Literature DB >> 34510231

Electronic search programs are effective in identifying patients with minimal trauma fractures.

K Blaker1, A Wijewardene2,3,4, E White5, G Stokes6, S Chong1, K Ganda1,7,8, L Ridley7,9, S Brown10, C White6, R Clifton-Bligh5,7, M J Seibel1,7,8.   

Abstract

We assessed two electronic search tools that screen medical records for documented fractures. Both programs reliably identified patients with any fracture but missed individuals with minimal trauma fracture to different degrees. A hybrid tool combining the methodology of both tools is likely to improve the identification of those with osteoporosis.
PURPOSE: Most patients who suffer a minimal trauma fracture remain undiagnosed, placing them at high risk of refracture. Case finding can be improved by electronic search tools that screen medical records for documented fractures. Here, we assessed the efficacy of two new programs, AES and XRAIT, in identifying patients with minimal trauma fracture.
METHODS: Each tool was applied to search the electronic medical record and/or radiology reports at two tertiary hospitals in Sydney, Australia, from 1 July to 31 December 2018. Samples of the extracted reports were then manually reviewed to determine the sensitivity of each program in detecting minimal trauma fractures.
RESULTS: At the two centers, AES detected 872 and 1364 cases, whereas XRAIT identified 1414 and 2180 patients with fractures, respectively. The true positive rate for "any fracture" was similar for both instruments (77-88%). However, the ability to detect "minimal trauma fractures" differed between programs and centers (53-75% accuracy), with each tool identifying separate subsets of patients. Concordance between both tools was less than half of the combined total number of minimal trauma fractures (43-45%). Considering the total number of minimal trauma fractures detected by both tools combined, AES correctly identified 52-55% of cases while XRAIT identified 88-93% of cases.
CONCLUSION: Both programs reliably identified patients with any fracture but missed individuals with minimal trauma fracture to different degrees. Hybrid tools combining the methodology of XRAIT and AES are likely to improve the identification of patients who require investigation and treatment for osteoporosis.
© 2021. International Osteoporosis Foundation and National Osteoporosis Foundation.

Entities:  

Keywords:  Electronic search tools; Fracture liaison service; Health informatics; Minimal trauma fracture; Natural language processing; Osteoporosis

Mesh:

Year:  2021        PMID: 34510231     DOI: 10.1007/s00198-021-06105-z

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  2 in total

1.  Automated identification of postoperative complications within an electronic medical record using natural language processing.

Authors:  Harvey J Murff; Fern FitzHenry; Michael E Matheny; Nancy Gentry; Kristen L Kotter; Kimberly Crimin; Robert S Dittus; Amy K Rosen; Peter L Elkin; Steven H Brown; Theodore Speroff
Journal:  JAMA       Date:  2011-08-24       Impact factor: 56.272

2.  A comparison of two approaches to text processing: facilitating chart reviews of radiology reports in electronic medical records.

Authors:  Julie A Womack; Matthew Scotch; Cynthia Gibert; Wendy Chapman; Michael Yin; Amy C Justice; Cynthia Brandt
Journal:  Perspect Health Inf Manag       Date:  2010-10-01
  2 in total

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