title: Automated Reconciliation of Radiology Reports and Discharge Summaries.
abstract: We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g., fractures) there is often a multi-day delay before the radiology report is available to ER staff, by which time the patient may have been discharged home with the possibility of undiagnosed fractures. ER staff, currently, have to manually review and reconcile radiology reports with the ER discharge diagnosis; this is a laborious and error-prone manual process. Using radiology reports from three different hospitals, we show that extracting detailed features from the reports to train Support Vector Machines can effectively automate the identification of limb fractures, dislocations and foreign bodies. These can be automatically reconciled with a patient's discharge diagnosis from the ER to identify a number of cases where limb abnormalities went undiagnosed.
authors.affiliation: Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia; Queensland University of Technology, Brisbane, QLD, Australia.
authors.forename: Bevan
authors.initials: B
authors.lastname: Koopman
authors.affiliation: Queensland University of Technology, Brisbane, QLD, Australia.
authors.forename: Guido
authors.initials: G
authors.lastname: Zuccon
authors.affiliation: Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia.
authors.forename: Amol
authors.initials: A
authors.lastname: Wagholikar
authors.affiliation: Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia.
authors.forename: Kevin
authors.initials: K
authors.lastname: Chu
authors.affiliation: Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia.
authors.forename: John
authors.initials: J
authors.lastname: O'Dwyer
authors.affiliation: Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia.
authors.forename: Anthony
authors.initials: A
authors.lastname: Nguyen
authors.affiliation: Gold Coast Hospital, Gold Coast, QLD, Australia.
authors.forename: Gerben
authors.initials: G
authors.lastname: Keijzers
mesh_terms: D003951:Diagnostic Errors / Q000517:prevention & control; D004636:Emergency Service, Hospital; D005121:Extremities / Q000000981:diagnostic imaging / Q000293:injuries; D006801:Humans; D000069550:Machine Learning; D009323:Natural Language Processing; D063886:Patient Discharge Summaries; D011871:Radiology; D011873:Radiology Information Systems; D012984:Software; D060388:Support Vector Machine; D014947:Wounds and Injuries / Q000000981:diagnostic imaging*