Evidence map›Paper›PMID 28637208›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2018

Unit conversions between LOINC codes.

Ronald G Hauser, Douglas B Quine, Alex Ryder, Sheldon Campbell

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Interactive Machine Learning for Laboratory Data Integration.Studies in health technology and informatics · 2019
    Article
  7. Article
  8. Response to Unit conversions between LOINC codes.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ronald G HauserVeterans Affairs Connecticut Healthcare, West Haven, CT, USA.
Douglas B QuineVeterans Affairs Connecticut Healthcare, West Haven, CT, USA.
Alex RyderChildren's Foundation Research Institute, Le Bonheur Children's Hospital, Memphis, TN, USA.
Sheldon CampbellVeterans Affairs Connecticut Healthcare, West Haven, CT, USA.

Funding

IMMUNOHEMATOLOGY/TRANSFUSION MEDICINE RESEARCH TRAININGT32HL007974 · NHLBI · YALE UNIVERSITY · PI JEANNE E HENDRICKSON, Diane S Krause · 2001 to 2026
$8.1M
NHLBI NIH HHS T32 HL007974
6 · The paper itself

Abstract

Logical Observation Identifiers Names and Codes (LOINC) is the most widely used controlled vocabulary to identify laboratory tests. A given laboratory test can often be reported in more than 1 unit of measure (eg, grams or moles), and LOINC defines unique codes for each unit. Consequently, an identical laboratory test performed by 2 different clinical laboratories may have different LOINC codes. The absence of unit conversions between compatible LOINC codes impedes data aggregation and analysis of laboratory results. To develop such conversions, a computational process was developed to review the LOINC standard for potential conversions, and multiple expert reviewers oversaw and finalized the conversion list. In all, 285 bidirectional conversions were identified, including conversions for routine clinical tests such as sodium, magnesium, and human immunodeficiency virus (HIV). Unit conversions were applied to the aggregation of laboratory test results to demonstrate their usefulness. Diverse informatics projects may benefit from the ability to interconvert compatible results.

Indexed as

Clinical Laboratory Information SystemsLogical Observation Identifiers Names and CodesMathematical ConceptsLaboratoriesclinical laboratory information systemscontrolled vocabularyLOINC

Identifiers

PMID28637208
PMCPMC6251580

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.