Evaluating Completeness of a Radiology Glossary Using Iterative Refinement.
A lay-language glossary of radiology, built to help patients better understand the content of their radiology reports, has been analyzed for its coverage and readability, but not for its completeness. We present an iterative method to sample radiology reports, identify "missing" terms, and measure t...
| Publicado en: | Journal of Digital Imaging Vol. 32; no. 3; pp. 417 - 420 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136223487&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136223487 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2019 vid: 32 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136223487 136223487 136223487 10.1007/s10278-018-0137-0 136223487 ppf: 417 ppct: 3 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Evaluating Completeness of a Radiology Glossary Using Iterative Refinement. aug: au: Chan, Peter Y. W. Kahn, Charles E. affil: Department of Radiology, University of Pennsylvania, 3400 Spruce Street, 19104, Philadelphia, PA, USA sug: subj: Diagnostic Imaging Dictionaries Standards Reports Standards Quality Improvement Random Sample United States Academic Medical Centers Descriptive Statistics Vocabulary Nomenclature ab: A lay-language glossary of radiology, built to help patients better understand the content of their radiology reports, has been analyzed for its coverage and readability, but not for its completeness. We present an iterative method to sample radiology reports, identify "missing" terms, and measure the glossary's completeness. We hypothesized that the refinement process would reduce the number of missing terms to fewer than 1 per report. A random sample of 1000 radiology reports from a large US academic health system was divided into 10 cohorts of 100 reports each. Each cohort was reviewed in sequence by two investigators to identify terms (single words and multi-word phrases) absent from the glossary. Terms marked as new were added to the glossary and hence was shown as matched in subsequent cohorts. This HIPAA-compliant study was IRB-approved; informed consent was waived. The refinement process added a mean of 288.0 new terms per 100 reports in the first 5 cohorts vs. a mean of 66.0 new terms per 100 reports in the last 5 cohorts; the difference was statistically significant (p <.01). After reviewing 500 reports, the review process found fewer than 1 new term per report in each of 500 subsequent reports. The findings suggest that 500 to 1000 reports is adequate to test the completeness of a glossary, and that the glossary after iterative refinement achieved a high level of completeness to cover the vocabulary of radiology reports. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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