New and emerging technology for adult social care - the example of home sensors with artificial intelligence (AI) technology.

Background: Digital technology is a focus within the NHS and social care as a way to improve care and address pressures. Sensor-based technology with artificial intelligence capabilities is one type of technology that may be useful, although there are gaps in evidence that need to be addressed. Objective: This study evaluates how one example of a technology using home-based sensors with artificial intelligence capabilities (pseudonymised as 'IndependencePlus') was implemented in three case study sites across England. The focus of this study was on decision-making processes and implementation. Design: Stage 1 consisted of a rapid literature review, nine interviews and three project design groups. Stage 2 involved qualitative data collection from three social care sites (20 interviews), and three interviews with technology providers and regulators. Results: • It was expected that the technology would improve care planning and reduce costs for the social care system, aid in prevention and responding to needs, support independent living and provide reassurance for those who draw on care and their carers. • The sensors were not able to collect the necessary data to create anticipated benefits. Several technological aspects of the system reduced its flexibility and were complex for staff to use. • There appeared to be no systematic decision-making process in deciding whether to adopt artificial intelligence. In its absence, a number of contextual factors influenced procurement decisions. • Incorporating artificial intelligence-based technology into existing models of social care provision requires alterations to existing funding models and care pathways, as well as workforce training. • Technology-enabled care solutions require robust digital infrastructure, which is lacking for many of those who draw on care and support. • Short-term service pressures and a sense of crisis management are not conducive to the culture that is needed to reap the potential longer-term benefits of artificial intelligence. Limitations: Significant recruitment challenges (especially regarding people who draw on care and carers) were faced, particularly in relation to pressures from COVID-19. Conclusions: This study confirmed a number of common implementation challenges, and adds insight around the specific decision-making processes for a technology that has been implemented in social care. We have also identified issues related to managing and analysing data, and introducing a technology focused on prevention into an environment which is focused on dealing with crises. This has helped to fill gaps in the literature and share practical lessons with commissioners, social care providers, technology providers and policy-makers. Future work: We have highlighted the implications of our findings for future practice and shared these with case study sites. We have also developed a toolkit for others implementing new technology into adult social care based on our findings (https://www.birmingham.ac.uk/documents/college-social-sciences/social-policy/brace/ai-and-social-care-booklet-final-digital-accessible.pdf). As our findings mirror the previous literature on common implementation challenges and a tendency of some technology to 'over-promise and under-deliver', more work is needed to embed findings in policy and practice. Study registration: Ethical approval from the University of Birmingham Research Ethics Committee (ERN_13-1085AP41, ERN_21-0541 and ERN_21-0541A). Funding: This project was funded by the National Institute of Health and Care Research (NIHR) Health Services and Delivery Research programme (HSDR 16/138/31 - Birmingham, RAND and Cambridge Evaluation Centre).

Social care is facing pressures due to a lack of funding and staff and COVID-19. One way to ease pressures is by using digital technology. We looked at a technology that places sensors around people's homes to monitor changes in daily activity, including how this technology was brought into social care and how it works. We reviewed evidence and spoke with experts (including people who draw on care and support) to finalise the study design. We then interviewed people from social care organisations, carers, technology developers and regulators. • Organisations expected the technology to do a lot, including preventing illness, assessing needs, supporting independent living, reassuring people drawing on care (and their carers) and saving money. • Some social care decision-makers may not have the skills and understanding needed to make decisions about the use of new technology, and lacked a strategic approach to decision-making. • It was difficult to collect the data needed to use the sensors correctly, which meant the technology did not meet expectations. • Care staff were trained on how to use the sensors, although many struggled to make sense of the data they collected. • Social care is often focused on dealing with a crisis, rather than preventing one. This means a culture change is needed to use the sensors properly.

Our research confirmed challenges in using new technology in social care. We also found new problems, such as dealing with large amounts of health data, asking care staff to use this information without enough training, and introducing a technology focused on prevention into an environment which is focused on dealing with crises. Our findings have helped to fill gaps in knowledge and will let us share practical learning with those introducing new technology in social care.

Implementing Asset-Based Integrated Care: A Tale of Two Localities.

BACKGROUND: To date, few studies have examined the implementation of asset-based integrated care in the UK. This paper aims to address this gap in knowledge through examining the implementation of one model of asset-based integrated care, Local Area Coordination (LAC), within two localities in England. METHODS: This paper draws upon data collected from two local authorities (site A and site B), which had both implemented LAC. Using a case study approach, qualitative data was collected from interviews with relevant stakeholders both internal and external to the local authorities. Data was analysed thematically. RESULTS: The findings demonstrate the marked differences between the two sites' approaches to LAC, especially in relation to: the implementation process; impact; and their collaboration with other agencies and communities. DISCUSSION: The evidence presented in this paper demonstrates that the implementation of LAC, as with most complex service innovations, is dependent on the interplay of organisational and people-based components. In particular, successful implementation depends on maintaining a common vision of what an intervention will achieve and how it will work in practice, continual engagement with the political and organisational leaders of influence, positively addressing the anxieties of existing services and professions, and working with community groups.

The Effect of Beat Frequency Vibration on Sleep Latency and Neural Complexity: A Pilot Study.

Insomnia affects millions of people worldwide, and non-pharmacological treatment options are limited. A bed excited with multiple vibration sources was used to explore beat frequency vibration (BFV) as a non-pharmacological treatment for insomnia. A repeated measures design pilot study of 14 participants with mild-moderate insomnia symptom severity (self-reported on the Insomnia Severity Index) was conducted to determine the effects of BFV, and traditional standing wave vibration (SWV) on sleep latency and sleep electrocortical activity. Participants were monitored using high-density electroencephalography (HD-EEG). Sleep latency was compared between treatment conditions. A trend of decreasing sleep latency due to BFV was found for unequivocal sleep latency (p ≤ 0.068). Neural complexity during wake, N1, and N2 stages were compared using Multi-Scale Sample Entropy (MSE), which demonstrated significantly lower MSE between wake and N2 stages (p ≤ 0.002). During N2 sleep, BFV showed lower MSE than the control session in the left frontoparietal region. As a measure of information integration, reduced entropy may indicate that BFV decreases conscious awareness during deeper stages of sleep. SWV caused reduced alpha activity and increased delta activity during wake. BFV caused increased delta activity during N2 sleep. These preliminary results suggest that BFV may help decrease sleep latency, reduce conscious awareness, and increase sleep drive expression during deeper stages of sleep. SWV may be beneficial for decreasing expression of arousal and increasing expression of sleep drive during wake, implying that beat frequency vibration may be beneficial to sleep.

Co-research with older people with dementia: experience and reflections.

BACKGROUND: There is growing evidence that people with dementia want to participate in research and benefit from their involvement. However, little attention has been given to date to the potential to involve people with dementia as co-researchers, not just participants. AIMS: The paper discusses the implications for people with dementia of involvement in research as co-researchers. METHOD: Older people with dementia participated in planning the research methods, conducting interviews and making sense of the findings. RESULTS: The project found that it is possible to involve older people with dementia in a meaningful way in research processes and that both co-researchers and participants can benefit significantly from their participation. CONCLUSIONS: The project has wider implications for the development of participatory research with people with dementia and for interventions based on peer support.

Empowerment and care management: swimming against the tide.

This paper is concerned with the policy and practice of care management, that is, the system for assessing care needs and arranging services to meet them, developed under the legislative framework of National Health Service (NHS) and Community Care Act 1990. The paper takes as its starting point the contrast between the rhetoric of service user empowerment in professional training, particularly of social workers, with the disempowering realities that arise in practice. It examines some of the sources of this conflict, looking in particular at contradictions inherent within the development of care management as a policy, conflicts contained within the legislation and associated guidance and contradictions evident at the level of practice. It argues that organizational processes and procedures consequent upon care management as it is evolving in practice are decreasing the possibilities for empowering practice and reinforcing the power of care managers at the expense of service users. It suggests that the power of the care manager is based on increased administrative and managerial responsibility, counterbalanced by diminishing professional autonomy and discretion. Some possibilities for future development if empowerment is to survive as a meaningful concept within care management are outlined. The paper concludes that there are serious limitations on the scope for empowerment within care management and that the real hope for empowerment lies in the encouragement and support of user-led initiatives in service planning, evaluation and provision.