Mapping of HIE CT terms to LOINC®

analysis of content-dependent coverage and coverage improvement through new term creation

Paul Peng, Anton Oscar Beitia, Daniel Vreeman, George T. Loo, Bradley N. Delman, Frederick Thum, Tina Lowry, Jason S. Shapiro

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)19-27
Number of pages9
JournalJournal of the American Medical Informatics Association : JAMIA
Volume26
Issue number1
DOIs
StatePublished - Jan 1 2019

Fingerprint

Logical Observation Identifiers Names and Codes
Tomography
Terminology
Health Information Exchange
Radiology

ASJC Scopus subject areas

  • Health Informatics

Cite this

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; Loo, George T.; Delman, Bradley N.; Thum, Frederick; Lowry, Tina; Shapiro, Jason S.

In: Journal of the American Medical Informatics Association : JAMIA, Vol. 26, No. 1, 01.01.2019, p. 19-27.

Research output: Contribution to journalArticle

Peng, Paul ; Beitia, Anton Oscar ; Vreeman, Daniel ; Loo, George T. ; Delman, Bradley N. ; Thum, Frederick ; Lowry, Tina ; Shapiro, Jason S. / Mapping of HIE CT terms to LOINC® : analysis of content-dependent coverage and coverage improvement through new term creation. In: Journal of the American Medical Informatics Association : JAMIA. 2019 ; Vol. 26, No. 1. pp. 19-27.
@article{35a1c69cb4b64ab694ed2e9756690f1d,
title = "Mapping of HIE CT terms to LOINC{\circledR}: analysis of content-dependent coverage and coverage improvement through new term creation",
abstract = "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{\circledR}) 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.",
author = "Paul Peng and Beitia, {Anton Oscar} and Daniel Vreeman and Loo, {George T.} and Delman, {Bradley N.} and Frederick Thum and Tina Lowry and Shapiro, {Jason S.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1093/jamia/ocy135",
language = "English (US)",
volume = "26",
pages = "19--27",
journal = "Journal of the American Medical Informatics Association : JAMIA",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "1",

}

TY - JOUR

T1 - Mapping of HIE CT terms to LOINC®

T2 - analysis of content-dependent coverage and coverage improvement through new term creation

AU - Peng, Paul

AU - Beitia, Anton Oscar

AU - Vreeman, Daniel

AU - Loo, George T.

AU - Delman, Bradley N.

AU - Thum, Frederick

AU - Lowry, Tina

AU - Shapiro, Jason S.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85059260221&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059260221&partnerID=8YFLogxK

U2 - 10.1093/jamia/ocy135

DO - 10.1093/jamia/ocy135

M3 - Article

VL - 26

SP - 19

EP - 27

JO - Journal of the American Medical Informatics Association : JAMIA

JF - Journal of the American Medical Informatics Association : JAMIA

SN - 1067-5027

IS - 1

ER -