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User-Based Evaluation of a Data-Driven Medical Education Platform.
Dimitrios Zikos1, Cassie E Sprague1
1Central Michigan University.
Studies in Health Technology and Informatics
|January 22, 2022
Summary
TrainCoMorb, an online platform for medical training, received positive user feedback for its ability to help users recognize comorbidities and their risks. Familiarity with simulation systems and data-driven education positively influenced user ratings of the platform's usefulness and features.
Area of Science:
- Medical Education
- Health Informatics
- Clinical Decision Support
Background:
- Online training platforms are increasingly vital for medical education.
- Recognizing comorbidities and their impact on patient outcomes is a critical skill for physicians.
- Data-driven educational tools offer potential for enhanced learning experiences.
Purpose of the Study:
- To evaluate the TrainCoMorb online platform's usability and perceived value among medical residents.
- To assess the association between user characteristics (age, simulation experience, views on data-driven education) and platform evaluations.
- To determine the platform's suitability as a supplementary educational tool for future physicians.
Main Methods:
- A cross-sectional study involving 18 medical residents.
- Participants engaged in scenario-based evaluations using the TrainCoMorb platform.
- An online survey was administered to collect data on platform dimensions (navigation, usefulness, validity, features) and user background.
Main Results:
- Residents rated the platform's four dimensions highly, with scores ranging from 3.77 to 4.15 on a 5-point scale.
- Positive attitudes towards data-driven medical education were prevalent among participants.
- Greater experience with clinical simulation systems and positive views on data-driven education correlated with higher ratings for usefulness, validity, and features.
Conclusions:
- The TrainCoMorb platform demonstrates positive user-based feedback, indicating its potential as an effective supplementary educational tool.
- The platform effectively supports the practice of recognizing comorbidities and their attributable risks.
- User experience and perception of data-driven education are key factors influencing the evaluation of such training tools.
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