Recent Case Studies
These examples illustrate the multifaceted impact of AI across various aspects of care home management, from resident safety and health monitoring to workforce efficiency and financial administration.
By targeting specific pain points, these AI applications have enhanced the quality of care, optimised resource allocation, and improved financial sustainability, making them invaluable tools in modernising the care sector.
Fall Prevention and Response with Nobi Smart Lamps at Hartland House
The Nobi Smart Lamps at Hartland House provide a proactive approach to fall prevention by leveraging AI and optical sensors to track residents’ movements. If a resident sits up in bed at night, the lamps emit a soft light to help orient them, reducing disorientation—a key contributor to nighttime falls. Upon standing, the lamps fully illuminate the room and send an alert to the care team via an app, enabling them to intervene before a potential fall. The system detected 100% of falls and significantly decreased the average response time from 57 minutes to under 2 minutes, allowing the care team to prevent “long-lie” falls, which can lead to serious complications. This pilot, initially in eight rooms, was so successful that it was expanded to the entire facility, demonstrating the power of technology in creating safer care environments and improving job satisfaction among carers by reducing high-stress emergency situations
Remote Health Monitoring at Havering Care Homes Using Feebris
Feebris was introduced at Havering Care Homes in Essex to address the challenges of early detection and routine health monitoring. The AI-powered system includes devices like a pulse oximeter and a stethoscope, connected to a smartphone app, enabling carers to monitor residents’ vital signs. Trained carers can capture high-quality lung sounds, heart rate, and blood oxygen levels without a clinician present, and the AI algorithm within Feebris analyses this data against a baseline established over time for each resident. This remote health monitoring reduces the need for in-person GP visits and enables timely interventions. The system has improved care efficiency, allowing carers to conduct a full assessment in under 10 minutes, while also easing the workload on nursing staff. GPs can remotely access and review data via a secure portal, supporting triage decisions and reducing unnecessary hospital admissions.
Health Data Integration with Health Call Digital Care Home in County Durham
In County Durham, the Health Call Digital Care Home system bridges the data gap between care homes and NHS systems, enabling more streamlined care. Using this system, carers input baseline health observations and daily metrics into a digital platform, creating a comprehensive resident health profile that is accessible by local GPs and NHS professionals. During the COVID-19 pandemic, this system played a crucial role in remote consultations and wound care management, which significantly reduced hospital admissions by allowing for early intervention on issues that could previously escalate without frequent in-person visits. Additionally, digital integration has reduced administrative burden by cutting time spent on phone consultations and improving the accuracy of referrals, leading to enhanced, continuous care for residents across multiple healthcare providers.
AI-Powered Workforce Planning and Management with Intelligent Workforce Solutions (IWS)
IWS, an AI-driven workforce management solution, has been used to tackle the challenge of scheduling in healthcare environments, specifically by analysing historical staffing needs and predicting high-demand periods. It leverages indoor positioning technology to track staff in real time, assigning tasks based on location and workload to improve efficiency. For instance, the system can automatically assign carers to assist residents based on proximity, thus reducing response time for urgent needs. AI-powered rostering also helps address staff shortages by predicting times when additional personnel may be necessary, supporting staff morale and reducing turnover. IWS’s data-driven approach to staffing has also shown a positive impact on financial management by minimising overtime costs and helping facilities manage budgets better by optimising staffing levels
Automated Financial Management at Thoughtful AI for Billing, Claims, and Revenue Reporting
Thoughtful AI streamlines financial management tasks, such as billing and claims processing, by automating complex coding and reconciliation. Through natural language processing, the AI system reviews care notes and medical codes to ensure accuracy, reducing billing errors and claims denials, which can be costly and time-consuming. This automation allows staff to focus on resident care rather than administrative tasks. Additionally, Thoughtful AI’s predictive analytics help identify claims likely to encounter issues, improving overall cash flow. By reducing errors in coding and automating reconciliations, Thoughtful AI has improved financial transparency and compliance, ensuring that care homes maintain financial health while minimising administrative overhead. This tool has proven especially valuable for facilities with complex billing structures, helping them to navigate reimbursement challenges more effectively
Use Case Examples of AI Implementation for Care Homes
Emotion Recognition and Mental Health Monitoring
Some AI tools can analyse residents’ facial expressions, body language, and vocal tones to assess their emotional state and flag any signs of anxiety, depression, or distress. For example, certain AI-powered cameras use advanced emotion-detection algorithms to monitor for signs of emotional change. If a resident shows indicators of sadness or confusion, the system alerts carers so they can check in. This proactive approach helps detect and address mental health concerns early, contributing to overall well-being and quality of life.
Predictive Health Analytics for Early Disease Detection
AI models can predict health issues before symptoms even appear by analysing a combination of vital signs, behavioural patterns, and genetic predispositions. Some care homes have begun using predictive analytics to foresee conditions such as urinary tract infections, heart issues, or respiratory problems. By leveraging this data, carers can take preventive measures, potentially preventing hospitalisations or serious medical interventions. A system like IBM Watson Health’s predictive models has been applied to large datasets, helping carers make proactive, life-saving decisions.
Robotic Assistance for Resident Engagement and Mobility
Advanced robotic devices, like the “Pepper” and “PARO” robots, are being used to provide companionship and mobility assistance. PARO, a robotic seal, responds to touch, voice, and even eye contact, designed specifically to provide comfort to residents with dementia, reducing agitation and creating a calming environment. Another robot, “Pepper,” interacts with residents through speech and gestures, engaging them in games, physical activity prompts, and memory exercises, helping stimulate cognitive functions while offering companionship.
AI-Driven Nutritional Assistance and Dietary Management
AI can manage dietary needs by analysing individual residents’ health records, preferences, and restrictions, ensuring that meals are personalised to optimise health. For example, systems are being used that monitor residents’ eating patterns and identify when someone may be at risk of malnutrition or dehydration. In some facilities, AI even helps prepare these meals based on each resident’s unique nutritional profile, with recipes adjusted daily to meet evolving dietary needs.
Smart Sensors for Real-Time Health and Safety Monitoring
Some cutting-edge AI systems utilise smart sensors to monitor residents’ physical environment in real time. These sensors track everything from air quality to body movement, helping prevent falls, and monitoring bed occupancy to ensure residents aren’t left unattended. Certain systems use AI to detect subtle changes in movement or routine that might signal deteriorating health, such as changes in gait or time spent in bed. These sensors can send alerts to caregivers instantly, enabling immediate intervention if necessary.
AI-Powered Cognitive Therapy Tools
Cognitive AI therapy tools like “MyCognition” are used to assess and enhance cognitive functions in elderly residents. These tools evaluate memory, reasoning, attention, and processing speed, tailoring exercises to boost cognitive health. AI-driven cognitive training helps residents retain mental agility and can even improve daily functioning for those with mild cognitive impairment, enhancing independence for longer periods.
