Evidence map›Paper›PMID 30060091›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2018

Patient information organization in the intensive care setting: expert knowledge elicitation with card sorting methods.

Thomas Reese, Noa Segall, Paige Nesbitt, Guilherme Del Fiol, Rosalie Waller, Brekk C Macpherson, Joseph E Tonna, Melanie C Wright

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. Impact of integrated graphical display on expert and novice diagnostic performance in critical care.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  7. Article
  8. 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

8 authors.

Thomas ReeseDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Noa SegallDepartment of Anesthesiology, Duke University Medical Center, Durham, NC, USA.
Paige NesbittTrinity Health and Saint Alphonsus Regional Medical Center, Boise, ID, USA.
Guilherme Del FiolDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Rosalie WallerDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Brekk C MacphersonSchool of Nursing, Virginia Commonwealth University, Richmond, VA, USA.
Joseph E TonnaDepartment of Surgery, University of Utah School of Medicine, Salt Lake City, UT, USA.
Melanie C WrightTrinity Health and Saint Alphonsus Regional Medical Center, Boise, ID, USA.

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
Right Place, Right Time: Information Design to Support Decisions in Acute CareR56LM011925 · NLM · SAINT ALPHONSUS REGIONAL MEDICAL CENTER · PI WRIGHT, MELANIE C · 2015 to 2016
$544k
NLM NIH HHS R56 LM011925NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Introduction: Many electronic health records fail to support information uptake because they impose low-level information organization tasks on users. Clinical concept-oriented views have shown information processing improvements, but the specifics of this organization for critical care are unclear. Objective: To determine high-level cognitive processes and patient information organization schema in critical care. Methods: We conducted an open card sort of 29 patient data elements and a modified Delphi card sort of 65 patient data elements. Study participants were 39 clinicians with varied critical care training and experience. We analyzed the open sort with a hierarchical cluster analysis (HCA) and factor analysis (FA). The Delphi sort was split into three initiating groups that resulted in three unique solutions. We compared results between open sort analyses (HCA and FA), between card sorting exercises (open and Delphi), and across the Delphi solutions. Results: Between the HCA and FA, we observed common constructs including cardiovascular and hemodynamics, infectious disease, medications, neurology, patient overview, respiratory, and vital signs. The more comprehensive Delphi sort solutions also included gastrointestinal, renal, and imaging constructs. Conclusions: We identified primarily system-based groupings (e.g., cardiovascular, respiratory). Source-based (e.g., medications, laboratory) groups became apparent when participants were asked to sort a longer list of concepts. These results suggest a hybrid approach to information organization, which may combine systems, source, or problem-based groupings, best supports clinicians' mental models. These results can contribute to the design of information displays to better support clinicians' access and interpretation of information for critical care decisions.

Indexed as

Critical CareData DisplayElectronic Health RecordsNeuropsychological TestsUser-Computer InterfaceCluster AnalysisDelphi TechniqueHumansMedical Informatics Applications

Identifiers

PMID30060091
PMCPMC6077790

What OpenQuestion holds

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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.