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Interventional Diagnostic Procedure: A Practical Guide for the Assessment of Coronary Vascular Function

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Using Feedback Intervention Theory to Guide Clinical Dashboard Design.

Dawn Dowding¹, Jacqueline Merrill², David Russell³

¹The University of Manchester, Manchester, UK.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|March 1, 2019

Summary

This summary is machine-generated.

Clinical dashboards provide feedback to improve care quality. This study used Feedback Intervention Theory (FIT) to design an effective dashboard for home care nurses, enhancing clinician behavior and patient outcomes.

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Area of Science:

Health Informatics
Human-Computer Interaction
Quality Improvement

Background:

Feedback on care quality can influence clinician and organizational behavior, potentially improving patient care.
Clinical dashboards utilize data visualization to present performance metrics and facilitate feedback.
Existing dashboard designs may not adequately consider user comprehension of visualized data.

Purpose of the Study:

To outline a theoretical approach for designing clinical dashboards based on Feedback Intervention Theory (FIT).
To identify key feedback priorities for home care nurses through focus groups.
To evaluate the usability of a prototype dashboard informed by theoretical design and user input.

Main Methods:

Focus groups with 61 home care nurses to determine feedback priorities.
An online survey to assess graph literacy, numeracy, and data comprehension among nurses.
Development and usability evaluation of a prototype clinical dashboard with home care nurses.

Main Results:

Feedback Intervention Theory (FIT) provided a theoretical framework for dashboard design.
Focus groups and surveys informed the selection of feedback content and design elements.
The prototype dashboard underwent usability testing with home care nurses.

Conclusions:

A theoretically grounded approach, like FIT, is crucial for designing effective clinical dashboards.
Understanding user characteristics, such as graph literacy, is essential for optimizing data visualization in dashboards.
The developed prototype demonstrated potential for positively impacting clinician behavior and improving care quality.