Resident Care Support

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Resident Care Support

Resident Care Support

Introduction

This use case from South London Partnership – InnOvaTe “IoT” Project.

Outcome
Discrete monitoring of vulnerable residents in their homes to enable them to live independently by detecting changes in activity that may require interventions that could ultimately save lives.

Sectors
Local authority, Adult Social Care, public sector.

Key Stakeholders
Adult Social Care, housing partnership, housing, Data Team.

Summary

Overview

Sutton and Merton launched pilots in an effort to explore how IoT can contribute to Independent Living Officers’ (ILOs’) work, keeping at-risk residents living independently and safely at home. Digital solutions are becoming increasingly important as analogue telephone services, on which the existing telecare providers rely, will be reduced from 2023, and switched off entirely by 2025. This use case was prompted by the COVID-19 outbreak in particular, because vulnerable residents could not be as closely monitored during that period. They were also likely to be at higher risk of illness and physical or mental decline given the conditions of lockdown.

The hospital to home trial partially reproduced the strategy used above to support carers in assisting residents within their scope of activity, but with a system called Vayyar.

The ability to review resident well being data gathered by in-home sensors has fundamentally changed how the council services organise their workload, ultimately improving care delivered. Quantifying financial benefit (and therefore investment justification) has been difficult, especially when other organisations (e.g. NHS) could be the indirect beneficiaries. This technology has proven itself by optimising council resources and saving human lives.

There were three main IoT trials related to resident care support; two in Sutton and one in Merton.

The first cases for Sutton and Merton were born of the need to support vulnerable residents during the COVID-19 pandemic, when physical visits were not permitted. A single battery-powered device was hand-posted to the resident, which was used to indicate decline in the health of the resident and allow an ILO (Independent Living Officer) to intervene. In Sutton, the ability to review the sensor data has fundamentally changed how the ILOs organise their workload and allowed them to provide a more targeted and efficient support service to residents. Data visualisation has emerged as a key benefit from this system. The provider of the sensors was IoTSG (IoT Solutions Group).

In the second trial for Sutton, 50 sensors would be deployed in dwellings used for the rehabilitation of people discharged from the hospital (hospital to home). While people were still recovering, carers would provide tailored support to those people for up to six weeks. The aim was to use Vayyar devices on the wall to pick up if, when and where a person falls. Then the device would send an alert to the carers so they could take immediate action.

About the Author

The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.

Case Study Challenge

The adult social care system in the UK is facing a number of challenges, including increased demand, complexity, workforce shortages, and integration. These challenges are having a number of negative consequences, including cuts in other services, longer waiting times, and declining quality of care. Increased strain on Independent Living Officers (ILOs) has meant less time can be given to individuals. Unobtrusive and easily deployable pilots were aimed to address this by providing prioritised actionable insights to staff to focus on those who need care the most.

Implementation

Use Case Design Objectives

Use cases were designed to help council services work more efficiently by detecting changes in residents’ daily activities and alerting teams to declining activity. This provides early warning of vulnerable residents becoming unwell. Sensors were hand-posted to residents and continuously recorded humidity and temperature data. The data was reported back to a central database every four hours. Data was processed using machine learning to understand the resident’s normal activity patterns, giving smart insights into any possible changes. In addition, to support vulnerable residents returning from hospital, sensors were deployed to detect falls and send alerts to carers, providing tailored support to people recovering at home.

Commissioning (budget/procurement)

In November 2020, a selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team. The contract was awarded to IoT Solutions Group in January 2021. The budget range for each trial was less than £50,000 and trials typically lasted 1-2 years.

Deployment (what / who / where / how long)

Around 150 sensors were deployed in Sutton and less than 50 in Merton. The sensors were posted to the trial participants with instructions to place the device in the kitchen. Sensors were battery-powered and required no setup or install by residents. Each morning council services team members checked status of each of the sensors via an online dashboard portal – this data would focus the staff members attention for the day, prioritising their workload to perform check-ins on residents who most likely needed assistance that day. In addition, alerts were generated if a resident’s status changed drastically within a four-hour period. In Merton, the sensors were deployed in two groups of residents. The first was a group of 15 adults with learning disabilities, where there was a genuine concern that cuckooing of some of these residents may be occuring. The second group was 6 adults receiving telecare support. This provided key learnings to contrast across the groups. Monitoring residents returning from hospital helps to provide essential intervention when needed.

Technology Implemented

Sensors measuring a number of factors to assess activity were deployed. Connectivity was provided via the NB-IoT wireless network to a cloud hosted service. A secure data dashboard was also created on Microsoft Power BI allowing officers to see and drill into all data generated by the solution.

Outcomes

Results / Key Findings

In Sutton, IoT technology helped Sutton Housing Partnership (SHP) save the lives of five residents. The sensors improved council service efficiencies, delivering better care to more residents – it’s important to add that no normal checking calls were due for the affected residents. Insights were also generated to investigate possible fuel poverty, as well as provide alerts during periods of extreme hot and cold weather. Five residents’ lives were saved because of proactive alerts. The sensors proved to be non-invasive and gave residents peace of mind. Overall, the IoT trial in Sutton was a success, and the technology has the potential to improve the lives of many people. SLP won the Smart Places Award at Connected Britain Awards 2022 as a result of this trial.

In the Merton trial, capacity in the care team was stretched over the busy winter period due to COVID-19. Merton continued to monitor the 21 homes with the sensors but did not roll out anymore. Merton officers found the sensors useful, as they confirmed cuckooing was not occurring. However, they already had access to similar technology in their adult accommodation and this product added no significant additional value to what was already in place.

With regards to monitoring residents returning to home from hospital, sensors were successful in detecting if a resident fell in their home after release from hospital. Sutton was interested in using the sensors to monitor residents’ health and safety. There is also an intention in exploring other functionalities of the devices, such as monitoring residents’ breathing and heart rate to capture anomalies to enable swift action to be taken.

Benefits / Usefulness of Data

Data obtained from the trial has shown that these kinds are insights are very valuable. There has been improved decision-making and has led to changes in the way the service has been run. Additional insights were obtained that were not expected, e.g. confirming the support needs of adults with learning disabilities. Over time, the quality of the data obtained has improved its reliability, strengthening the value of the overall solution.

Lessons Learned

Some key lessons learned involved the display / presentation of the data obtained. Data visualisation has emerged as a key requirement for this case study. We learnt that it is advisable for early response sensors to be rolled out primarily where a local authority owns the housing stock, and can roll out the sensor as standard to many homes at once. When a local authority has officers with responsibility for many more residents than they can reasonably monitor in close detail. Communication with the residents was key, investment into this was essential. Ensuring requirements for outcomes (not technology) was also important.

Conclusion

IoT sensor deployment in Sutton has been considered a big success, providing more insights than expected, and having saved a life in the first week, expectations were exceeded on all counts. Additionally, the insights generated have driven a good number of fuel poverty and temperature related interventions. The trial did deliver on its original goal, which was to enable officers to be more efficient with their allocation of time to vulnerable residents, improving the overall service experience. Merton did also generate good outcomes but not as significant as Sutton, primarily due to the fact that Merton does not have its own housing stock.

Photos from the use case