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Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

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Using Clinical Data Visualizations in Electronic Health Record User Interfaces to Enhance Medical Student Diagnostic

Lucille Cheng¹, Yalini Senathirajah²

¹School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.

JMIR Human Factors

|April 13, 2023

Summary

This study shows that medical students can learn faster, intuitive "System 1" diagnostic reasoning using novel electronic health record (EHR) interfaces with data visualizations. This approach may reduce cognitive load and improve medical education.

Keywords:

EHR System-1–type diagnostic reasoning clinical reasoning cognitive burden cognitive load data visualization diagnosis diagnostic electronic health record hGraph heuristics medical education medical school medical student reasoning process type-1 reasoning user design user interface

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Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Area of Science:

Medical Education
Cognitive Science
Human-Computer Interaction

Background:

Dual-process theory describes medical decision-making as intuitive System 1 (experienced physicians) and deliberative System 2 (students).
System 1 reasoning is less cognitively demanding and may reduce physician error.
Limited research exists on inducing System 1 diagnosis in students via cognitive heuristics, especially with electronic health record (EHR) interfaces.

Purpose of the Study:

To induce System 1 diagnostic reasoning in medical students using cognitive user interface heuristics.
To assess the impact of clinical data visualizations on cognitive load and medical education.

Main Methods:

Third- and fourth-year medical students diagnosed 8 patient cases using a novel EHR with data visualization.
Group A reviewed 4 cases repeatedly (up to 4 times, 30s/case); Group B reviewed cases twice (2 min/case).
User experience interviews were conducted for qualitative analysis.

Main Results:

Group A scored higher (76%) than Group B (69%) and diagnosed cases 50% faster.
73% of participants rated the new EHR favorably compared to previous versions.
73% of participants reported using pattern-recognition strategies consistent with System 1 decision-making.

Conclusions:

Inducing System 1 diagnostics in learners is feasible.
Data visualization and user design heuristics can potentially reduce cognitive burden in clinical settings.
Innovations in clinical data presentation are needed for medical education.