Impact of Selective Mapping Strategies on Automated Laboratory Result Notification to Public Health Authorities

dc.contributor.authorGamache, Roland E
dc.contributor.authorDixon, Brian E.
dc.contributor.authorGrannis, Shaun
dc.contributor.authorVreeman, Daniel J
dc.date.accessioned2014-04-22T19:32:11Z
dc.date.available2014-04-22T19:32:11Z
dc.date.issued2012-11
dc.description.abstractAutomated electronic laboratory reporting (ELR) for public health has many potential advantages, but requires mapping local laboratory test codes to a standard vocabulary such as LOINC. Mapping only the most frequently reported tests provides one way to prioritize the effort and mitigate the resource burden. We evaluated the implications of selective mapping on ELR for public health by comparing reportable conditions from an operational ELR system with the codes in the LOINC Top 2000. Laboratory result codes in the LOINC Top 2000 accounted for 65.3% of the reportable condition volume. However, by also including the 129 most frequent LOINC codes that identified reportable conditions in our system but were not present in the LOINC Top 2000, this set would cover 98% of the reportable condition volume. Our study highlights the ways that our approach to implementing vocabulary standards impacts secondary data uses such as public health reporting.en_US
dc.identifier.citationGamache, R. E., Dixon, B. E., Grannis, S., & Vreeman, D. J. (2012). Impact of selective mapping strategies on automated laboratory result notification to public health authorities. In AMIA Annual Symposium Proceedings (Vol. 2012, p. 228). American Medical Informatics Association.en_US
dc.identifier.urihttps://hdl.handle.net/1805/4306
dc.language.isoen_USen_US
dc.rightsAttribution 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/
dc.subjectelectronic laboratory reportingen_US
dc.subjectselective mappingen_US
dc.titleImpact of Selective Mapping Strategies on Automated Laboratory Result Notification to Public Health Authoritiesen_US
dc.typeArticleen_US
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