Evidence map›Paper›PMID 33086396›Full record

ArticleApplied clinical informatics2020

User-Centered Clinical Display Design Issues for Inpatient Providers.

Thomas A Lasko, David A Owens, Daniel Fabbri, Jonathan P Wanderer, Julian Z Genkins, Laurie L Novak

Abstract read
In one paragraph

Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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.

Thomas A LaskoDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.ORCID 0000-0003-2300-9529
David A OwensOwen Graduate School of Management, Vanderbilt University, Nashville, Tennessee, United States.
Daniel FabbriDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Jonathan P WandererDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Julian Z GenkinsDepartment of Medicine, University of California, San Francisco, San Francisco, California, United States.
Laurie L NovakDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Funding

Identification, Extraction and Display of Clinical Data Patterns with Application to Anesthesia WorkflowsR01EB020666 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LASKO, THOMAS · 2016 to 2018
$1.2M
NIBIB NIH HHS R01 EB020666
6 · The paper itself

Abstract

backgroundSuboptimal information display in electronic health records (EHRs) is a notorious pain point for users. Designing an effective display is difficult, due in part to the complex and varied nature of clinical practice.

objectiveThis article aims to understand the goals, constraints, frustrations, and mental models of inpatient medical providers when accessing EHR data, to better inform the display of clinical information.

methodsA multidisciplinary ethnographic study of inpatient medical providers.

resultsOur participants' primary goal was usually to assemble a clinical picture around a given question, under the constraints of time pressure and incomplete information. To do so, they tend to use a mental model of multiple layers of abstraction when thinking of patients and disease; they prefer immediate pattern recognition strategies for answering clinical questions, with breadth-first or depth-first search strategies used subsequently if needed; and they are sensitive to data relevance, completeness, and reliability when reading a record.

conclusionThese results conflict with the ubiquitous display design practice of separating data by type (test results, medications, notes, etc.), a mismatch that is known to encumber efficient mental processing by increasing both navigation burden and memory demands on users. A popular and obvious solution is to select or filter the data to display exactly what is presumed to be relevant to the clinical question, but this solution is both brittle and mistrusted by users. A less brittle approach that is more aligned with our users' mental model could use abstraction to summarize details instead of filtering to hide data. An abstraction-based approach could allow clinicians to more easily assemble a clinical picture, to use immediate pattern recognition strategies, and to adjust the level of displayed detail to their particular needs. It could also help the user notice unanticipated patterns and to fluidly shift attention as understanding evolves.

Indexed as

Electronic Health RecordsInpatientsHumansReproducibility of ResultsUser-Centered Design

Identifiers

PMID33086396
PMCPMC7595798

What Socratic 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 Socratic graph.