Demand-Side Indicators in Health Workforce Planning: Evidence from a Scoping Review

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Abstract

Introduction: Despite advancements in health workforce planning, there is still a lack of clarity regarding demand-side indicators utilized in workforce projection models and the rationale for their application. 


Goals and Methods: This scoping review aimed to identify, categorize, and analyze demand-side indicators currently used in health workforce planning. The scoping review was carried out in accordance with the framework developed by Arksey and O’Malley, and the guidelines of the Joanna Briggs Institute (JBI). We searched Medline/PubMed, SciELO, Google Scholar, Embase, and Web of Science, and included studies that explore demand-side indicators in the context of health workforce planning. Studies published in English, Portuguese, and Spanish from 2015 to 2025 were included. Grey literature from international organizations and national agencies, including reports, policy documents, and conference proceedings, was also considered. Data were synthesized narratively using a standardized extraction form, organized in tables and matrices, and complemented by qualitative content analysis that coded indicators across demographic, epidemiological, service utilization, behavioural, economic, and access/quality domains.


Results: We included 34 peer-reviewed studies and 16 grey literature sources, highlighting a wide range of health workforce planning models, including simulation and needs-based models, as well as hybrid and econometric approaches. Demand-side indicators focused mainly on demographic, epidemiological, and service utilization domains, with economic, behavioural, and patient-centred measures less frequently applied. While persistent data gaps remain—particularly regarding private-sector activity and migration flows—the evidence also highlights the growing use of standardized indicator frameworks to improve comparability and policy alignment.


Conclusions: This review highlights methodological variation and data gaps in demand-side indicators for workforce planning. Standardized frameworks can improve comparability and policy alignment. Advancing these areas will support more resilient health systems and universal health coverage.
 

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Institutions
  • 1 Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, Lisboa, Portugal
  • 2 NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, REAL, CCAL, NOVA University Lisbon, Lisbon, Portugal
Track
  • 1. Qualitative Research in Health
Keywords
Workforce
Health workforce
Human resources
Forecasting
Health Planning