Australia has an ageing population due to increasing life expectancy and declining fertility rates. Older aged people are growing in numbers and the older people has an increasing share in the total population (CEPAR 2021). As of June 2020 it’s estimated that there are over 4.2million Australians aged 65 and over, comprising 16% of the total Australian population.
On the other hand, the aged care industry is facing staffing shortage affecting the quality of care provided to residential aged care and home care services. Being one of Australia’s largest service industries, aged care providers delivered services for 1.3million people in 2018 through half a million aged care providers.
As these challenges continue to plague the system, is the industry ready to embrace technology, particularly artificial intelligence in monitoring and enhancing programs for elderly care?
Artificial intelligence in aged-care and AI-powered health monitoring technologies may fill a significant gap in human resource by complementing current care provisions, helping reduce burdens of family care givers, and improving quality of care. Equipping aged care facilities with tools, such as AI and assistive technology may better manage care requirements and provide better patient outcomes.
The advancement in technology and wearable devices has paved way for readily accessible technology that can collect wellness data and provide an overview of an elder’s lifestyle. While these are helpful, they are not as powerful as AI-powered health monitoring tech that goes beyond data collection. These devices have the capacity to collect, learn, analyse, adopt, and predict, which will provide significant support to health care providers in caring for the elderly.
Medical sensors are used to diagnose, monitor, and treat diseases. These sensors comply with statutory specifications including standards for quality management, risk management, and functional safety to ensure that these devices function correctly with response to given inputs. These sensors can monitor blood pressure, EEG, oxygen saturation heart rate, temperature, and more.
Widely used medical sensors include:
Temperature Probes or thermometers are used in measuring body temperature to help provide better medication and treatment to patients.
Implantable Pacemakers are real-time embedded sensor systems delivering synchronized rhythmic electric stimulus to the heart muscle to maintain effective cardiac rhythm.
Pressure Sensors are commonly integrated with embedded systems to monitor blood pressure, medical diagnosis, and more.
Magnetometers sensors used to examine changes in the patients direction through the earth’s magnetic field around the user.
With machine learning capacity, these devices can continually collect and analyse data, identify, categorise patterns, and use predictive analytics to assess the risk level of the person as well as make behavioral and care recommendations.
Data obtained from regular monitoring of patients through medical sensors can be used to analyse and model data about age, medications, conditions, clinical factors, sociodemographic factors, health telemetry (e.g. blood pressure, temperature, ECG etc), and more to predict and monitor patient health. Over time, doctors and medical practitioners are able to better understand how elderly patients are responding to their treatment and care. Providing real-time understanding of their condition. At the same time service providers are able to provide better care.
Hospitals and aged care facilities have started adopting AI and machine vision to detect falls and monitor pain. Camera and visual monitoring streams may now be used to gauge pain levels based on facial expressions. This is particularly beneficial for patients who suffer from dementia and other conditions where they are not able to communicate when they feel pain and their pain level.
Fall detection is a valuable artificial intelligence in the aged-care function that helps cut down critical response time for medical workers to respond to patients. In aged-care facilities, this is extremely helpful in monitoring patients as they are not attended by staff 24/7 and accidents can occur at any time of the day.
For the elderly who opt to stay at home under the care of family members, there are AI-based machine vision technologies that monitor a person’s behaviour and abnormal interactions which then sends alerts to family members, caregiver and other medical providers. Abnormal behaviour includes falls, flu-like symptoms, and other abnormal movements.
The shortage of skilled caregivers has given rise to robotic helpers who can help elderly patients with daily assistance. Though home assistants are niched in nature, some are conversational robots that provide tailored conversations and help obtain monitoring and patient data, others are to keep them engaged and connected with families and the outside word.
Elderly patients especially those with cases of dementia will have disoriented states which may result in dangerous activities such as wandering on their own and leaving the house. Family members and service providers can monitor the where abouts of their elderly members through GPS-enabled wearables to provide realy-time location. Program safe areas and use this as parameter fence. Alerts can be sent to certain individuals to warn them that their elderly is leaving the area. Through AI, find patterns in their behaviour, places they frequent, time they will most likely wander around and other important observations.
High staff turnover rates coupled with the shortage of available qualified aged-care service providers remain a challenge in the industry. A number of organisations are looking into data analytics to help them understand how they can develop well-functioning and happy service providers to deliver outstanding care to their patients and clients.
When it comes to management and organizational improvement, data analytics is helping organisations become smart in drilling down to improve employee satisfaction and loyalty. Providing a platform that provide powerful insights in bringing change that will have the highest impact to retaining aged care workers and service providers.
Get a 360-view of payroll, finance, and HR data on one platform. A comprehensive view of your employee management including cost of payroll helps identify areas of inefficiency where improvements can be introduced for maximum impact.
Stay updated on compliance requirements. One of the most efficient ways to utilise data in management is to keep track of employee trainings, certifications and other compliance requirements. This way health care services can eliminate gaps when people can’t work due to compliance issues.
Smart Automation through machine learning and artificial intelligence help free up highly valuable time for health care providers for repetitive, redundant paper works and admin tasks. By doing so, they can dedicate more time to providing actual care and service to the elderly. Enhancing the quality of care and interaction which leads to better care management.
Data analytics in the aged-care industry is also valuable in the overall operation efficiency especially in managing cost and profitability for aged-care service facilities.
Examples of business metrics where data can help:
Artificial Intelligence and Generative AI in aged-care promises potential in providing comprehensive elderly care assistance and if developed ethically, is a valuable tool for medical practitioners. This will effectively complement the currently burdened caregivers and healthcare professionals. Ultimately improving the quality of care patients receive and as well as enhancing the well-being of aged-care service providers.
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