This article was originally published in the Journal of mHealth magazine in the February / March edition on Artificial Intelligence in Healthcare.
As the future of the Affordable Care Act hangs on the balance, insurance companies are bracing for what comes next. A recent paper issued by the Urban Institute explores the implications of various repeal scenarios on insurers, which range from market withdrawals, destabilization and increased premiums. In the midst of every scenario, there is one thing that will not only remain consistent, it will be paramount: adjusting to the changes without losing ground requires that insurers transform their business processes to remain efficient and competitive while they switch to the new world order.
“At Lumiata, we believe that insurance companies, by the very nature of their operations and influence, are poised to lead the way in adoption of AI, and our conversations with payer executives reinforce this belief.”
With the explosion of data and significant advancements in machine learning, the best means to transformation is through artificial intelligence (AI). But AI can be an ambiguous concept that conjures confusion, awe anxiety and excitement. In an industry that has been a relatively late adopter of AI, where does one begin?
It first starts with understanding current, demonstrable applications. AI is not magic. With the breadth of labor-intensive administrative tasks in healthcare, there are specific AI applications that have the potential to impact revenue, cost, and business decision-making. It also requires a mind shift that actively seeks a new, innovative way of operating: from business-as-usual to business-for-the-future; from slow-moving transactions to fast, efficient, automated interactions; from blunt analytics to precise insights; from one-size-fits-all outreach to highly personalized, nimble engagement and care.
At Lumiata, we believe that insurance companies, by the very nature of their operations and influence, are poised to lead the way in adoption of AI, and our conversations with payer executives reinforce this belief. Insurance companies are one of the primary fulcrums in healthcare delivery and access. Their business processes and decision-making have direct implications on the entire value chain; applying AI to these two specific areas could swing the pendulum toward better, more affordable healthcare.
Insurance companies have also been dealing with large data sets for years. Their back-offices – the main sites of data aggregation – are fertile ground for AI to make an impact. They are overloaded with costly and labor-intensive tasks, routine and repetitive processes that can be automated, and that require some level of clinical insight. Additionally, insurance companies have been operating under mounting regulatory and policy pressures throughout the Affordable Care Act, forcing them to seek innovative technologies that put their data to work and transform those back-offices into engines of value.
“There are a number of business processes in those back-offices where AI could be transformative: customer service, care coordination, prior authorization, predictive analytics, underwriting, to name a few.”
During that same period, there has also been impressive progress in computer science, particularly in machine learning, computer vision, natural language processing, speech recognition and robotics – technologies that could be game-changers for business processes in health plans. With these forcing functions already in place, the payer back-office – that dark place laden with heavy costs – is perhaps the greatest point of opportunity and impact for AI. There are a number of business processes in those back-offices where AI could be transformative : customer service, care coordination, prior authorization, predictive analytics, underwriting, to name a few.
Pilot projects by researchers and a few health plans point to high-value, low cost experiments that can result in demonstrable value. For example, prior authorization – a costly and time-consuming process that can cost a large health plan up to $90 million annually – can be automated using machine learning, which provides recommendations within seconds as opposed to three to five days when performed manually. Virtual health apps that use text-to-speech and search technologies are being deployed to improve customer service interactions with members and patients. AI can also help executives improve their business decision-making and strategy through continuous (rather than episodic) risk stratification that helps them gain competitive advantage by revealing precise utilization trends and reimbursement patterns, and driving more timely and cost-effective care coordination and disease management.
Numerous studies are also showing promising accuracy of AI in improving payer-provider collaboration: because AI can tackle the inevitable heterogeneity of data in healthcare and be more clinically precise, it can help payers determine which providers to reach out to for specific and urgent patient outreach. It can also help providers be more precise with their care choices, coordinating care in a way that reduces waste, and align priorities between payers, providers and care managers.
“AI can also help executives improve their business decision-making and strategy through continuous (rather than episodic) risk stratification.”
As we look to the future, AI can help payers thrive in the midst of a lot of uncertainty. We foresee three trends that payers are likely to encounter in the coming year, and the role of AI in helping them pave the path toward better, more affordable healthcare.
These trends are not new, but in the new policy environment, they will demand greater leadership from insurers. And as always, in times of change, it’s either evolve or go extinct. For businesses today, that means embracing new technology and AI or getting left behind with legacy systems. At a time when the future of the industry is once again shrouded in uncertainty, practical AI applications that are ripe for deployment can empower organizations to focus on growing their business, rather than playing catch up and administering it. If payers lead the way in adopting AI, it can help them unlock their potential to be the platforms of tomorrow’s healthcare, in spite of the uncertainty that lies ahead.