Health workforce planning methods in rural and remote primary care: a scoping review.

backgroundRural and remote communities experience poorer health outcomes and lower life expectancy than their metropolitan counterparts. This is in part due to the lack of access to an appropriately skilled health workforce to meet their primary healthcare needs. Various health workforce planning and forecasting methods have been described in the literature at the country and regional level; however, methods designed specifically for rural and remote communities may be required. The aim of this scoping review is to identify and critically analyse existing methods for health workforce planning and forecasting in rural and remote primary care to improve access to primary care services in those communities.

methodsThe review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). A comprehensive search strategy was developed and conducted in PubMed, SCOPUS, EMBASE and CINAHL for peer-reviewed articles published in English between January 2005 and July 2025.

resultsThe search yielded 3938 records for screening and 57 full-text studies were assessed for eligibility, resulting in 26 articles included in the final review. Articles originated from 10 countries with the majority from Australia. Data sources used in planning included administrative registries, census and demographic data, health service utilisation records, workload and service statistics, population surveys, and qualitative inputs such as expert consensus and stakeholder engagement. Five approaches to workforce planning were identified: Workload Indicators of Staffing Need (WISN), geospatial accessibility and catchment models, stock-flow forecasting models, skill-mix and competency-based planning, and synthetic estimation modelling.

conclusionsFindings highlight a lack of clear guidance for policymakers in how to choose planning methods aligned to the models of care used (or visioned) in rural and remote areas. Whilst a "whole of system" approach at a local level shows promise, there is a lack of clearly accepted methods and empirical evidence evaluating the effectiveness of such approaches. Additionally, the limited integration of workforce competency metrics alongside traditional headcount represents a notable gap, constraining opportunities for competency and skills-based planning at scale. Planning undertaken in isolation from the different models of care employed in rural and remote areas is likely to exacerbate workforce maldistribution. Progress requires the creation of integrated, longitudinal, competency-linked workforce datasets that link administrative, clinical and population domains to capture the dynamic realities of practice, including geography, mobility, workload intensity, models of care, scopes of practice and role flexibility to inform responsive rural and remote primary care workforce planning and resource allocation.