Identifying proximal humerus fractures: an algorithmic approach using registers and radiological visit data
Authors' conclusion
The proposed approach enables a more reliable way of identifying proximal humerus fractures from administrative data.
Study context
- Population
- Post-menopausal women living in the Kuopio region 2004–2022 (OSTPRE cohort); gold standard from patient records and self-reports
- Participants
- 11,863 post-menopausal women
- Comparison
- Algorithm combining register and radiological visit data vs traditional register analysis
- Outcome
- Reliability of automated identification of proximal humerus fractures from administrative datasets without manual review
Methodological detailsalgorithm development and validation, register-based
- Algorithm development and validation
- Register-based
Performance
As reported in the abstract
Identification of proximal humerus fractures (coverage, false discovery rate)
Coverage
False discovery rate
Further findings
National registers' coverage over the 19-year period
- Coverage initially improved but then settled at
- 75%
Image archive (PACS) coverage of radiographs for fracture cases
- Almost complete coverage, but excluding false positives poses a challenge
Original publication
Identifying proximal humerus fractures: an algorithmic approach using registers and radiological visit data. Osteoporos Int. Published 7 February 2025. doi:10.
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