ArticleLaboratory medicine2015
Learning From the Crowd in Terminology Mapping: The LOINC Experience.
Article in Laboratory medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Influences on Emergency Clinician Use of Health Information Exchange: Interview Study.JMIR medical informatics · 2025Article
- Encoding laboratory testing data: case studies of the national implementation of HHS requirements and related standards in five laboratories.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Logical Observation Identifiers Names and Codes (LOINCDiagnostics (Basel, Switzerland) · 2021Article
- International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.NPJ digital medicine · 2020Article
- Interactive Machine Learning for Laboratory Data Integration.Studies in health technology and informatics · 2019Article
- Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.JMIR research protocols · 2016Article
- Learning from the crowd while mapping to LOINC.Journal of the American Medical Informatics Association : JAMIA · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
National policies in the United States require the use of standard terminology for data exchange between clinical information systems. However, most electronic health record systems continue to use local and idiosyncratic ways of representing clinical observations. To improve mappings between local terms and standard vocabularies, we sought to make existing mappings (wisdom) from healt care organizations (the Crowd) available to individuals engaged in mapping processes. We developed new functionality to display counts of local terms and organizations that had previously mapped to a given Logical Observation Identifiers Names and Codes (LOINC) code. Further, we enabled users to view the details of those mappings, including local term names and the organizations that create the mappings. Users also would have the capacity to contribute their local mappings to a shared mapping repository. In this article, we describe the new functionality and its availability to implementers who desire resources to make mapping more efficient and effective.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.