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Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation.
Peng, Paul; Beitia, Anton Oscar; Vreeman, Daniel J; Loo, George T; Delman, Bradley N; Thum, Frederick; Lowry, Tina; Shapiro, Jason S.
Afiliación
  • Peng P; Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Beitia AO; Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Vreeman DJ; Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.
  • Loo GT; Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Delman BN; Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Thum F; Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Lowry T; Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Shapiro JS; Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
J Am Med Inform Assoc ; 26(1): 19-27, 2019 01 01.
Article en En | MEDLINE | ID: mdl-30445562
Objective: We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology. Methods: Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions. Results: LOINC's content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001). Conclusion: LOINC's content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Tomografía Computarizada por Rayos X / Logical Observation Identifiers Names and Codes / Intercambio de Información en Salud Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Tomografía Computarizada por Rayos X / Logical Observation Identifiers Names and Codes / Intercambio de Información en Salud Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
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