Implementing innovative care models in European countries: What are the implications for health and care workforce planning and training?
Policy Brief 77 (HEROES BRIEF 1)
4 May 2026
| Policy brief
Overview
Using planning and forecasting to respond to future health care workforce (HCWF) needs is central to a health system’s ability to meet the challenges of population ageing and workforce shortages. This is one of a set of three policy briefs that reflect the evidence collected for the HEROES project. These briefs cover:
- how forecasting and planning can support innovative care models;
- data and tools for forecasting and planning; and
- making forecasting and planning sustainable through institutionalization.
- Europe’s health systems need to implement innovative care models if they are to meet future needs. The pressures of population ageing, chronic conditions and multimorbidity overlap with financial pressures and a shrinking HCWF, making it imperative that countries develop new ways of meeting needs in different settings, including primary care and community settings.
- Transforming the HCWF will be essential if health systems are to reduce the demand for health and personal care (including through prevention) and improve the efficiency of care delivery (through integration, digitalization and other innovative models of care).
- Health workforce forecasting and planning are crucial for addressing new roles, developing new professions, developing other competencies and capturing the training implications that will allow policy-makers to prepare for innovative care models and for the interprofessional education and training and joint-learning needed to support their implementation.
- HCWF forecasting and planning can help develop appropriate strategies, including by:
- exploring different scenarios for future demand, factoring in population needs;
- modelling the implications of new care-delivery models, such as population health management, person-centred integrated care or hospital-at-home services;
- helping to anticipate the types of workforce, capacities and skills required; and
- highlighting the need for better practice, fairer valuation and clearer career pathways in undervalued areas such as primary care and social care.
- The evidence generated by forecasting and planning will be key in enabling governments, education and training bodies to promote relevant skills:
- in primary care and transitional care;
- by using digital and e-health technologies that will support a shift to remote and self-care;
- by using team, communication and cross-professional skills to enable properly integrated care; and
- by working with patients, their families and communities to foster self-management, a person-centred focus and the engagement (and support) of informal carers.
- HCWF planning models will need to evolve to guide future decisions and the design and implementation of new models of care.
- Current approaches must be made conceptually stronger and consistently data driven.
- The emphasis needs to shift from traditional single-profession planning to new ways of working; new roles, skill mixes and collaborations; and integration and coordination across disciplines and professions.
- Improvements in HCWF planning models could also usefully tackle the:
- combination of specific, generic (transversal) and leadership competencies;
- balance between cost-effectiveness, scope of practice and skill development;
- feasibility and sustainability of different staff and skill mixes;
- whole-system needs of clinical practice, population health and social care.
- Governance is crucial and policy-makers need to ensure forecasting and planning are central to HCWF policies and play a key role in strategy, policy design and implementation, steering the transition towards care models that achieve more tailored, coordinated, efficient and equitable care.
WHO Team
European Observatory on Health Systems and Policies
Editors
Ronald Batenburg,
Mieke Rijken,
Peter Groenewegen
Number of pages
37
Reference numbers
ISBN: 1997-8073
Copyright
CC BY-NC-SA 3.0 IGO