Radiotherapy infrastructure and human resources in Switzerland: Present status and projected computations for 2020

Using national data to model the New Zealand radiation oncology workforce

Introduction

Demand for radiation therapy is expected to increase over time. In Aotearoa/New Zealand, the radiation oncology workforce experiences high numbers of clinical hours but an intervention rate that is lower than in comparable countries, suggesting unmet treatment need. Accurate models on the supply and demand for radiation oncologists (ROs) are needed to ensure adequate staffing levels.

Methods

We developed a demand model that predicted the future number of ROs required, using national data from the Radiation Oncology Collection (ROC) and a survey of ROs. Radiation therapy intervention and retreatment rates (IR/RTRs), and benign and non‐cancer conditions being treated, were derived from the ROC and applied to Census population projections. Survey data provided definitions of treatment by complexity, time spent in different activities and time available for work. Results were linked to radiation oncology workforce forecasts from a supply model developed by the Ministry of Health.

Results

The demand model showed that 85 ROs would be needed in 2031, if current IR/RTRs were maintained, an increase from 68 in 2021. The supply model predicted a decrease in ROs over time, leaving a significant shortfall. Model parameters could be modified to assess the impact of workforce or practice changes; more ROs would be needed if average working hours reduced or IR/RTRs increased.

Conclusion

Workforce models based on robust data collections are an important tool for workforce planning. The RO demand model presented here combines detailed information on treatment and work activities to provide credible estimates that can be used to inform actions on training, recruitment and retention.

Staffing Levels and Workload for Radiation Therapists in Canada

PURPOSE

The safe delivery of radiation therapy is dependent in part on the provision and organization of oncology professionals. General recommendations for staffing of radiation oncologists, medical physicists, and radiation therapists have been published, but most of these provide little detail, especially in the case of radiation therapists (RTs). In Canada, there are no guidelines or national standards for the staffing of RTs, and there is a paucity of Canadian data on the existing staffing levels of RTs and the models used to establish these levels. This project sought to identify and compare the staffing models used for Canadian RTs, and the staffing levels and workload resulting from these models.

METHODS AND MATERIALS

In January 2016, a survey was sent to managers of the 46 radiation treatment centres in Canada. This survey sought information on a range of staffing and practice variables for the fiscal year 2014/2015. Respondents were requested to provide the staffing model used for RTs at each centre and enough additional information to calculate the staffing levels and workload resulting from their staffing model. The survey included further variables that had the potential to influence staffing levels and workload, and centres were compared to establish if these variables did indeed impact staffing.

RESULTS

Of the 46 centres contacted, 37 centres responded, representing an 80.4% response rate. Survey results showed there are a variety of ways used to determine staffing across the country. Twenty of the 37 responding centres include some type of workload measurement in their staffing model, whereas 17 centres base staffing solely on historic levels or operating funds. There is a great deal of variation in the staffing levels and workload of RTs in Canada, with staff at some centres planning and treating twice the number of patients as RTs at other centres. Radiation therapist staffing levels at most radiation treatment centres in Canada are below the level recommended in recent publications. Differences in staffing levels or workload could not be accounted for by treatment complexity, number of specialty programs, use of relief staff, or number of RTs working in specialty nontreatment roles.

CONCLUSIONS

A high degree of variability in staffing levels and workload exists for RTs in Canada, which is not explained by differences in patterns of practice. It is likely that workload for RTs exceed safe levels at some Canadian centres. It is recommended that treatment centres use an up-to-date staffing model for RTs and continue to review staffing levels at regular intervals.

Health services research in German radiation oncology: new opportunities to advance cancer care

BACKGROUND

Health services research (HSR) is of increasing relevance to scientists, health-care providers, and clinicians. Complex population-based secondary data are a key source of information for analyses of health-care effects in radiation oncology.

METHODS

In this short paper, we examine potential applications of secondary data focusing on statistics from the diagnosis-related groups (DRG). This data set incorporating all hospitalized cases in Germany is based on claims of reimbursements and is provided by the Research Data Centers (RDC) of the Federal Statistical Office and the Statistical Offices of the federal states. A short outlook regarding other data sources is also presented.

RESULTS

In radiation oncology, secondary data such as the DRG statistics have rarely been used to examine health-care effects, despite their great potential for reporting effects in a broad population-based setting. Furthermore, for most data sources, the application to use these data is accessible with minor effort. However, data concerning outpatient care are difficult to analyze on a comparable level.

CONCLUSION

DRG statistics and related secondary data provide a remarkable source of information for analyses of health-care-related effects in radiation oncology.

Equipment, staffing, and provision of radiotherapy in Lombardy, Italy: Results of three surveys performed between 2012 and 2016

INTRODUCTION:

Several efforts are being implemented at the European level to measure provision of up-to-date radiation treatments across the continent.

METHODS:

A snapshot survey involving all radiation oncology centers within Lombardy, Italy, was performed in 2012 and repeated in 2014 and 2016, in cooperation with regional governmental officers. Centers were asked to provide detailed information concerning all individual patients being treated on the index day, and to report data on available local resources.

RESULTS:

We observed an increase in the number of centers and of megavoltage units (MVU) (from 76 to 87, i.e., 8.7 MVU per million inhabitants in 2016). Mean number of MVU per center was 2.5. Average age of MVU increased from 5.3 to 7.5 years and patients on the waiting list also increased. Conformal 3D radiotherapy (RT) treatments decreased from 56% to 42% and were progressively replaced by intensity-modulated RT treatments (from 39% to 49%). Waiting times were overall satisfactory. Radiation oncologists treated on average 152 and radiation therapists 100 RT courses per year. Average reimbursement per course was €4,879 (range €2,476-€8,014).

CONCLUSIONS:

The methodology of snapshot survey proved feasible and provided valuable information about radiation oncology provision and accessibility in Lombardy.

ÖGRO survey on radiotherapy capacity in Austria : Status quo and estimation of future demands

BACKGROUND

A comprehensive evaluation of the current national and regional radiotherapy capacity in Austria with an estimation of demands for 2020 and 2030 was performed by the Austrian Society for Radiation Oncology, Radiobiology and Medical Radiophysics (ÖGRO).

MATERIALS AND METHODS

All Austrian centers provided data on the number of megavoltage (MV) units, treatment series, fractions, percentage of retreatments and complex treatment techniques as well as the daily operating hours for the year 2014. In addition, waiting times until the beginning of radiotherapy were prospectively recorded over the first quarter of 2015. National and international epidemiological prediction data were used to estimate future demands.

RESULTS

For a population of 8.51 million, 43 MV units were at disposal. In 14 radiooncological centers, a total of 19,940 series with a mean number of 464 patients per MV unit/year and a mean fraction number of 20 (range 16-24) per case were recorded. The average re-irradiation ratio was 14%. The survey on waiting times until start of treatment showed provision shortages in 40% of centers with a mean waiting time of 13.6 days (range 0.5-29.3 days) and a mean maximum waiting time of 98.2 days. Of all centers, 21% had no or only a limited ability to deliver complex treatment techniques. Predictions for 2020 and 2030 indicate an increased need in the overall number of MV units to a total of 63 and 71, respectively.

CONCLUSION

This ÖGRO survey revealed major regional differences in radiooncological capacity. Considering epidemiological developments, an aggravation of the situation can be expected shortly. This analysis serves as a basis for improved public regional health care planning.