United KingdomUnited KingdomMavis has the Beanbag Care service installed, supporting her to maintain independence at home. She has a very supportive family who visit her regularly and are committed to keeping their mum safe and happy. In initial conversations with the family on our home survey, they were confident that Mavis went to bed in her own room each night and slept through reducing any concerns with her night-time routine.
Disturbed sleep can really help to highlight deterioration in a person’s health, through illness or exacerbation of a long-term condition. Sleep is essential for our bodies and a lack of it can cause our mental wellbeing to decline and our ability to think clearly impacted. Many of the people on our pilot with East Riding of Yorkshire have a diagnosis of dementia or have some memory difficulties. A consistent sleep routine can really help a person with dementia to feel better, be less confused, and more coordinated.
The sleep system is a part of the Beanbag Care service, as it can provide many useful insights. After installation in Mavis’ home, the Beanbag Care app immediately highlighted some concerns to Mavis’ daughter Fiona.
It showed that Mavis was not getting into bed in the evening, at least 3-4 times a week, despite the family’s assumptions. Further investigation found that instead of going to bed, Mavis was spending time exploring her home, sitting in her spare room, and sleeping on the sofa.
This was important to discover, and great for Mavis and her family. It helped to explain why Mavis sometimes appeared tired and lethargic, and why her carers would find her still asleep in the morning. This service can also provide useful insights that can be shared with Mavis’Consultant who can use the information to determine any deterioration of her condition.
The Sleep Monitoring service within Beanbag Care was designed to highlight a change in sleep patterns to help detect a decline in health. For example, it enabled Fiona to see if Mavis has not gone to bed or gotten out of her bed at her normal times, as well as showing the number of times she got up through the night. These insights can be used to detect conditions such as urinary tract infections, declining health, and anxiety, all of which can increase the risk of falls, and cause long term impact or death if not addressed quickly.
Please note all names used in this case study have been changed to protect the identity of the service user.