Evidence map›Paper›PMID 27406187›Full record

ArticleJournal of biomedical semantics2016

The ontology of medically related social entities: recent developments.

Amanda Hicks, Josh Hanna, Daniel Welch, Mathias Brochhausen, William R Hogan

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Generation of Interactive Knowledge Graphs to Enable Research of the Effects of Trauma Center Organization on Patient Outcomes.Knowledge graphs and semantic web : 7th international conference, KGSWC 2025, Leipzig, Germany, November 26-28, 2025 : proceedings. KGSWC (Conference) (7th : 2025 : Leipzig, Germany) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Towards Healthy Aging through Semantic Enrichment.CEUR workshop proceedings. · 2025
    Article
  7. Article
  8. Article
  9. Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO).Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  10. Article
  11. CRENO: An ontology to model concepts relating to culture, race, ethnicity, and nationality for health data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Amanda HicksDepartment of Health Outcomes and Policy, University of Florida, Gainesville, FL, USA. aehicks@ufl.edu.
Josh HannaDepartment of Health Outcomes and Policy, University of Florida, Gainesville, FL, USA.
Daniel WelchDepartment of Health Outcomes and Policy, University of Florida, Gainesville, FL, USA.
Mathias BrochhausenDepartment of Biomedical Informatics, University of Arkansas for Medical Science, Little Rock, AR, USA.
William R HoganDepartment of Health Outcomes and Policy, University of Florida, Gainesville, FL, USA.

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
UF Clinical and Translational Science AwardUL1TR000064 · NCATS · UNIVERSITY OF FLORIDA · PI NELSON, DAVID R · 2012 to 2014
$12.2M
Arkansas Center for Clinical and Translational ResearchUL1TR000039 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI BECK, CORNELIA MARIE, JAMES, LAURA P · 2012 to 2014
$10.0M
Trauma Institutional Priorities and Teams for Outcome Efficacy (TIPTOE)R01GM111324 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI BROCHHAUSEN, MATHIAS, SEXTON, KEVIN WAYNE · 2015 to 2025
$3.1M
NCATS NIH HHS UL1 TR000039NCATS NIH HHS UL1 TR000064NCATS NIH HHS UL1 TR001427NIGMS NIH HHS R01 GM111324
6 · The paper itself

Abstract

backgroundThe Ontology of Medically Related Social Entities (OMRSE) was initially developed in 2011 to provide a framework for modeling demographic data in Resource Description Framework/Web Ontology Language. It is built upon the Basic Formal Ontology and conforms to Open Biomedical Ontologies Foundry's best practices. DESCRIPTION: We report recent development of OMRSE which includes representations of organizations, roles, facilities, demographic data, enrollment in insurance plans, and data about socio-economic indicators.

conclusionsOMRSE's coverage has been expanding in recent years to include a wide variety of classes and has been useful in several biomedical applications.

Indexed as

Biological OntologiesDemographyHealth FacilitiesHumansInsuranceMarital StatusSocioeconomic FactorsOMRSEOntologyOrganizationsSocial entitiesSocial roles

Identifiers

PMID27406187
PMCPMC4942889

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.