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Library›Open textbooks›New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology›Results of the scoping exercise

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New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology · Results of the scoping exercise

Results of the scoping exercise

CC BY 4.0 · National Institute for Health and Care Research · approximately 10 min read

Box 7 provides a summary of Chapter 3 of this report. The chapter presents the results of the scoping work which was conducted for this study, including all results from the rapid literature review.

  • The scoping exercise encompassed the first stage of this research and consisted of a rapid scan of relevant literature, nine key informant interviews and three online project design groups.
  • Key themes were fed into the design of stage 2 of the study. Given the challenges described in Chapter 2, it is possible that stage 2 may not have been feasible to complete without the insights and relationships developed during stage 1.

To inform our study design, the research team undertook scoping work to better understand new and emerging digital technologies for social care, with a focus on home sensors with AI technology. We conducted a rapid scan of relevant evidence, undertook nine key informant interviews, ran three project design groups with 11 stakeholders, and selected our case study sites. Scoping work included an exploration of which questions we should ask stakeholders, which themes to consider, and how best to collect the data from care providers and commissioners, people drawing on care and support, carers and care staff. This also enabled us to explore the challenges and lessons learnt from previous research and evaluation efforts and develop our research questions.

Rapid scan of relevant evidence

As part of our scoping work, we conducted a rapid scan of literature relating to the implementation of new and emerging digital technology, as well as evidence from research and evaluations of home sensors with AI technology specifically. We did this to clarify the research questions, develop research tools and identify appropriate analytical frameworks for the study. This was an informal process, using Google and Google Scholar searches, as well as ‘snowballing’ techniques, where sources emerged through looking at references and citations of relevant sources.52 As mentioned in Chapter 2, due to the rapid and pragmatic nature of this rapid scan of the evidence, we are not able to provide exact search strings, the number of articles included in the rapid scan or a reflection on the quality of the evidence. This was a pragmatic step to inform the design of stage 2, and should not be understood as a systematic review of the literature.

From this informal/rapid scan we identified the studies and literature discussed in Chapter 1 of this report – many of which were categorised into three main themes (see Table 4). First of all, there was a widespread sense that technology in general was not being used to maximum effect in social care. In particular, there seems to be a lack of evidence around the implications of new and emerging digital technologies – hence why this topic emerged as such a priority for rapid evaluation in the national prioritisation exercise which led to the current study. Second, there can be significant difficulties in terms of selecting what technologies might be most appropriate within social care. There is apparently little in the way of guidance for those procuring digital technology and a lack of awareness of the needs and opinions of the people who are ultimately expected to benefit  – those who draw on care and support. These challenges around choosing the most appropriate example of the technology are exacerbated by a rapidly changing marketplace populated by numerous smaller start-up companies that provide new and sometimes optimistically described technology. The final theme relates to the management of what can sometimes seem unrealistic expectations of the technology compared with the actual impact it can have on social (as opposed to health) care. The extent of these expectations is not aided by the lack of demonstrable evidence of the efficacy of much of this new technology.

Table 4 Key themes and subthemes from the rapid review of relevant evidence
Key themesSubthemes
Understanding the functionality of digital technologies Technology not being used to its full potential in social care
Gaps in understanding of new and emerging technology in particular
Selecting appropriate digital technology Little information to support stakeholders in selecting technology
Importance of the voices of people who draw on care and support and carers
Fast pace of change of the technology market and challenges this poses to the use of technology for social care
Managing expectations A lack of evidence concerning the outcomes expected by key stakeholders (including commissioners and providers, people who draw on care and support and carers)
Predominance of health over social care outcomes

Key informant interviews

We spoke to strategy and technology leads, commissioners and programme managers from across our case study sites. The interviews covered three key topics. First, we discussed the key areas that might be explored in our evaluation and the nature of the questions that should be asked of senior managers and care staff. Second, we discussed potential challenges and solutions when undertaking research of this kind. Third, we explored the practicalities of trying to collect data from a diverse workforce and a range of people who draw on care and support and carers, especially in a challenging policy context. This helped to ensure that stage 2 of our study was designed in such a way as to ask the right questions, generate helpful learning and ensure our methods of recruitment and data collection were practical and appropriate.

Emerging themes are summarised in Table 5. In relation to the content of the evaluation, our stakeholders felt it was important to understand not only the potential benefits of using new and emerging digital technologies to provide predictive care, but also in which circumstances it might be used and to surface any ethical concerns about collecting and using individual-level data in this way. Our key informants also felt it was important to understand the implications for the workforce, and whether it met the needs and expectations of senior staff, as well as capturing the experiences of front-line workers who had to use the technology in practice. In considering the key challenges and potential solutions when conducting such research, participants felt that we should focus on a single piece of technology, rather than including multiple interacting technologies and systems across different sites. They were also keen to capture outcomes relevant to social care (rather than to health care, as in most of the literature), and felt that something like the NASSS framework (which we shared with them) would be a helpful way of making sense of what we were likely to find. Finally, in considering the practical considerations of data collection, it was felt important to capture the experiences of people who draw on care and support and their carers, to include a range of different perspectives from different stakeholders, and to consider and accommodate the impact of COVID.

Table 5 Summary of key themes and subthemes from key informant interviews
ThemeSubthemes
Questions to ask in relation to AI technologyPotential benefits of technology for social care in terms of planning care
Ethical and political consequences of using data to make decisions
Importance of living situation (e.g. whether or not a person is living alone)
A need to better understand what service managers want from technology
Implications for front-line staff and the ways in which they interact with technology
The key challenges/solutions for conducting research in this areaLimitations of having multiple technologies from different providers in a single evaluation – focus on a single piece of technology across sites
The need for more research with social rather than health outcomes
The appropriateness of an underpinning framework such as NASSS
Practical considerations of data collectionImportance of collecting data from people who draw on care and support and carers
Incorporating different stakeholder views in the study design and in terms of their experience of the technology
The impact of COVID-19 on recruitment and data collection, and the importance of being sensitive to the pressures sites may be facing

Online project design groups

These online project design groups (for local authorities/care providers, and for people drawing on care and support and carers) helped us reflect on the type of questions and themes that group members thought we should explore in the evaluation and the practicalities of collecting data (particularly given the COVID-19 pandemic). This was to help us develop the topic guides for data collection and select appropriate and feasible methods in our evaluation.

A number of key themes emerged in relation to areas of importance and concern to both groups, as summarised in Tables 6 and 7. For local authorities and care providers, key themes included understanding what the technology can offer and which specific groups might benefit, and the risk of unrealistic expectations. This might be a particular issue if sites were exploring new and emerging technology with a view to generating savings, which might not materialise if the pilot was not successful. They also felt that it was important to understand the broader context in which technology was being implemented, with a risk that new ways of working might not be aligned with key pressures and drivers in the broader context. Other key themes were related to the digital literacy of the social care workforce, the best way of engaging a range of different stakeholders in implementation, and the difficulty of evaluating outcomes if what counts as success is often unclear.

Table 6 Key themes and subthemes from online project design groups with local authorities and care providers
Key themesSubthemes
Understanding the technology and the problem being addressedImportance of a clear understanding of what technology can offer at the outset of adoption
Identifying care and support needs before selecting which technology to use
Unrealistic expectations may drive decision-making and negatively impact resource planning
The importance of the environment/context in which the technology works
Digital literacy of those involvedThe skills required of staff and users are a primary consideration and influence on success
Challenges around understanding what new and emerging technologies can do in a fast-changing market
Participant engagementStrategies for how best to approach and engage staff, people who draw on care and support and carers in the research
Measuring outcomesWhat constitutes success and how to measure it is often unclear
Table 7 Key themes and subthemes from online project design groups with people who draw on care and support and carers
Key themesSubthemes
Impact on care and shared decision-makingWill people still have choice and control over their care, and can they choose whether or not to engage with new technology?
Impact on social contact with care workers
Data protection and information governanceWhat are the implications for privacy?
How data are gathered and used
Accountability/responsibility
Digital literacyTechnical skill and requirements of people who draw on care and support and carers
Strategies for supporting the participation of people who draw on care and support and carers

In contrast, people who draw on care and support and their carers expressed interest in how the technology might impact on their care and the shared decision-making associated with it. This included concerns that pilots might reduce social contact with care staff, and might erode choice and control (e.g. a feeling that analysis by the technology might drive what care is provided, rather than the person being able to exercise a degree of choice and control). They also raised questions about privacy, accountability and the use of data, as well as around the technological skills of people who draw on care and support and carers (see Table 7).

Research questions

As a result of this scoping work, the study seeks to answer the following core research questions:

  • RQ1. How do commissioners and providers decide to adopt new and emerging technology for adult social care? (Decision-making)
  • RQ2. When stakeholders (local authorities and care providers, staff, people who draw on care and support and carers) start to explore the potential of new and emerging technology, what do they hope it will achieve? (Expectations)
  • RQ3. What is the process for implementing technological innovation? (Implementation)
  • RQ4. How is new and emerging technology for adult social care experienced by people who draw on care and support, carers and care staff? (Early experiences)
  • RQ5. What are the broader barriers to and facilitators of the implementation of new and emerging technology in addressing adult social care challenges? (Barriers and facilitators)
  • RQ6: How has the COVID-19 pandemic influenced responses to the questions above? (Impact of COVID-19)
  • RQ7: How can the process of implementing new technology be improved? (Making improvements)

We answer each of these questions in turn in Chapters 4–9, with Chapter 10 (Discussion and conclusion) exploring the final research question and putting findings in a broader context.

← MethodologyFindings: Expectations of those adopting AI in social care →

Attribution. Jon Glasby; Ian Litchfield; Sarah Parkinson; Lucy Hocking; Denise Tanner; Bridget Roe et al. (2023). New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology. National Institute for Health and Care Research. Copyright © 2023 Glasby et al. Licensed under CC BY 4.0. NCBI Bookshelf NBK593317. CC BY 4.0. Original source ↗. Text reproduced from the Bookshelf XML without changing wording; figures, images and supplements are not reproduced.

In this chapter Contents

  • Results of the scoping exercise

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