Open Call PHC-27-2015 Self-management of Health and Disease and Patient Empowerment Supported by ICT

European CommissionEmpowering citizens and patients to manage their own health and disease can result in more cost-effective healthcare systems by enabling the management of chronic diseases outside institutions, improving health outcomes, and by encouraging healthy citizens to remain so. Several clinical situations would be prevented or better monitored and managed with the participation of the patient him or herself. Care sciences may complement the medical perspective without increasing the cost.

Opening Date 30-07-2014
Publication date 11-12-2013 Deadline Date 21-04-2015 17:00:00 (Brussels local time)
Total Call Budget €104,500,000 Main Pillar Societal Challenges
Status Open OJ reference OJ C 361 of 11 December 2013

This requires research into socio-economic and environmental factors and cultural values, behavioural and social models, attitudes and aspirations in relation to personalised health technologies, mobile and/or portable and other new tools, co-operative ICTs, new diagnostics, sensors and devices (including software) for monitoring and personalised services and interventions which promote a healthy lifestyle, wellbeing, mental health, prevention and self-care, improved citizen/healthcare professional interaction and personalised programmes for disease management.

Support for knowledge infrastructures is also required. Implementation of programs or applications for different target populations to capture gender- and age-dependent differences in health, behaviour and handling of devices is encouraged.

This topic is a continuation of PHC 26 - 2014 giving more and different opportunities to develop solutions and services for self-management of health and diseases.

Solutions should be developed and tested with the use of open innovation platforms such as large scale demonstrators for health and service innovation. Gender and ethical issues should be duly considered. Proposals should involve health procurers and support them in their efforts to lower costs, and reduce difficulties associated with limited numbers of health professionals by utilising the capacity and potential of the patient as a co-producer of health. Proposals should use pre-commercial procurement to maximise the engagement of innovation in healthcare organisations following the community building and road-mapping activity in the seventh framework programme call 10 CSA on innovation in health procurement.

Proposals should aim to empower patients to manage their pre-existing conditions. Health management will be addressed holistically, including healthy lifestyle interlinked with disease management, placing the patient in the centre and putting increased emphasis on health education, secondary prevention and self-management of individual conditions, including co-morbidities.

Proposals should address all of the following elements a) personalised guidance to patients based on their profiles and the use of wearable/portable devices and improved individual/healthcare-professional interaction, b) engagement of patients as active members in managing their diseases, in particular addressing chronic diseases, co-morbidities, treatment adherence, rehabilitation, self-diagnostics and self-care and c) decision support systems interoperable and/or maintaining integrity with electronic health records.

The Commission considers that proposals requesting a contribution from the EU of between EUR 3 and 5 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Expected impact:

  • Improving the participation of the patient in the care process.
  • Improving the management of a disease by reducing the number of severe episodes and complications.
  • Increasing the level of education and adherence of individuals, patients and care givers related to application of ICT for personalised care.
  • Improved interaction between patients, their relatives, providers of health-, social-, and informal care givers.
  • Strengthened evidence base on health outcomes, quality of life, care efficiency gains and economic benefits from the use of ICT in new care models.
  • Reinforced medical knowledge with respect to efficient management of comorbidities.
  • Increased confidence in decision support systems for disease/patient management.
  • Involvement of health care providers/authorities with increased commitment in the deployment of innovative services empowering the patient.

Type of action: Pre-commercial procurement co-fund actions.

For further information, documents and submission service, please visit:
http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/2270-phc-27-2015.html

Find your partners or consortia preparing a project proposal
If you need help to identify a potential partner or consortia with particular competences, facilities or experience, please join Health IT Space at http://www.healthitspace.eu

Health IT Space is the first social networking platform for Health IT Professionals and Stakeholders. Explore the list of all Health IT Space registered members at http://www.healthitspace.eu/network/members

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...