As you or your loved ones become older, questions about retirement will emerge: What kind of care will my loved ones or I receive, or where will we go? For many families, nursing homes are a solution.
With over 1.4 million people living in nursing homes1, more and more seniors are exploring their options for long-term care facilities. The National Center for Health Statistics also states that over 83% of nursing home residents are above the age of 65 with at least one chronic condition, such as arthritis or heart disease 2.
With a growing senior population, artificial intelligence (AI) adoption plays a crucial role in shaping the future of elder care. From the earliest iterations of life alert bracelets that can detect falls to data-driven intelligence that can help nursing home staff care more effectively, AI in nursing homes is improving patient outcomes, monitoring resident health in real-time, and even allowing seniors to live autonomously for longer.
Benefits of AI for Elder Care
With a tough staffing climate, an aging population, and rising healthcare costs, the elderly healthcare industry faces unique challenges. Fifty percent of nursing home leaders said adopting new technology, specifically predictive analytics, was key to improving the quality of care3.
AI offers the opportunity to revolutionize both patient care and the administration of elder care. It helps with resource allocation and staffing shortages and assists providers and nurses in creating personalized care plans, proactively monitoring diseases, managing medications, and enhancing communication between residents and their families.
Real-World Applications of AI in Nursing Homes
AI has played a role in elder care for decades, with things such as medication reminders to reduce the risk of a missed dose and life-alert necklaces patients could press in case of a fall. Integrating AI through wearables or sensors can help improve resident care by enhancing the operations of nursing homes to notify nurses or providers of which residents require additional attention.
Remote Patient Monitoring in Nursing Homes
For long-term care residents, a great deal of nurse and provider energy goes into routine monitoring of blood pressure, heart rate, oxygen, temperature, and more. AI-powered remote patient monitoring devices (RPM) can monitor patient movements and activity and alert providers of changes. Plus, predictive analytics can play a role in identifying problematic trends.
For example, HealthSnap is a wearable health monitoring platform that empowers elders to proactively manage chronic conditions, with 84% of patients saying they felt an improved sense of control over their health4. Plus, more real-time remote patient monitoring through interconnected Internet of Things (IoT) devices allows for more proactive care that reduces potential emergencies.
Fall Detection and Prevention
Fall detection and prevention was one of the earliest applications of AI in healthcare, allowing for a quick response from medical teams and potentially life-saving interventions. Battery-powered, energy-efficient IoT environmental sensors in hallways and bedrooms like the HALO Smart Sensor can even monitor air quality conditions in addition to unusual activities like a fall5.
Sensors such as these are helpful in areas such as bedrooms or bathrooms where users need privacy. The device continuously monitors without video or audio recording and never captures personally identifiable information.
Data-Driven and Personalized Care Plans
Already, the data analyzed by AI is being used to transform the outcomes of clinical trials. In the same way, machine learning algorithms can aggregate billions of data points to determine likely trends and patterns within a nursing home resident’s behavior, medical histories, and more. Analyzing data such as the ones from remote patient monitoring devices can allow providers to create more personalized, targeted care plans.
For example, IBM Watson Health aggregates billions of data points from electronic medical records to create personalized care plans with targeted interventions for elders6. UK-based Mayden used this knowledge to deliver better mental health services faster to over 5 million patients7.
Improving the Quality of Life
For senior nursing home patients, quality of life improvements can include increased communication with family members or early voice analysis detection for anxiety or mental health issues. CarePredict leverages AI-powered wearables to log daily activities and send real-time updates to family members, allowing loved ones to stay connected8.
The CarePredict system includes precise real-time location tracking, pinpoint contact tracing if a senior with a contagious disease interacts with others, and an automated platform that measures the demand for each resident, improving staff efficiency.
Potential Challenges of AI in Nursing Homes
Like many AI applications, integrating continuous monitoring and edge intelligence provokes questions about privacy and data security, cost, ethical considerations, and more. Nursing homes handle sensitive personal information that requires strict regulatory compliance.
Also, while the potential benefits are great, the cost of purchasing and installing AI throughout large facilities quickly adds up, especially when you consider ongoing maintenance, hardware, and future upgrades. Plus, some experts worry about large-scale bias influencing machine learning algorithms, leading to unfavorable outcomes instead of improved healthcare.
Future Outlook of AI in Nursing Homes
AI healthcare is projected to exceed $36 billion in market value by 20259. With more people needing long-term care in the late stages of their lives for more serious conditions, AI adoption in elder care will most likely increase, making nurse homes a “smart home” of the future.
Augmented reality and virtual reality innovations could also provide unique emotional and cognitive support functions, using immersive, interactive experiences to prevent mental decline. Also, as innovation in robotics becomes a reality, routine tasks can be automated, allowing providers to focus on the patients themselves.
How Ambiq is Contributing
Artificial intelligence can be used to embed a nursing home’s walls, ceilings, and floors with low-power microcontrollers, such as the Apollo family of System-on-Chip (SoC) from Ambiq. The Apollo SoCs perform AI at the lowest power possible, reducing the possibility of a lapse in monitoring because the battery on a sensor died.
It also provides on-device inferencing that improves security vulnerabilities that may become exposed from data leaks transferred to the Cloud. Residents and their loved ones can gain peace of mind that they are in excellent care, while nursing homes can improve their operations and efficiency.
Sources:
1 Nursing Home Statistics: What to Know in 2024 | May 28, 2024
2 National Center For Health Statistics, Vital and Health Statistics | May 2022
3 Nursing Home Leaders Aim to Harness AI, Data to Beat Staffing and Payment Challenges in 2024 | January 17, 2024
4 HALO Smart Sensor | 2024
5 HealthSnap | 2024
6 Transforming Healthcare for Better Outcomes | 2024
7 IBM Case Studies – Mayden | 2024
8 CarePredict | 2024
9 AI in Healthcare Market to Grow to $36 Billion By 2025 | January 2, 2019
