ABSTRACT
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.
Subject(s)
Health Workforce , Humans , Health Workforce/standards , Health Services Needs and Demand , Delivery of Health Care/standards , Forecasting , Health Personnel , Models, TheoreticalABSTRACT
BACKGROUND: Australia's health workforce is facing significant challenges now and into the future. Health Workforce Australia (HWA) was established by the Council of Australian Governments as the national agency to progress health workforce reform to address the challenges of providing a skilled, innovative and flexible health workforce in Australia. HWA developed Australia's first major, long-term national workforce projections for doctors, nurses and midwives over a planning horizon to 2025 (called Health Workforce 2025; HW 2025), which provided a national platform for developing policies to help ensure Australia's health workforce meets the community's needs. METHODS: A review of existing workforce planning methodologies, in concert with the project brief and an examination of data availability, identified that the best fit-for-purpose workforce planning methodology was the stock and flow model for estimating workforce supply and the utilisation method for estimating workforce demand. Scenario modelling was conducted to explore the implications of possible alternative futures, and to demonstrate the sensitivity of the model to various input parameters. Extensive consultation was conducted to test the methodology, data and assumptions used, and also influenced the scenarios selected for modelling. Additionally, a number of other key principles were adopted in developing HW 2025 to ensure the workforce projections were robust and able to be applied nationally. RESULTS: The findings from HW 2025 highlighted that a 'business as usual' approach to Australia's health workforce is not sustainable over the next 10 years, with a need for co-ordinated, long-term reforms by government, professions and the higher education and training sector for a sustainable and affordable health workforce. The main policy levers identified to achieve change were innovation and reform, immigration, training capacity and efficiency and workforce distribution. CONCLUSION: While HW 2025 has provided a national platform for health workforce policy development, it is not a one-off project. It is an ongoing process where HWA will continue to develop and improve health workforce projections incorporating data and methodology improvements to support incremental health workforce changes.
Subject(s)
Health Personnel , Health Policy , Health Workforce , National Health Programs , Policy Making , Australia , HumansABSTRACT
This editorial introduces the 'Right time, Right place: improving access to health service through effective retention and distribution of health workers' thematic series. This series draws from studies in a range of countries and provides new insights into what can be done to improve access to health through more effective human resources policies, planning and management. The primary focus is on health workforce distribution and retention.