Preparing a collection of radiology examinations for distribution and retrieval

dc.contributor.authorDemner-Fushman, Dina
dc.contributor.authorKohli, Marc D.
dc.contributor.authorRosenman, Marc B.
dc.contributor.authorShooshan, Sonya E.
dc.contributor.authorRodriguez, Laritza
dc.contributor.authorAntani, Sameer
dc.contributor.authorThoma, George R.
dc.contributor.authorMcDonald, Clement J.
dc.contributor.departmentDepartment of Radiology and Imaging Sciences, IU School of Medicineen_US
dc.date.accessioned2017-07-31T13:52:40Z
dc.date.available2017-07-31T13:52:40Z
dc.date.issued2016-03
dc.description.abstractOBJECTIVE: Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. MATERIALS AND METHODS: The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. RESULTS: The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. CONCLUSION: Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/).en_US
dc.identifier.citationDemner-Fushman, D., Kohli, M. D., Rosenman, M. B., Shooshan, S. E., Rodriguez, L., Antani, S., … McDonald, C. J. (2016). Preparing a collection of radiology examinations for distribution and retrieval. Journal of the American Medical Informatics Association : JAMIA, 23(2), 304–310. http://doi.org/10.1093/jamia/ocv080en_US
dc.identifier.urihttps://hdl.handle.net/1805/13649
dc.language.isoen_USen_US
dc.publisherOxford University Pressen_US
dc.relation.isversionof10.1093/jamia/ocv080en_US
dc.relation.journalJournal of the American Medical Informatics Associationen_US
dc.rightsPublisher Policyen_US
dc.sourcePMCen_US
dc.subjectInformation storage and retrievalen_US
dc.subjectAbstracting and indexingen_US
dc.subjectRadiographyen_US
dc.subjectMedical recordsen_US
dc.subjectBiometric identificationen_US
dc.titlePreparing a collection of radiology examinations for distribution and retrievalen_US
dc.typeArticleen_US
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