Silver tsunami: how advanced analytics and AI can contribute to healthy ageing


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In this interview, four SAS experts explain how governments can use artificial intelligence and analytics to help citizens enjoy health and wellbeing in later life, touching on healthcare planning, supported community living, and the challenges and opportunities of ageing populations

Around the world, populations are aging at an accelerating pace due to increased life expectancy and declining birth rates. In many countries, especially developed ones, the population segment of older individuals is the fastest growing. The World Economic Forum has stated an expectation that, by 2050, for the first time in history, there will be more humans who are over 60 years than under 15. It is also expected that 80% of older people will be living in low and middle-income countries.

As such, all countries are facing major challenges to ensure that their health and social systems are ready to respond appropriately to this demographic shift, which is commonly referred to as the ‘silver tsunami’.

Here, Dora Rencoret, public sector marketer and industry leader at SAS, interviews four expert colleagues on the issue of healthy ageing.

The silver tsunami – friend or foe?

Andrea Covino, a SAS public sector leader based in Italy: The silver tsunami is often seen as a threat and a negative trend globally but both governments and private companies could benefit from this opportunity from a socio-economic perspective. Indeed, this trend could mean increased welfare services from governments and tremendous business development opportunities for the private sector. However, it does raise the question of how to cope with the increased age in population and related costs associated with it, including consideration that a smaller share of younger people will be at traditional working age.

What defines healthy ageing?

Andrea Covino: Older people can make positive contributions to society if they are healthy and dynamic; they can provide economical and societal benefits. This concept is called ‘healthy ageing’ and analytics can play a big role in it. The World Health Organization (WHO) defines healthy ageing as “the process of developing and maintaining the functional ability that enables wellbeing in older age”.

Active ageing is a multidimensional concept referring to a situation where people continue to participate in the formal labour market, engage in unpaid productive activities, and live healthy, independent, and secure lives as they get older. I would advocate for active ageing policies to address all the following dimensions: enabling possibilities for longer working life, ensuring social involvement, encouraging healthy lifestyles, and providing opportunities for independent living for both men and women. In addition, the domains which have been identified as drivers of healthy ageing by the WHO are: employment; participation in society; independent, healthy and secure living; and capacity and enabling environment for active ageing.

Why should governments care about healthy ageing?

John Maynard, an industry advisor in the SAS Global Fraud & Securities Intelligence team: We can throw money at a problem but not solve it. So, the real question is: how do we create a sustainable system? The silver tsunami is here. How much does it cost to take care of someone who is 20 vs 75 years old? In the USA, we spend the most money, but we do not have the best results in terms of a healthy elderly population.

More specifically, access to better quality care is key for healthy ageing. Seniors need better preventive care and care management for disease to maintain their health. These are essential for both containing healthcare costs and promoting quality health outcomes for seniors. Governments and healthcare systems can support these goals with more effective analytics. This includes assessing and understanding social determinants of health and health equity.

Lars Kirdan, Nordic director of business development at SAS Institute: In a lot of countries, the taxes collected every year directly finance the state pensions. If the number of people in the workforce shrinks and the number of pensioners grow, the burden on society to finance it will grow both in a relative and absolute sense and take funds away from other investment areas. There is a growing political pressure to shift resources towards climate, defence, education, and other priorities. There is also a growing number of voters who are 60+ so politicians will need programmes that address quality of life and healthy ageing. We must introduce analytics into this agenda because investment alone won’t solve this problem. My answer to this is something I call: personalised and compassionate ageing.

We need to think about ageing as an information problem, not a healthcare, economic nor societal problem. To advocate for compassionate ageing – and to make the right decisions – we must gather the data related to a life: data about healthcare, or jobs, or where people live when they are older, and more. And as we say at SAS, having the data and integrating it is only a first step. One needs to apply analytics. With unsupervised machine learning techniques, we can ask new questions. As a result, we can start with the early indicators and alerts, move to assessment and root cause analysis and finally adapt to drive personalised interventions supported by data and analytics.

Lars just spoke about how data analytics can be used to improve care for the elderly. How do you think technology – especially data-driven analytics – can address those issues and more particularly the gap in social and familial support for elderly people?

Mark Wolff, an advisory industry consultant for SAS Institute’s Global IoT Division: As John said, spending money does not always solve the problem, especially within governments. The answer should include the use of technology for efficiency and cost reduction but also the use of new technologies that Lars mentioned such as artificial intelligence, machine learning and natural language processing. Imagine for a second if we could start channeling those technological advancements into this problem, it would bring very exciting opportunities. How do we adapt and adjust that technology for the specific application of improving the lives of the elderly? The population is undoubtedly shifting, and isolation and loneliness are becoming significant challenges. From a governmental perspective, ensuring a quality of life for the elderly is a critical mission. However, the solution to these issues cannot solely rely on increasing spending.

John Maynard: Independent living for seniors means remaining in the community. Yet, that often requires some supports to assist with activities of daily living like personal care, medication management, and food preparation. Here, analytics can be used to measure access to these services and patient wellness. Governments can promote the adoption and use of advancing smart technologies to help seniors remain in the community. Hospitals and nursing homes are expensive to build and maintain. Given the growth in senior numbers, there will likely not be enough capacity to adequately serve seniors in such institutions.

In addition, governments around the world at all levels are bringing their collections of data together to have a single portal which allows them to understand a citizen, their involvement with the government, and needs. These initiatives will benefit senior citizens as governments develop a data-driven view of the current state of senior populations, current health service needs, actual health services access, and related gaps. With this information, governments would be able to determine the technology and policy changes to best fill gaps. Additionally, governments should be able to use predictive analytics using AI to forecast future needs as senior populations grow and life expectancy increases. Healthy ageing is the goal, and analytics is key to effectively balancing the needs to this growing population.

More specifically, how can analytics help the elderly at home?

John Maynard: Smart homes incorporate advancing technology like connected devices, sensors, and remote video to assist seniors and their families. The New York Times recently ranked their top 15 technologies for smarter homes for seniors. As artificial intelligence and machine learning advance, we can expect greater capabilities with increased ease of use.

For example, computer vision is being explored to help monitor homes of seniors for signs of potential trouble such as falls or seniors in distress. The goal is to avoid the need for seniors to call for help, as this is sometimes not possible. The use of computer vision and machine learning for visual tracking has several benefits. It supplants the need to have other humans present to perform monitoring which is particularly useful as the shortage of home healthcare workers has driven up the cost for assistance.  Also, automated monitoring promotes senior privacy. The hope is for artificial intelligence to identify distress and only then call for necessary human intervention. It is anticipated that the data collected from a network of sensors at home will feed predictive machine learning models and analytics to identify patient health changes and avoid acute patient issues and distress.

Seniors often need short-term rehabilitative services to recover from acute illness and return to the community. Others may need permanent skilled nursing care in a facility. Analytics can help measure and address gaps in accessible facilities. In the US, the Centers for Medicare and Medicaid Services (CMS) used text analytics on long-term care and rehabilitative facilities quality assessment reports. The effort turned large swathes of unstructured data into structured data. Analytics were then used to identify specific quality-of-care risks, and ultimately, pandemic readiness and response for items like personal protection equipment and infection prevention. This allowed local governments and health systems to better respond to the emerging COVID threat to keep patients, who were most often seniors, safer and help them return to the community where possible.

How can analytics protect the elderly from being victims of scams, fraud, and abuse and/or violence?

John Maynard: Fighting fraud is essential in helping seniors maintain financial independence. Governments should adopt technology-based solutions, while promoting private sector adoption of such solutions in both finance and healthcare, to help keep seniors safe. Recognising fraud exists in any system and fighting that fraud is necessary to ensure the long-term financial health of our healthcare systems. Fighting fraud is also essential for healthy ageing by working to ensure healthcare quality and health outcomes goals are achieved. Providers that are solely focused on money cannot maintain the patient focus necessary to help seniors support their healthy ageing goals. Likewise, governments should educate seniors about fraud schemes, such as those emerging deepfake voices, to raise awareness and help seniors understand how such technology may be used to defraud them.

What should the public sector be thinking about in regard to healthy ageing objectives?

Andrea Covino: I think the COVID-19 pandemic taught governments and the private healthcare systems that we cannot “play catch-up” in the middle of a crisis. That costs us many lives. Therefore, we need to move quickly to gather the data and apply the advanced analytics available to help us to be more prepared for not only an acute health crisis that arises but the silver tsunami that is a known challenge that has already begun.

Healthy ageing is a complex problem area that demands innovation and deployment of real-world IT solutions in several areas, more specifically in employment; participation in society; independent, healthy, and secure living; capacity; and enabling environment for active ageing. The question I would like to ask is: what can technology do to help us make better decisions? It seems like there is no right or easy solution but what is sure is that we are not moving at the pace that we could and should be moving. We could be doing so much more.

Interviewer and interviewee bios

Dora Rencoret is a Franco-Finnish public sector marketer and industry leader at SAS. Based in London, she works with global teams to propel SAS technology forward in governments across the world.

John Maynard is an industry advisor in the SAS Global Fraud & Securities Intelligence team and brings over 30 years of experience with healthcare and insurance programmes. Prior to joining SAS, he worked directly in public and private healthcare, with insurers, and in government social benefits programmes where he focused on compliance, fraud control, and redesigning processes using analytics to promote efficiency.

Andrea Covino is one of the SAS public sector leaders in Italy. Andrea has nearly 20 years of experience in different management roles including business and IT advisory and system integration, and focuses on how IT can help public administrations transform and improve the way they conduct their business and create value for citizens.

Dr. Mark Wolff is an advisory industry consultant for SAS Institute’s Global IoT Division. He has 30 years of experience in the health and life science industries as a scientist and analyst working in the US and Europe. Wolff is recognised as an accomplished practitioner, thought leader and lecturer in the development and application of advanced and predictive analytics.

Lars Kirdan has more than 25 years of senior management and board experience from both the private and public sectors. He has been the Nordic director of business development at SAS Institute A/S since 2018.


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