| EPSRC Reference: |
EP/P010024/1 |
| Title: |
SCAMPI: Self-Care Advice, Monitoring, Planning and Intervention |
| Principal Investigator: |
Maiden, Professor N |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Faculty of Management |
| Organisation: |
City, University of London |
| Scheme: |
Standard Research |
| Starts: |
01 March 2017 |
Ends: |
31 May 2020 |
Value (£): |
1,006,003
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| EPSRC Research Topic Classifications: |
| Human-Computer Interactions |
Information & Knowledge Mgmt |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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06 Sep 2016
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Intelligent Technologies Prioritisation Panel
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Announced
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Summary on Grant Application Form |
In order to relieve pressure on an increasingly overstretched NHS, there is an ever-growing need to deliver more efficient, effective, patient-centric care in the community. New intelligent healthcare technologies have the potential to deliver this care relieve the pressure, in the form of simple-to-use digital technologies in people's home that support self-care and reduce the need for routine interventions from healthcare professionals.
Therefore, the SCAMPI consortium will develop a new form of computerised toolkit that will allow someone living in their own home with a chronic condition, together with their relatives, carers and healthcare professionals, to self-manage both their care of the condition and life with it. People will interact with the new toolkit through a new form of intelligent visual care plan, called VIZ-CARE. Any care plan is a documented agreement between a patient and healthcare professionals about the patient's care goals and qualities to maintain or work towards, and the desired services, medicines, and activities such as eating, exercising and socialising. SCAMPI's new form of care plan will be visual, natural and simple-to-use, enabling a person living at home with a chronic condition to customise their life and care according to their individual needs and preferences, with pro-active support for thinking about important care goals and qualities, as well as the means to achieve those goals and qualities. The person using VIZ-CARE will also be able to share the plan with named relatives, their carers and targeted healthcare professionals such as specialist nurses and their GPs, and make joint decisions about customising the care plan so that the person's needs can be met more effectively, even when these other people are elsewhere, using web technologies.
Moreover, the visual care plan will update regularly with care-specific feedback from discrete and cost-effective sensor devices placed around the person's home. Using the available data from these sensors as input to different artificial intelligence algorithms, a person's visual care plan in VIZ-CARE will indicate the degree to which the care goals and qualities of the person as specified in the plan are being achieved, and if needed, flag potential risk indicators along with care recommendations when a goal or quality is not being achieved. For example, to monitor planned daily activities such as a 20-minute local walk, VIZ-CARE will collect data not only about walking using a device such as a pedometer, but also about life and care qualities specific to the person and dependent on good hydration associated with walking about weight loss (from scales), movement in the home (to detect disorientation), kitchen temperature (to detect food consumption), loss of energy (from bed sensors) and water usage (from tap meters), and generate risks warnings if needed. This intelligence-led feedback is predicted to support self-care and reduce the need for routine interventions from healthcare professionals in the management of chronic conditions.
To develop and evaluate this new computerised toolkit, leading researchers in computer science, the health sciences and digital business at City University London have joined forces. The team will develop the first version of the toolkit to support with people with two conditions - dementia and Parkinson's disease. And to engage people with these conditions, their families, carers and disease experts in the co-design and evaluation of the toolkit, the researchers will work closely with the Alzheimer's Society and Parkinson's UK.
Moreover, to maximise impact from SCAMPI, the team will work with 6 London-based Care Commissioning Groups (CCGs) - Sutton CCG and the CWHHE Collaborative of 5 CCGs. Digital entrepreneurs Evalucom Consulting will seek to commercialise the research results so that the elements of the toolkit can be made quickly and widely available.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.city.ac.uk |