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Calcif Tissue Int. 2019 Apr 29. doi: 10.1007/s00223-019-00557-6. [Epub ahead of print]

Identification of Patients with Osteoporotic Vertebral Fractures via Simple Text Search of Routine Radiology Reports.

Author information

1
Department of Orthopaedic Surgery, Westmead Hospital, Westmead, NSW, Australia.
2
Western Sydney University, Sydney, NSW, Australia.
3
Department of Endocrinology and Metabolism, Concord Repatriation General Hospital, Concord, NSW, Australia. kirtan.ganda@sydney.edu.au.
4
Concord Clinical School, University of Sydney, Sydney, NSW, Australia. kirtan.ganda@sydney.edu.au.
5
Department of Radiology, Concord Repatriation General Hospital, Concord, NSW, Australia.
6
Department of Endocrinology and Metabolism, Concord Repatriation General Hospital, Concord, NSW, Australia.
7
Concord Clinical School, University of Sydney, Sydney, NSW, Australia.

Abstract

Secondary fracture prevention programs mostly identify patients with symptomatic non-vertebral fractures, whereas asymptomatic vertebral fractures are usually missed. We here describe the development and validation of a simple method to systematically identify patients with radiographic vertebral fractures using simple text-based searching of free-text radiology reports. The study consisted of two phases. In the development phase (DP), twelve search terms were used to identify vertebral fractures in all X-ray and CT reports issued over a period of 6 months. Positive reports were manually reviewed to confirm whether or not a vertebral fracture had in fact been reported. The three search terms most effective in detecting vertebral fractures during the DP were then applied during the implementation phase (IP) over several weeks to test their ability to identify patients with vertebral fractures. The search terms 'Loss of Height' (LoH), 'Compression Fracture' (CoF) and 'Crush Fracture' (CrF) identified the highest number of imaging reports with a confirmed vertebral fracture. These three search terms identified 581 of 689 (84%) of all true vertebral fractures with a positive predictive value of 76%. Using these three terms in the IP, 126 reports were identified of which 100 (79%) had a vertebral fracture confirmed on manual review. Amongst a sample of 587 reports in week 1 of the IP, 7 (1.2%) were false negatives. Many patients with vertebral fractures can be identified via a simple text-based search of electronic radiology reports. This method may be utilised by secondary fracture prevention programs to narrow the 'care gap' in osteoporosis management.

KEYWORDS:

Electronic records; Imaging; Osteoporosis; Text search; Vertebral fracture identification

PMID:
31037427
DOI:
10.1007/s00223-019-00557-6

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