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Precision Workforce Management for Radiographers: Monitoring and Managing Competences with an Automatic Tool.

Andrea Lastrucci¹, Yannick Wandael¹, Giovanni Orlandi¹

¹Department of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.

Journal of Personalized Medicine

|July 27, 2024

Summary

This summary is machine-generated.

This study introduces the Skills Retention Monitoring (SRH) tool to optimize radiographer work shifts, improving skill monitoring and resource allocation in healthcare. The SRH tool enhances organizational performance and supports personalized medicine through competency-based insights.

Keywords:

competence monitoring performance radiographer skill workload

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Area of Science:

Healthcare Management
Health Informatics
Organizational Psychology

Background:

Optimizing healthcare work shifts is essential for service quality and professional growth.
Skill-oriented shift optimization is an emerging area in healthcare management.
Radiographers face unique challenges in workload management and skill utilization.

Purpose of the Study:

To introduce and evaluate the Skills Retention Monitoring (SRH) tool for optimizing radiographer work shifts.
To enhance skill monitoring, workload management, and organizational performance in healthcare settings.
To explore the potential for personalized medicine through competency-data integration.

Main Methods:

Development and preliminary deployment of the SRH tool, a resource-efficient solution.
Utilizing a Computer-Assisted Web Interviewing (CAWI) tool for pre-release feedback.
Implementing a continuous quality improvement approach with a maintenance and monitoring plan.
Developing a transfer plan involving professional associations for profession-specific customization.

Main Results:

The SRH tool demonstrated effectiveness in optimizing work based on competency monitoring for radiographers.
The tool generates weekly reports, streamlining activity management and resource allocation.
The SRH tool provides actionable insights for organizational context and supports tailored medicine through data integration.

Conclusions:

The SRH tool offers a viable solution for skill-oriented work shift optimization in healthcare.
Effective implementation requires maintenance, monitoring, and profession-specific customization.
Future integration with AI and broader deployment could further advance healthcare efficiency and personalized patient care.