Topic: Prioritising Care Resources with Advanced Health Risk Monitoring – Improved Wellbeing and Independence Through Preventative Care
Day: Thursday 22 October 2020
Time: 3:30pm-4:00pm AEDT
To understand how we can reduce adverse health outcomes for individuals in both residential aged care and community care settings we must address one of the root problems that leads to us being deemed at high risk.
Addressing adverse outcomes prior to them occurring has been achieved with the use of Advanced Risk Monitoring (ARMED) technology that detects escalating health risk with reference to adverse outcomes such as falls based on activity, inactivity, long periods of inactivity and sleep quality and duration.
Evidence in the UK and Australia has shown with the use of the ARMED system that analyses data from quality wearable and peripheral consumer devices allows for early intervention and targeted care where escalating risk is identified within a person so people can gain improvements in sleep quality and general wellbeing.
Our research and practical application have been through individuals in these community and aged care settings being provided with a Polar smartwatch and a smartphone device to allow for the passive onboarding of data.
The system performs a daily prediction of each individual’s data set for the day previous and assigns them a risk flag rating being one of four levels; High, Medium, Low and Zero. An alert could also be sent daily to the individual, family member, care provider and allied health professionals to keep them aware of escalations in risk.
In the UK setting a project involving 24 users experienced zero falls in a 6-month period compared to a control group of where 59 falls occurred with 22 individuals in the same period. As a follow up to this an aged care provider also achieved only 1 fall in the ARMED user group and 54 falls in the control group of clients.
In Australia, we have seen a decrease in falls in a residential aged care setting for participants involved with the ARMED project over a 6 month period as well clients experiencing improved sleep quality and improved hydration levels when compared to the start of the project.
By linking the use of a smartwatch device, that is connected in real time to a predictive analytics system that utilises AI & Machine Learning, we can help individuals live independently in their home or in aged care for as long as possible by having advanced warning of a decline in health and wellbeing.
Mark is an independent consultant currently working with a range of aged care and health providers from large to medium and small sized Retirement Living, Home Care, Residential and Health care providers. His consultancy also includes working with organizations that provide primary health care, public health services, aged care and disabilities services in metropolitan, regional, rural and remote regions of Australia. Each of these organizations are different and require advice across a range of services.
His latest work has been in changing the operations of residential care from an institutional model to one of communal living where people are able to live their lives the way they did prior to coming into residential care.
This has now been achieved with a number of organisations operating his model of normalisation for people living in residential care.