Evidence map›Paper›PMID 21031148›Full record

ArticleApplied clinical informatics2010

Generating Clinical Notes for Electronic Health Record Systems.

S Trent Rosenbloom, William W Stead, Joshua C Denny, Dario Giuse, Nancy M Lorenzi, Steven H Brown, Kevin B Johnson

Abstract read
In one paragraph

Article in Applied clinical informatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Clinical Documentation as End-User Programming.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. Electronic health records improve clinical note quality.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  12. Secondary use of clinical data: the Vanderbilt approach.Journal of biomedical informatics · 2014
    Article
  13. Article
  14. Article
  15. Article
  16. Implementing an interface terminology for structured clinical documentation.Journal of the American Medical Informatics Association : JAMIA · 2013
    Article
  17. Article
  18. The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.Journal of the American Medical Informatics Association : JAMIA · 2013
    Article
  19. Article
  20. 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

7 authors.

S Trent RosenbloomDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
William W Stead
Joshua C Denny
Dario Giuse
Nancy M Lorenzi
Steven H Brown
Kevin B Johnson

Funding

A Framework Based Clinical Documentation Evaluation MethodR01LM009591 · NLM · VANDERBILT UNIVERSITY · PI ROSENBLOOM, S TRENT · 2008 to 2010
$914k
NLM NIH HHS R01 LM009591
6 · The paper itself

Abstract

Clinical notes summarize interactions that occur between patients and healthcare providers. With adoption of electronic health record (EHR) and computer-based documentation (CBD) systems, there is a growing emphasis on structuring clinical notes to support reusing data for subsequent tasks. However, clinical documentation remains one of the most challenging areas for EHR system development and adoption. The current manuscript describes the Vanderbilt experience with implementing clinical documentation with an EHR system. Based on their experience rolling out an EHR system that supports multiple methods for clinical documentation, the authors recommend that documentation method selection be made on the basis of clinical workflow, note content standards and usability considerations, rather than on a theoretical need for structured data.

Identifiers

PMID21031148
PMCPMC2963994

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Registered trials

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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.