The actions should ensure that the novel ideas are accompanied mechanisms/tools that will aim to improve health outcomes and quality of life, not only to lower health care costs.
Actions should integrate health care research, health services research, innovation, health economics, implementation science, operations management/research, data science etc.

Applicants should propose activities underpinned by health care data in one or more of the following areas:

• The development of data-driven, interactive policy and visualisation tools bringing novel insights on populations, systems and services as a whole, to help policymakers make data-driven decisions.
• The development of data-driven solutions helping health care organisations take evidence-informed decisions on cancer care delivery processes such as logistics planning and management, capacity, utilisation of health services and allocation of resources, infrastructures, availability of and access to health care technologies (i.e. pharmaceuticals, vaccines, medical devices, etc.);
• The development of data-driven solutions empowering citizens’ and cancer patients’ interaction with the health care systems, including feedback mechanisms, guidance on health care pathways and on managing health care data, supporting patients in making health care decisions and treatment adherence;
• The development of digital toolkits and indicators to improve the reporting and assessment of outputs from end-user involvements, including those of patient-reported outcomes measures (PROMs) and patient-reported experience measures (PREMs), and help gauge the actual impact in health care (including interaction between patients and health care providers).

Applicants are encouraged to establish dynamic relations and synergies with the following areas, where applicable:

• Decision-making processes and tools, including social innovation
• Monitoring and evaluating the budgetary impact of health care interventions
• Health technology assessment and cost-effectiveness analysis
• Artificial intelligence/deep learning tools in social medicine to determine causal factors of disease/conditions and develop interventions
• Data sharing between different institutions
• European Health Data Space (EHDS)
• Open source and/or common building blocks used in Connecting Europe Facility (CEF)
• Standards and mechanisms to allow for interoperability between primary and secondary use of data
• Privacy-preserving protocols for secondary use of data for public health policy-making and research
• Federated/distributed access or data processing protocols for data-driven decision-support tools for better health care delivery and policy-making.