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.
Authors
- Markus J. Seibel (ORCID: https://orcid.org/0000-0002-2701-378X)
- Brendan Goodger
- Patrick Bolton (ORCID: https://orcid.org/0000-0002-5270-6262)
- Michael G. Moore (ORCID: https://orcid.org/0000-0002-9160-7224)
- Daniel Moses (ORCID: https://orcid.org/0000-0001-9404-0035)
Institutions
- 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)
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