Using national data to model the New Zealand radiation oncology workforce

Supply and Demand for Radiation Oncologists in Canada: Workforce Planning Projections From 2020 to 2040

PURPOSE

The number of Canadians diagnosed with cancer, and subsequent demand for radiation therapy, are expected to increase over time. This study aimed to update our needs-based workforce planning model to ensure appropriate staffing levels in the future.

METHODS AND MATERIALS

The supply of radiation oncologists, by age group, sex, and full-time equivalent status, was projected from 2020 to 2040 using a recursive-aging, input-output model developed with seeding parameters derived from national sources. The demand for radiation oncologists until 2040 was estimated using referral patterns for radiation therapy and consultation workload metrics applied to projected annual cancer incident cases to calculate required full-time equivalent positions. Baseline model parameters were also applied to the 2005-2019 workforce and incident case data to evaluate preprojection supply and demand trends.

RESULTS

Preprojection trends for 2005 to 2019 revealed accelerated staffing growth that transitioned from a workforce shortage to a surplus state in 2014 followed by substantial growth slowdown in 2016. The model predicts a transient surplus of radiation oncologists until 2026 followed by a projected deficit in subsequent years. Sensitivity analyses using the plausible range for each parameter continued to favor an undersupply, suggesting a trainee shortage unable to meet workforce expansion needs. Considering possible future declining trends in radiotherapy utilization and workload, calculations to inform corrective efforts in resident numbers resulted in 25 entry positions per year, up from 21 per year currently. Geographic distribution of trainees, relative to workforce and cancer incidence distributions, could be improved with more residency positions in Canadian regions outside Ontario.

CONCLUSIONS

Demand for radiation therapy and radiation oncologists in Canada are expected to grow more quickly than future expansion in staffing levels. Our workforce planning model provides evidence for more trainee requirements to inform stakeholders of possible corrective actions to training programs and recruitment. Further research is needed to explore additional strategies to expand capacity and high-quality delivery of radiation therapy to meet the foreseeable increase in Canadian patients with cancer.

Methods for health workforce projection model: systematic review and recommended good practice reporting guideline

BACKGROUND

Health workforce projection models are integral components of a robust healthcare system. This research aims to review recent advancements in methodology and approaches for health workforce projection models and proposes a set of good practice reporting guidelines.

METHODS

We conducted a systematic review by searching medical and social science databases, including PubMed, EMBASE, Scopus, and EconLit, covering the period from 2010 to 2023. The inclusion criteria encompassed studies projecting the demand for and supply of the health workforce. PROSPERO registration: CRD 42023407858.

RESULTS

Our review identified 40 relevant studies, including 39 single countries analysis (in Australia, Canada, Germany, Ghana, Guinea, Ireland, Jamaica, Japan, Kazakhstan, Korea, Lesotho, Malawi, New Zealand, Portugal, Saudi Arabia, Serbia, Singapore, Spain, Thailand, UK, United States), and one multiple country analysis (in 32 OECD countries). Recent studies have increasingly embraced a complex systems approach in health workforce modelling, incorporating demand, supply, and demand-supply gap analyses. The review identified at least eight distinct types of health workforce projection models commonly used in recent literature: population-to-provider ratio models (n = 7), utilization models (n = 10), needs-based models (n = 25), skill-mixed models (n = 5), stock-and-flow models (n = 40), agent-based simulation models (n = 3), system dynamic models (n = 7), and budgetary models (n = 5). Each model has unique assumptions, strengths, and limitations, with practitioners often combining these models. Furthermore, we found seven statistical approaches used in health workforce projection models: arithmetic calculation, optimization, time-series analysis, econometrics regression modelling, microsimulation, cohort-based simulation, and feedback causal loop analysis. Workforce projection often relies on imperfect data with limited granularity at the local level. Existing studies lack standardization in reporting their methods. In response, we propose a good practice reporting guideline for health workforce projection models designed to accommodate various model types, emerging methodologies, and increased utilization of advanced statistical techniques to address uncertainties and data requirements.

CONCLUSIONS

This study underscores the significance of dynamic, multi-professional, team-based, refined demand, supply, and budget impact analyses supported by robust health workforce data intelligence. The suggested best-practice reporting guidelines aim to assist researchers who publish health workforce studies in peer-reviewed journals. Nevertheless, it is expected that these reporting standards will prove valuable for analysts when designing their own analysis, encouraging a more comprehensive and transparent approach to health workforce projection modelling.

Use of Novel National Data Sets to Monitor Chemotherapy Use and Outcomes: A Retrospective Cohort Study of Non-Small-Cell Lung Cancer in Aotearoa New Zealand

PURPOSE

Te Aho o Te Kahu, the New Zealand Cancer Control Agency, is establishing a systemic anticancer therapy (SACT) database (Anti-Cancer Therapy-Nationally Organized Workstream [ACT-NOW]) which can be linked to other national health data collections. In this article, we explore the application of ACT-NOW data in the monitoring of uptake and outcomes after the public funding of pemetrexed in Aotearoa New Zealand.

METHODS

We used the ACT-NOW collection to identify patients with advanced nonsquamous non-small-cell lung cancer, who were treated with first-line platinum-based doublet chemotherapy over an 8-year period. Data were extracted for a period of 4 years before and 4 years after the national funding of pemetrexed (November 1, 2017). Treatments were classified as historical platinum doublet (cisplatin or carboplatin with gemcitabine, vinorelbine, paclitaxel, or docetaxel) or platinum pemetrexed doublet (cisplatin or carboplatin with pemetrexed). The primary outcome was the proportion of patients receiving each treatment type, before and after November 1, 2017. To prototype linkage to outcomes data, we evaluated hospitalization and 1-year overall survival (OS) rates by treatment.

RESULTS

A total of 331 patients were included from four cancer centers. All patients (116 of 116) who were treated with first-line platinum-based doublet chemotherapy between November 2013 and November 2017 received historical platinum doublet chemotherapy. After the introduction of pemetrexed, between November 2017 and November 2021, 94% (203 of 215) were treated with platinum pemetrexed doublet chemotherapy and 6% (12 of 215) with historical platinum doublet chemotherapy. Linkage to outcomes data for 1-year OS, hospitalization rates, and lengths of stay outcome data were achievable.

CONCLUSION

The ACT-NOW data set has the potential to facilitate evaluation of the impact of national-level SACT funding decisions on prescribing practice and specific patient outcomes. Our results support the use of these data to inform resource planning and quality improvement.

Radiotherapy-specific quality indicators at national level: How to make it happen

PURPOSE /OBJECTIVE

To promote best practice and quality of care, the Belgian College of Physicians for Radiotherapy Centers established a set of radiotherapy specific quality indicators for benchmarking on a national level. This paper describes the development, the collected QIs, the observed trends and the departments' evaluation of this initiative.

MATERIAL AND METHODS

The Donabedian approach was used, focussing on structural, process and outcome QIs. The criteria for QI selection were availability, required for low-threshold regular collection, and applicability to guidelines and good practice. The QIs were collected yearly and individualized reports were sent out to all RT departments. In 2021, a national survey was held to evaluate the ease of data collection and submission, and the perceived importance and validity of the collected QIs.

RESULTS

18 structural QI and 37 process and outcome parameters (n = 25 patients/pathology/department) were collected. The participation rate amounted to 95 % overall. The analysis gave a national overview of RT activity, resources, clinical practice and reported acute toxicities. The individualized reports allowed departments to benchmark their performance. The 2021 survey indicated that the QIs were overall easy to collect, relevant and reliable. The collection of acute recorded toxicities was deemed a weak point due to inter-observer variabilities and lack of follow-up time.

CONCLUSION

QI collection on a national level is a valuable process in steering quality improvement initiatives. The feasibility and relevance was demonstrated with a high level of participation. The national initiative will continue to evolve as a quality monitoring and improvement tool.