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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›Findings: Early experiences of those using AI in social care

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New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology · Findings: Early experiences of those using AI in social care

Findings: Early experiences of those using AI in social care

CC BY 4.0 · National Institute for Health and Care Research · approximately 5 min read

Box 12 provides a summary of Chapter 7 of this report.

Summary of key points

  • The instability of the sensors (not producing data on a continuous basis for long enough to be consistently meaningful) meant there was no evidence of the expected cost benefits from a reduction in direct staff contact. That they were single-use further impacted on any potential savings.
  • Though the data gathered by the sensors were potentially useful, question marks remained over their reliability and precision (making it difficult to rely solely on the system for the safety of those who draw on care and support).
  • Several technological aspects of the system reduced its flexibility. For example, it could only be installed by the provider and was perceived as difficult to maintain and update independently. The complexity of the user interface and volume of the data it produced were also felt to overwhelm staff.
  • Given challenges in engaging people drawing on care and support and their carers, we were not able to collect information regarding the experience of these users of IndependencePlus.

The experiences of staff using the digital technology tended to fall into three main areas: cost, utility and usability. As noted in Chapter 2, we were not able to include the experiences of people who draw on care and support or carers in the way we had hoped, so the themes reported here are based on staff perceptions – both of their own experiences and their interpretations of the way in which the technology was experienced by people drawing on care and support/carers.

Cost

Some sites had hoped that IndependencePlus would be cost-saving in the short term, in particular due to its perceived ability to support independent living with a less intensive care package and less staff time. However, participants felt that the instability of the technology (see next page) meant that there could be no reliable evidence of it conserving resources. Another cost implication was the misplaced expectation that the sensors could be reused across multiple locations. However, it transpired during the implementation that the sensors were single-use only:

I think we thought it would be used more like a rolling piece of kit that you would take in and out of people’s homes. I think the original vision was you could just deploy this kit, gather the information you needed, take the kit away and deploy it somewhere else. And like I say, it became more about you know, like, giving somebody a piece of furniture that they have to keep forever and a day and it just continuously records data on them, transmits that data.

Utility

Several participants across two case study sites questioned the usefulness of the data they were presented with, as – in common with other remote sensor-based technology – they could not provide precise information on the activity of the individual. One example quoted was that a sensor indicating that the kettle had been switched on did not necessarily mean that a hot drink had been made and hydration levels were being maintained. Another issue that surfaced was that there seemed to be no way of determining whether the hub had been turned off or whether there was a lack of data on an individual because, for example, someone had fallen and was not moving. Undoubtedly, though, the overriding issue was a reported instability of the sensors (i.e. perceived as not working properly and providing continuous data for long enough to be consistently meaningful):

In terms of useful output of the kit, we were never able to get enough stability from the system to engage staff to look at the data because it was always quite patchy or always empty or things weren’t charged… It has to be 30 to 60 days of all of the sensors stable and staying online and feeding data into the system. And we spent almost a year and were never even able to get behaviour patterns established because we couldn’t keep the sensors online enough.

Usability

The sensors were perceived by staff to be relatively unobtrusive and well designed (although as mentioned above, we do not know if this was also the view of people drawing on care and support of their carers). However, it was a source of frustration for staff that they could not install the new equipment independently as they had done with previous sensor-based technologies. Instead, IndependencePlus technicians were required for installation. Because they were based at distance, they were reluctant to travel until a number of ‘subscribers’ were identified, leading to delays in installation. Sites also experienced practical difficulties in ensuring ‘compliance’ from intended beneficiaries, who might remove sensors or disrupt their functioning by adjusting their position (e.g. the sensors on the bed recording hours of sleep):

They have to wear this and they have to not touch this and they have to put the seatbelt on and this, that and the other – and it sounds very, very complicated, the technology… But for us, the kind of people that we could guarantee that compliance with are most likely not the people that we would want to use it for.

In order to use the data effectively, social care workers described how they needed the data interface to be straightforward to navigate and intuitive to comprehend. Although IndependencePlus adjusted the dashboard at one site in response to feedback, other interviewees reported that the quantity of data being pushed to the dashboard tended to overload staff and hinder comprehension. One example quoted was the way in which time was presented to the nearest second, instead of being rounded up into 15-minute slots. There was also a broader issue related to the technological expertise required to maintain and update the IndependencePlus software:

Technical maintenance was a very technically complex – well it was more technically complex and fiddly than we would have liked – to delete a sensor and add another sensor in meant going into, logging into that user’s portal as an admin person on an Android device. I wasn’t too familiar with Android devices myself – I’m an Apple user – so even that kind of navigation around the devices was a bit of a challenge. And I guess we’ve got to remember as well that within the care home there is nobody technical, there are pockets of accidental technical expertise, but this is really just people like the chef who have an interest, but his job is cooking the food, not supporting the technology!

Faced with these various technical complications, sites concluded that the pilots had not ‘worked’, and by the time of our involvement all had abandoned the experiment. However, as described in Chapter 4, at least some of this may also be linked to a lack of consensus around desired outcomes. If different people expect the technology to achieve different things, then it might prove impossible to design and deliver a new way of working which meets everyone’s aspirations, thereby leading to an inevitable conclusion that the technology has not been successful.

← Findings: Implementation of AI in social careFindings: Barriers and facilitators to the use of 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.

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  • Findings: Early experiences of those using AI in social care

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