Repurposing a machine QA platform for medical physics residency management

Area of Science:

• Medical Physics Education
• Residency Program Management
• Health Informatics

Background:

• Medical physics residency programs face challenges with organizing rotation files, documenting activities, and tracking resident progress.
• Current standards from the Commission on Accreditation of Medical Physics Educational Programs (CAMPEP) necessitate robust systems for training schedules, objectives, and evaluations.
• Existing methods using static documents or multiple platforms lead to administrative burdens and version-control issues.

Purpose of the Study:

• To describe the adaptation of RadMachine, a machine quality assurance (QA) platform, for managing medical physics residency programs.
• To evaluate its utility in organizing rotations, tracking activities, and managing competency sign-offs.

Main Methods:

• A framework was developed within RadMachine, configuring residents as virtual devices and using test lists for rotations and competencies.
• Tasks included learning objectives, practical assignments, reading, and supervisor sign-offs, with completion tracked via various methods.
• Qualitative comparison was made between the new RadMachine-based workflow and prior Microsoft Word-based systems.

Main Results:

• The RadMachine framework converted static documents into dynamic, trackable lists, improving version control and reducing administrative effort.
• Transparency was enhanced, with real-time access for residents to their progress and for faculty to review trainee development.
• Updates were simplified, and access to the most current curriculum was ensured.

Conclusions:

• Repurposing RadMachine offers a practical, scalable, and low-overhead solution for medical physics residency education and competency tracking.
• Leveraging existing, licensed QA software eliminates the need for additional procurement, licensing, or IT onboarding.
• This method presents an efficient alternative to traditional document-based systems with potential for future expansion.