Tiago S. Jesus - Global Health and Tropical Medicine & WHO Collaborating Center on Health Workforce Policy and Planning, Institute of Hygiene and Tropical Medicine - NOVA University of Lisbon, Lisbon, Portugal
Michel D. Landry - School of Medicine, Duke University, Durham, NC, USA
Helen Hoenig - Physical Medicine and Rehabilitation Service, Durham Veterans Administration Medical Center, Durham, NC, USA
Gilles Dussault - Global Health and Tropical Medicine & WHO Collaborating Center on Health Workforce Policy and Planning, Institute of Hygiene and Tropical Medicine - NOVA University of Lisbon, Lisbon, Portugal
Gerald C. Koh - Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
Inês Fronteira - Global Health and Tropical Medicine & WHO Collaborating Center on Health Workforce Policy and Planning, Institute of Hygiene and Tropical Medicine - NOVA University of Lisbon, Lisbon, Portugal

BackgroundTo determine whether population-adjusted rates of physical rehabilitation need (ie, disability-related epidemiological data) are associated with the workforce supply (ie, combined rates of practicing physical therapists (PTs) and occupational therapists (OTs) per ۱۰ ۰۰۰ population) across high-income countries (HICs), adjusted for socio-demographic and economic covariates. MethodsThis is a cross-national ecological study. Hierarchical, multiple linear regressions analyzed current international data across ۳۵ HICs using: current PTs and OTs supply data obtained from the international professional federations (outcome variable); needs data obtained from the Global Burden of Disease ۲۰۱۷ (GBD ۲۰۱۷); and finally relevant socio-demographic variables and supply-side covariates extracted from the World Bank, GBD ۲۰۱۷, the supply data sources, and the Global Health Expenditure Database. ResultsThe PTs and OTs per capita varied greatly across the ۳۵ HICs, differing by as much as ۴۰-fold. Denmark had the greatest supply per capita. Physical rehabilitation need was not a significant, independent predictor of workforce supply regardless of the multiple regression model used (P >.۱۰). In the final model, after Bonferroni correction, ۳ covariates were significant, independent predictors of the supply variable: gross national income (GNI) per capita and the current health expenditure in % of gross domestic product (GDP) were positive factors for workforce supply, while population size was a negative factor (all P <.۰۱). ConclusionPT and OT workforce supply is highly variable across HICs. This variability is not accounted for by an indicator of population need but rather by financial indicators and population size.

Health Workforce, Rehabilitation, Physical Therapy, Occupational Therapy, Health Services Needs, High-Income Countries