Summary
EU population today is the oldest it has ever been with 102 million people that are 65 years and older. This number is
forecasted to rise to 150 million and account for 30% of the overall EU population by 2050. Since most European seniors
wish to stay in their own home when growing old and since nursing homes are relatively more expensive, new care models
that prioritize home-care are required. To address this the European Parliament and EU member states are searching for
ways to provide high-quality care for the elderly, specifically through informal home-care and technological innovation.
Unfortunately, European seniors and caregivers are not getting the support they need. The EU’s unprecedented ageing has
created significant and growing need for care. Already today, there is a tremendous skills shortage in caregiving throughout
Europe. There are plenty of caregiver recruiting services, but they are ineffective as they are outdated and steeped in
conventional paper-based infrastructure. Furthermore, state-of-the-art solutions pair seniors and caregivers without attention
to differences in character traits, which too often leads to conflict and subsequently to early termination of caregiving
relationships. On top of that, they are expensive, fragmented and difficult to access because they lack online services.
mecasa addresses these problems by recruiting personnel via its online platform. Advertising takes place both on- and
offline, but actual recruiting is digitized through testing including voice analysis, automated document checks and video
interviews. mecasa has developed proprietary matching algorithms, which define matches based on individual character and
personality traits. Character traits are measured by standardized psychological testing, subsequently translated into a
mathematical logic and eventually enter the mecasa platform. The proposed mecasa-AI project is about further development
of the matching engine of the platform.
forecasted to rise to 150 million and account for 30% of the overall EU population by 2050. Since most European seniors
wish to stay in their own home when growing old and since nursing homes are relatively more expensive, new care models
that prioritize home-care are required. To address this the European Parliament and EU member states are searching for
ways to provide high-quality care for the elderly, specifically through informal home-care and technological innovation.
Unfortunately, European seniors and caregivers are not getting the support they need. The EU’s unprecedented ageing has
created significant and growing need for care. Already today, there is a tremendous skills shortage in caregiving throughout
Europe. There are plenty of caregiver recruiting services, but they are ineffective as they are outdated and steeped in
conventional paper-based infrastructure. Furthermore, state-of-the-art solutions pair seniors and caregivers without attention
to differences in character traits, which too often leads to conflict and subsequently to early termination of caregiving
relationships. On top of that, they are expensive, fragmented and difficult to access because they lack online services.
mecasa addresses these problems by recruiting personnel via its online platform. Advertising takes place both on- and
offline, but actual recruiting is digitized through testing including voice analysis, automated document checks and video
interviews. mecasa has developed proprietary matching algorithms, which define matches based on individual character and
personality traits. Character traits are measured by standardized psychological testing, subsequently translated into a
mathematical logic and eventually enter the mecasa platform. The proposed mecasa-AI project is about further development
of the matching engine of the platform.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/888297 |
| Start date: | 01-01-2020 |
| End date: | 31-05-2020 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
EU population today is the oldest it has ever been with 102 million people that are 65 years and older. This number isforecasted to rise to 150 million and account for 30% of the overall EU population by 2050. Since most European seniors
wish to stay in their own home when growing old and since nursing homes are relatively more expensive, new care models
that prioritize home-care are required. To address this the European Parliament and EU member states are searching for
ways to provide high-quality care for the elderly, specifically through informal home-care and technological innovation.
Unfortunately, European seniors and caregivers are not getting the support they need. The EU’s unprecedented ageing has
created significant and growing need for care. Already today, there is a tremendous skills shortage in caregiving throughout
Europe. There are plenty of caregiver recruiting services, but they are ineffective as they are outdated and steeped in
conventional paper-based infrastructure. Furthermore, state-of-the-art solutions pair seniors and caregivers without attention
to differences in character traits, which too often leads to conflict and subsequently to early termination of caregiving
relationships. On top of that, they are expensive, fragmented and difficult to access because they lack online services.
mecasa addresses these problems by recruiting personnel via its online platform. Advertising takes place both on- and
offline, but actual recruiting is digitized through testing including voice analysis, automated document checks and video
interviews. mecasa has developed proprietary matching algorithms, which define matches based on individual character and
personality traits. Character traits are measured by standardized psychological testing, subsequently translated into a
mathematical logic and eventually enter the mecasa platform. The proposed mecasa-AI project is about further development
of the matching engine of the platform.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
Geographical location(s)
Structured mapping
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