Evidence map›Paper›PMID 33084580›Full record

ArticleJMIR human factors2020

Characterizing and Visualizing Display and Task Fragmentation in the Electronic Health Record: Mixed Methods Design.

Yalini Senathirajah, David R Kaufman, Kenrick D Cato, Elizabeth M Borycki, Jaime Allen Fawcett, Andre W Kushniruk

Abstract read
In one paragraph

Article in JMIR human factors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
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  7. Generative AI Demonstrated Difficulty Reasoning on Nursing Flowsheet Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
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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

6 authors.

Yalini SenathirajahDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0001-8399-989X
David R KaufmanMedical Informatics Program, School of Health Professions, State University of New York - Downstate Health Sciences University, Brooklyn, NY, United States.ORCID https://orcid.org/0000-0001-9968-9968
Kenrick D CatoSchool of Nursing, Columbia University, New York, NY, United States.ORCID https://orcid.org/0000-0002-0704-3826
Elizabeth M BoryckiSchool of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID https://orcid.org/0000-0003-0928-8867
Jaime Allen FawcettDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0003-1173-2621
Andre W KushnirukSchool of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID https://orcid.org/0000-0002-2557-9288

Funding

Finding the safer way: Novel interaction design approaches to Health IT safetyR01HS023708 · AHRQ · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SENATHIRAJAH, YALINI · 2015 to 2018
$966k
AHRQ HHS R01 HS023708
6 · The paper itself

Abstract

backgroundThe complexity of health care data and workflow presents challenges to the study of usability in electronic health records (EHRs). Display fragmentation refers to the distribution of relevant data across different screens or otherwise far apart, requiring complex navigation for the user's workflow. Task and information fragmentation also contribute to cognitive burden.

objectiveThis study aims to define and analyze some of the main sources of fragmentation in EHR user interfaces (UIs); discuss relevant theoretical, historical, and practical considerations; and use granular microanalytic methods and visualization techniques to help us understand the nature of fragmentation and opportunities for EHR optimization or redesign.

methodsSunburst visualizations capture the EHR navigation structure, showing levels and sublevels of the navigation tree, allowing calculation of a new measure, the Display Fragmentation Index. Time belt visualizations present the sequences of subtasks and allow calculation of proportion per instance, a measure that quantifies task fragmentation. These measures can be used separately or in conjunction to compare EHRs as well as tasks and subtasks in workflows and identify opportunities for reductions in steps and fragmentation. We present an example use of the methods for comparison of 2 different EHR interfaces (commercial and composable) in which subjects apprehend the same patient case.

resultsScreen transitions were substantially reduced for the composable interface (from 43 to 14), whereas clicks (including scrolling) remained similar.

conclusionsThese methods can aid in our understanding of UI needs under complex conditions and tasks to optimize EHR workflows and redesign.

Indexed as

data visualizationelectronic health recordelectronic medical recordinformation technologymedical informaticsuser computer interface

Identifiers

PMID33084580
PMCPMC7641790

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.