AI is well-positioned to assist in addressing the future shortfall of senior home health care workers. Conversational AI devices, which can converse with humans, have improved the quality of life, independence, and mental health of elderly persons who live alone.
The expanding older population is putting pressure on care resources. Eldercare, long-term care, and chronic illness management are increasingly burdensome and costly health care problems, and the situation will worsen in the coming years as the population ages.
The number of Americans over 65 is expected to more than double in the United States, rising from 50 million now to almost 100 million by 2060. This rapidly expanding older population is already putting a burden on care teams, home health aides, and family caregivers.
The number of monitoring devices collecting patient data for AI applications like predictive analytics will skyrocket. There were 53,000 such devices in use in 2017, and there will be 3.1 million by 2021.
As more devices are connected to AI-based predictive analytics models, hospitals will save US$52 billion by 2021, with North America leading the way with US$21 billion in savings.
Many AI businesses start with hospitals, where they face bureaucratic roadblocks, budgetary constraints, and reluctance about turning over the personal data essential to train artificial intelligence models.
Wearables driven by AI provide users with real-time reminders and actions to avoid health risks and detect illnesses before they progress.
Furthermore, by continuously capturing and analyzing patient metrics and enabling remote monitoring, these AI wearables would allow clinicians to see changes in activity and behavior patterns that could aid in the prevention of potential problems such as heart failure, diabetes, chronic obstructive pulmonary disease, and even COVID-19.
Artificial intelligence’s disruptive power is being felt across many industries, but nowhere is its potential impact more profoundly life-changing than in health care.
Today, the potential of AI is being used in-home care settings to enhance and improve care to make it more effective, efficient, safe, and compassionate while meeting people where they are — at home.
Given the conditions, healthcare practitioners are beginning to delegate specific treatment pathways to AI-based automation. As a result, AI is now present in all therapeutic processes, from advanced biometric data surveillance to early sickness identification.
AI is supporting patients and their families in grasping treatment methods. AI is also helping doctors in treating patients more effectively.
24/7 Care Assistants
AI-powered virtual nursing assistants, who are accessible 24 hours a day, may easily contact (and be contacted by) a large population of patients to see whether they feel well, take their medications, and have any questions about their treatment up crucial clinical resources.
If patients need assistance, they can be sent to their physician or another provider, services, or a loved one without requiring human interaction.
Virtual nursing assistants can help patients manage chronic diseases at home or after being discharged from the hospital by increasing patient engagement and boosting self-management skills to keep chronic illnesses from deteriorating. In addition, by reducing barriers to care and enhancing communication among patients, their families, and their providers, these virtual nursing assistants can help improve treatment, and give better results while saving costs.
People’s health and well-being are exacerbated by loneliness. According to a recent Cigna/Ipsos study, 46% of Americans feel alone in their homes and neighborhoods.
The problem is particularly acute among the elderly: 25 million persons over the age of 60 suffer from chronic loneliness, which is expected to climb to 35 million by 2030.
AI-powered chatbots are especially well-suited to tackling social isolation in-home care settings.
These chatbots can carry on a real conversation by utilizing conversational voice assistants, smart speakers, and robust natural language processing algorithms.
These digital companions may gather information about a person’s emotional status, noting whether they are not sleeping well, in pain, or depressed, which may be symptoms of a more serious mental health problem, in addition to giving companionship and emotional support to users.
There is a lot of data accessible in the healthcare area; the problem is that it is scattered among several databases. Furthermore, for data to be effective, it must be accurate, uniform, and complete, which is not always the case in the healthcare profession. Finally, budget limits become a hurdle in a society where reimbursements are limited. It is expensive to maintain current technology, let alone invest in new ones. Perhaps AI may minimize the time and effort necessary to gather data, analyze data, and prescribe a plan of action, thereby helping to enhance the lives of individuals receiving care and those providing it.