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DrKnow: A Diagnostic Learning Tool with Feedback from Automated Clinical Decision Support.
Piyapong Khumrin1,2, Anna Ryan3, Terry Juddy3
1School of Computing and Information Systems, Melbourne School of Engineering, University of Melbourne, Australia.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|March 1, 2019
Summary
DrKnow, a web-based tool, uses virtual cases and clinical decision support systems (CDSS) to enhance medical students' diagnostic reasoning. It provides personalized feedback to improve problem-solving and decision-making skills.
Area of Science:
- Medical Education
- Health Informatics
- Diagnostic Reasoning
Background:
- Effective feedback is crucial for developing diagnostic reasoning skills in medical trainees.
- Traditional bedside teaching faces resource challenges.
- Technology can supplement traditional medical education methods.
Purpose of the Study:
- To present the design of DrKnow, a web-based learning application.
- To support the development of problem-solving and decision-making skills in medical students using virtual cases and a CDSS.
- To argue that a task-sensitive CDSS approach can improve student learning outcomes and overcome resource limitations.
Main Methods:
- DrKnow utilizes virtual cases and a clinical decision support system (CDSS).
- The application provides personalized feedback based on students' information requests and prioritization.
- Feedback is delivered at key decision points to aid in developing differential and provisional diagnoses.
Main Results:
- DrKnow offers personalized feedback to guide students through virtual diagnostic cases.
- Upon final diagnosis, students receive performance feedback and recommendations.
- The system aims to enhance diagnostic performance and learning outcomes.
Conclusions:
- Designing learning applications around task-sensitive CDSS is a suitable approach for medical education.
- DrKnow facilitates the development of diagnostic reasoning skills in medical students.
- This approach can overcome resource challenges associated with expert-led clinical teaching.
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