A quality improvement project to increase treatment rates of osteoporosis in general practice

Objective This study tests a model to improve the management of patients with an osteoporotic fracture. Methods Patients with fractures potentially due to osteoporosis were identified from imaging reports using computerised near natural language processing. A coordinator notified the referring GP about the finding and provided follow-up to remind GPs of the need for management. This provided an opportunity to assess action taken by the GP. Results Near natural language processing efficiently detected fractures in patients at risk of osteoporosis. GPs reported that they are managing osteoporosis in over 40% of patients identified. Notification of GPs coincided with a small increase in osteoporosis management. Conclusion Information technology can identify patient populations with clinically important risks such as osteoporosis. Methods to engage GPs to optimally address this risk have yet to be developed.

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Publication Details

Journal
Australian Health Review
Published
2024-10-16
DOI
https://doi.org/10.1071/ah24214
Primary Topic
Bone health and osteoporosis research
Type
article
Field-Weighted Citation Impact
0.00
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article

A quality improvement project to increase treatment rates of osteoporosis in general practice

Markus J. Seibel, Brendan Goodger, Patrick Bolton, Michael G. Moore et al.
Australian Health Review
Bone health and osteoporosis research
article

A quality improvement project to increase treatment rates of osteoporosis in general practice

Markus J. Seibel, Brendan Goodger, Patrick Bolton, Michael G. Moore, Daniel Moses
article en

Abstract

Objective This study tests a model to improve the management of patients with an osteoporotic fracture. Methods Patients with fractures potentially due to osteoporosis were identified from imaging reports using computerised near natural language processing. A coordinator notified the referring GP about the finding and provided follow-up to remind GPs of the need for management. This provided an opportunity to assess action taken by the GP. Results Near natural language processing efficiently detected fractures in patients at risk of osteoporosis. GPs reported that they are managing osteoporosis in over 40% of patients identified. Notification of GPs coincided with a small increase in osteoporosis management. Conclusion Information technology can identify patient populations with clinically important risks such as osteoporosis. Methods to engage GPs to optimally address this risk have yet to be developed.

Australian Health ReviewVol. 49(1)
Concord Repatriation General Hospital (AU), Hornsby Ku-ring-gai Hospital (AU), UNSW Sydney (AU), Eastern Health (AU), Sydney Children's Hospital (AU), South Eastern Sydney Local Health District (AU)
Openalex Percentile: Top 76%
Bone health and osteoporosis research
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