Evidence map›Paper›PMID 18693939›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2007

Assessing data relevance for automated generation of a clinical summary.

Tielman T Van Vleck, Daniel M Stein, Peter D Stetson, Stephen B Johnson

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Generalized Extraction and Classification of Span-Level Clinical Phrases.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Article
  8. Observational
  9. Automatic Generation of Conditional Diagnostic Guidelines.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  10. Article
  11. Article
  12. A qualitative analysis of EHR clinical document synthesis by clinicians.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012
    Article
  13. Review
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

4 authors.

Tielman T Van VleckDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Daniel M Stein
Peter D Stetson
Stephen B Johnson

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
A Biomedical Natural Language Processing ResourceR01LM008635 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2005 to 2008
$2.1M
Automated Detection of Medical ErrorsK22LM008805 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STETSON, PETER D · 2005 to 2007
$405k
NLM NIH HHS K22 LM008805NLM NIH HHS K22-LM008805NLM NIH HHS N01-LM07079NLM NIH HHS R01 LM008635NLM NIH HHS R01-LM008635NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Clinicians perform many tasks in their daily work requiring summarization of clinical data. However, as technology makes more data available, the challenges of data overload become ever more significant. As interoperable data exchange between hospitals becomes more common, there is an increased need for tools to summarize information. Our goal is to develop automated tools to aid clinical data summarization. Structured interviews were conducted on physicians to identify information from an electronic health record they considered relevant to explaining the patients medical history. Desirable data types were systematically evaluated using qualitative and quantitative analysis to assess data categories and patterns of data use. We report here on the implications of these results for the design of automated tools for summarization of patient history.

Indexed as

Attitude of Health PersonnelMedical Records Systems, ComputerizedDocumentationElectronic Data ProcessingHumansInterviews as TopicMedical Record Linkage

Identifiers

PMID18693939
PMCPMC2655814

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.