Evidence map›Paper›PMID 41535720›Full record

ArticleNPJ digital medicine2026

When better data meets better design: How EHR data usability and system usability shape physicians' cognitive load.

Curtis A Merriweather, Kalle Lyytinen, David Aron, Michael R Cauley

Abstract read
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors.

Curtis A MerriweatherFuqua School of Business, Duke University, Durham, NC, USA. curtis.merriweather@duke.edu.
Kalle LyytinenWeatherhead School of Management, Case Western Reserve University, Cleveland, OH, USA.
David AronWeatherhead School of Management, Case Western Reserve University, Cleveland, OH, USA.
Michael R CauleyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic health record (EHR) systems were designed to enhance clinical decision-making, yet the way data is organized and displayed can create significant cognitive demands for physicians. This study examines how EHR data usability (data quality, data completeness, and data-driven use) and system usability jointly shape physicians' cognitive load. Using survey responses from 564 physicians across 32 specialties, we tested a mediated model with covariance-based structural equation modeling. Reliability and validity were assessed through standard psychometric criteria. Findings show that stronger data usability increases germane cognitive load, promoting deeper engagement with clinically meaningful information. In contrast, higher system usability reduces extraneous cognitive load by aligning interface design with clinical workflow and minimizing navigation-related effort. Information overload partially mediated these effects, suggesting that better data usability helps physicians better filter irrelevant data and stay focused on diagnostically relevant cues. Overall, the results highlight two levers for improving cognitive performance: enhancing system usability lowers unnecessary cognitive effort and documentation-related errors, while improving data usability supports reasoning-intensive diagnostic work. Optimizing both fosters balanced cognitive load and more sustainable, error-resilient clinical decision-making.

Identifiers

PMID41535720
PMCPMC12864774

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.