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Updated: May 22, 2026
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Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
State population as a predictor of radiation therapy staffing levels
John Culbertson1, Kira Carbonneau, Myke Kudlas
1American Society of Radiologic Technologists, Albuquerque, NM, USA. jculbertson@asrt.org
Summary
State population accurately predicts radiation therapy staffing needs. Monitoring population changes can help healthcare professionals manage cycles of radiation therapist shortages and oversupplies.
Area of Science:
- Healthcare workforce analysis
- Population studies
- Radiation oncology workforce planning
Background:
- Radiation therapy staffing historically experiences cyclical shortages and oversupplies.
- Accurate personnel demand prediction is crucial for workforce stability.
Purpose of the Study:
- To identify reliable predictors for radiation therapy staffing levels.
- To establish state population as a key factor in forecasting radiation therapist demand.
Main Methods:
- Linear regression analysis was employed.
- Data spanned from 2002 to 2010, correlating state population with staffing levels.
Main Results:
- State population significantly predicts radiation therapist numbers.
- 89.5% to 91.4% of the variance in staffing levels was explained by population from 2002-2010.
Conclusions:
- State population serves as a strong predictor for radiation therapy workforce planning.
- Monitoring population trends enables proactive management of staffing cycles.
- Future research can refine demand estimation models for radiation therapists.
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