ArticleApplied clinical informatics2020
User-Centered Clinical Display Design Issues for Inpatient Providers.
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.
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.
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.
Who cites it
6 citing papers in PubMed.
- Why do probabilistic clinical models fail to transport between sites.NPJ digital medicine · 2024Review
- Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians.Applied clinical informatics · 2024Article
- Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, and Beyond.Critical care clinics · 2022Review
- Evaluating Electronic Health Record Limitations and Time Expenditure in a German Medical Center.Applied clinical informatics · 2021Article
- Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities.Yearbook of medical informatics · 2021Review
- A Perioperative Care Display for Understanding High Acuity Patients.Applied clinical informatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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
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What Socratic holds
Registered trials
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.