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Activity-Based Staffing Models for Diagnostic Imaging Medical Physics Workforce: A Case Study

Abstract
Purpose

Accurate estimation of diagnostic imaging medical physics staffing requirements remains challenging as clinical scope, regulatory burden, and academic expectations expand. Although multiple activity-based staffing models are commonly cited for workforce planning and justification, many have not been updated in years and are rarely evaluated side by side using identical institutional inputs. This work reviews international diagnostic imaging medical physics staffing frameworks and applies them to a single large academic medical center to quantify variability in estimated workforce requirements and assess implications for contemporary workforce planning.

Methods

Major international and professional staffing models were identified, including AAPM Report 33, IAEA Human Health Report No.15, European Commission Radiation Protection No.174, EFOMP Policy Statement No.7.1, and the ACPSEM Diagnostic Imaging Medical Physics workforce calculator. Local practice was evaluated by mapping core equipment, patient care, safety, service, training, and academic activities to each framework according to published model definitions. Staffing estimates were calculated from each model without modification or inclusion of ambiguous activities. Resulting full-time equivalent (FTE) requirements were compared across models.

Results

Substantial variation in estimated staffing requirements was observed across models, with FTE estimates ranging from 8.8 to 12.5. Models focused primarily on clinical service delivery and regulatory compliance produced lower estimates (AAPM:8.9; IAEA:8.8), whereas models incorporating teaching and academic responsibilities yielded higher requirements (EC 174:10.3; ACPSEM:9.88; EFOMP:12.5). Differences were driven predominantly by the treatment of academic and educational effort rather than regulatory or administrative workload, which was consistent across models.

Conclusion

Existing diagnostic imaging medical physics staffing models can yield different workforce estimates when applied to the same institution. This side-by-side comparison underscores the importance of transparent assumptions and highlights limitations of older, clinically focused models for contemporary workforce justification. The findings support the need for updated or harmonized staffing frameworks that reflect current diagnostic imaging medical physics practice.

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