Earlier and more precise palliative care

Expected Outcome: Proposals under this topic should aim to deliver results that are directed and tailored towards and contribute to all of the following expected outcomes: Patients will benefit from better access to earlier, more person-centred palliative care models including digital remote tools and options for home-based care. Carers will benefit from real-time information tools and better communication. Clinicians will benefit from guidelines on optimal patient referral and care predictions. Scope: This topic will contribute to the achievement of the EU Cancer Mission’s objective to provide better quality of life for cancer patients, their families and carers. The focus is on the development of innovative models for earlier, more precise and better integrated palliative care. According to an EU conference on innovative palliative care for people with cancer on 8 October 2024 [1] , palliative care has big potential but such interventions come much too late and are often imprecise. Palliative care is needed very early after cancer diagnosis with the best possible information on patient wishes and effective communication between all involved carers. Barriers also include the insufficient workforce allocation, insufficient retention and resilience of staff, incorrect transferals between care facilities, regional inequities and higher needs for home-based care. In order to improve the access to palliative care, innovative models for earlier, more precise and more patient-centred care should be developed. These models should be built on patients’ needs and the consideration of all possible care options. They should use AI and digital remote tools to empower clinicians, and to deliver well-integrated care with optimal care predictions. Proposals should address most of the following: Develop innovative models for earlier, more precise/personalised and integrated palliative care, including digital remote tools, to predict patients’ care preferences, to assign clear roles of carers and to avoid obstacles such as insufficient or inequal access. Testing and validation of these models in real-world settings through implementation research and clinical trials. Age, sex and gender differences should be duly considered. Attention should be given to address staff training, roles and adherence of conditions. Usage of AI and digital remote tools (such as explanatory videos, messaging, etc.) to allow real-time communication and to predict care needs and resources. Adoption of guidelines for optimal referrals, efficient and sustainable workforce allocation and retention …