Is Physical Rehabilitation Need Associated With the Rehabilitation Workforce Supply? An Ecological Study Across 35 High-Income Countries

Author:

Jesus Tiago S.1ORCID,Landry Michel D.23ORCID,Hoenig Helen45,Dussault Gilles1ORCID,Koh Gerald C.6ORCID,Fronteira Inês1ORCID

Affiliation:

1. 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.

2. School of Medicine, Duke University, Durham, NC, USA.

3. Duke Global Health Institute, Duke University, Durham, NC, USA.

4. Physical Medicine and Rehabilitation Service, Durham Veterans Administration Medical Center, Durham, NC, USA.

5. Division of Geriatrics, Department of Medicine, Duke University Medical Center, Durham, NC, USA.

6. Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

Abstract

Background: To 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 10 000 population) across high-income countries (HICs), adjusted for socio-demographic and economic covariates. Methods: This is a cross-national ecological study. Hierarchical, multiple linear regressions analyzed current international data across 35 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 2017 (GBD 2017); and finally relevant socio-demographic variables and supply-side covariates extracted from the World Bank, GBD 2017, the supply data sources, and the Global Health Expenditure Database. Results: The PTs and OTs per capita varied greatly across the 35 HICs, differing by as much as 40-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 >.10). In the final model, after Bonferroni correction, 3 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 <.01). Conclusion: PT 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.

Publisher

Maad Rayan Publishing Company

Subject

Health Policy,Health Information Management,Leadership and Management,Management, Monitoring, Policy and Law,Health (social science)

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