Impact factor: 2.983
Authors: R Lindsay; S L Silverman; C Cooper; D A Hanley; I Barton; S B Broy; A Licata; L Benhamou; P Geusens; K Flowers; H Stracke; E Seeman Journal: JAMA Date: 2001-01-17 Impact factor: 56.272
Authors: T Fuerst; C Wu; H K Genant; G von Ingersleben; Y Chen; C Johnston; M J Econs; N Binkley; T J Vokes; G Crans; B H Mitlak Journal: Osteoporos Int Date: 2008-12-13 Impact factor: 4.507
Authors: Eugene V McCloskey; Sreekanth Vasireddy; Jane Threlkeld; Joanne Eastaugh; Ailsa Parry; Nicolas Bonnet; Monique Beneton; John A Kanis; Diane Charlesworth Journal: J Bone Miner Res Date: 2008-10 Impact factor: 6.741
Authors: John T Schousboe; Tien Vo; Brent C Taylor; Peggy M Cawthon; Ann V Schwartz; Douglas C Bauer; Eric S Orwoll; Nancy E Lane; Elizabeth Barrett-Connor; Kristine E Ensrud Journal: J Bone Miner Res Date: 2015-10-21 Impact factor: 6.741