Advancing Healthcare Practice and Education via Data Sharing: Demonstrating the Utility of Open Data by Training an Artificial Intelligence Model to Assess Cardiopulmonary Resuscitation Skills

Merryn D. Constable, Francis Xiatian Zhang, Tony Conner, Daniel Monk, Jason Rajsic, Claire Ford, Laura Jillian Park, Alan Platt, Debra Porteous, Lawrence Grierson and Hubert P. H. Shum
Advances in Health Sciences Education (AHSE), 2024

 Impact Factor: 3.0 Top 25% Journal in Education & Educational Research

Advancing Healthcare Practice and Education via Data Sharing: Demonstrating the Utility of Open Data by Training an Artificial Intelligence Model to Assess Cardiopulmonary Resuscitation Skills

Abstract

Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances – both good and bad - provides an opportunity for interdisciplinary research collaborations that can advance our understanding of movement that reflects technical expertise, support educational tool development, and facilitate assessment practices. In this paper we raise important ethical and legal considerations when building and sharing health professions education data. Collective data sharing may produce new knowledge and tools to support healthcare professional education. We demonstrate the utility of a data-sharing culture by providing and leveraging a database of cardio-pulmonary resuscitation (CPR) performances that vary in quality. The CPR skills performance database (collected for the purpose of this research, hosted at UK Data Service's ReShare Repository) contains videos from 40 participants recorded from 6 different angles, allowing for 3D reconstruction for movement analysis. The video footage is accompanied by quality ratings from 2 experts, participants' self-reported confidence and frequency of performing CPR, and the demographics of the participants. From this data, we present an Automatic Clinical Assessment tool for Basic Life Support that uses pose estimation to determine the spatial location of the participant's movements during CPR and a deep learning network that assesses the performance quality.


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Plain Text

Merryn D. Constable, Francis Xiatian Zhang, Tony Conner, Daniel Monk, Jason Rajsic, Claire Ford, Laura Jillian Park, Alan Platt, Debra Porteous, Lawrence Grierson and Hubert P. H. Shum, "Advancing Healthcare Practice and Education via Data Sharing: Demonstrating the Utility of Open Data by Training an Artificial Intelligence Model to Assess Cardiopulmonary Resuscitation Skills," Advances in Health Sciences Education, Springer, 2024.

BibTeX

@article{constable24advancing,
 author={Constable, Merryn D. and Zhang, Francis Xiatian and Conner, Tony and Monk, Daniel and Rajsic, Jason and Ford, Claire and Park, Laura Jillian and Platt, Alan and Porteous, Debra and Grierson, Lawrence and Shum, Hubert P. H.},
 journal={Advances in Health Sciences Education},
 title={Advancing Healthcare Practice and Education via Data Sharing: Demonstrating the Utility of Open Data by Training an Artificial Intelligence Model to Assess Cardiopulmonary Resuscitation Skills},
 year={2024},
 doi={10.1007/s10459-024-10369-5},
 issn={1573-1677},
 publisher={Springer},
}

RIS

TY  - JOUR
AU  - Constable, Merryn D.
AU  - Zhang, Francis Xiatian
AU  - Conner, Tony
AU  - Monk, Daniel
AU  - Rajsic, Jason
AU  - Ford, Claire
AU  - Park, Laura Jillian
AU  - Platt, Alan
AU  - Porteous, Debra
AU  - Grierson, Lawrence
AU  - Shum, Hubert P. H.
T2  - Advances in Health Sciences Education
TI  - Advancing Healthcare Practice and Education via Data Sharing: Demonstrating the Utility of Open Data by Training an Artificial Intelligence Model to Assess Cardiopulmonary Resuscitation Skills
PY  - 2024
DO  - 10.1007/s10459-024-10369-5
SN  - 1573-1677
PB  - Springer
ER  - 


Supporting Grants

Northumbria University
Pose Estimation for Health Professional Education: Development of an Objective Computerized Approach for Measuring and Assessing Technical Competencies in Nursing
Northumbria University Application Seed Funding Scheme (Ref: ): £16,428, Co-Applicant (PI: Dr Merryn D. Constable)
Received from Northumbria University, UK, 2022-2022
Project Page

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