Evidence map›Paper›PMID 29888079›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2018

Evaluation of Flowsheet Documentation in the Electronic Health Record for Residence, Living Situation, and Living Conditions.

Tamara J Winden, Elizabeth S Chen, Karen A Monsen, Yan Wang, Genevieve B Melton

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Extracting Patient-level Social Determinants of Health into the OMOP Common Data Model.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021
    Article
  14. Article
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.

Tamara J WindenInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.
Elizabeth S ChenCenter for Biomedical Informatics, Brown University, Providence, RI.
Karen A MonsenSchool of Nursing, University of Minnesota, Minneapolis, MN.
Yan WangInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.
Genevieve B MeltonInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.

Funding

Tracking and Evaluation CoreU54GM115677 · NIGMS · BROWN UNIVERSITY · PI ROUNDS, SHARON IRENE SMITH · 2016 to 2025
$45.0M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
Leveraging the EHR to Collect and Analyze Social, Behavioral & Familial FactorsR01LM011364 · NLM · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CHEN, ELIZABETH S., MELTON-MEAUX, GENEVIEVE B · 2012 to 2015
$1.4M
NCATS NIH HHS UL1 TR000114NIGMS NIH HHS U54 GM115677NLM NIH HHS R01 LM011364
6 · The paper itself

Abstract

Social determinants of health (SDOH) are important considerations in diagnosis, prevention, and health outcomes. However, they are often not well documented in the EHR and found primarily in unstructured or semi-structured text. Building upon previous work, we analyzed all flowsheet data in 2013 for information related to the SDOH topic areas of Residence, Living Situation, and Living Conditions. Overall, 91 rows were identified as being related to the topics areas resulting in 604,616 unique observations. Individual rows contained SDOH data often covered multiple concepts especially free-text entries. These data included most often references to the residence, residence details, and with whom the patient lives. Very few contained living condition references. Additionally, there was significant duplication and inconsistency of row labels, as well as variation in value list content for rows collecting the same concepts. Our findings demonstrate significant opportunities to improve and achieve better standardization in documentation around these SDOH.

Identifiers

PMID29888079
PMCPMC5961798

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.