Imagine a world where healthcare is both accessible and affordable to patients. Where providers can diagnose and treat illness proactively rather than reactively. Researchers can predict and mitigate pandemics and outbreaks before they even happen. And payers can deliver better experiences to both providers and members in a shorter time and with less hassle. Imagine the ideal healthcare system, where each player can realize their ambitions and create value for the industry as a whole. This is the art of possible.

The healthcare industry today is working toward this ideal state. Its movers and shakers are looking for new ways to solve old challenges, amplify potential, and make life better for everyone. To that end, the technology revolution has enabled humanity to make great strides in diagnosis and treatment, in the development of tools to diagnose and treat illness, and in our understanding of how humans and the world around us work. But technology has only been able to take us so far, until now. This is where generative AI comes in. Never before have we had the ability that we do at the present moment to process large volumes of data in seconds, find patterns in seemingly disconnected information, free ourselves from time-consuming, repetitive tasks, and focus on the bigger picture. Therefore, it’s not surprising that enterprises across industries are excited to explore what this technology can do for them.

At Virtusa, we’re excited to see how generative AI will reshape the healthcare industry and impact members, payers, providers, biopharma, medical device, and HealthTech companies. In this blog, we discuss Virtusa Helio and our solutions for payers and providers.

AI A domain-driven approach to generative AI

Virtusa has always worked with healthcare and life sciences enterprises, innovating the tools to shape tomorrow’s landscape. Many of these solutions already use AI to help improve efficiency, optimize processes, and enhance productivity. With generative AI, too, we have adopted an engineering perspective, building solutions from the ground up for every industry under Virtusa Helio.

Over the past year, our teams have explored and identified a host of generative AI use cases for healthcare players. For payers, these range from a digital broker for marketing operations to automated policy administration to content refinement for empathy and inclusivity. Similarly, for providers, the solutions are wide and varied, ranging from an ambient AI scribe to auto-generating personalized patient education materials to clinical condition diagnosis. We know that we are only scratching the surface of this technology that everyone is so excited about.

‘Generative AI can make any experience around information frictionless.’

A bold statement, but one that we believe to be true, and the evidence holds up so far. Already, the aforementioned Digital Broker solution, an augmented marketing solution, is in production, with the capability of identifying the right product and add-ons tailored to individual or collective needs for B2B and B2C organizations. Its applications also extend to making personalized product suggestions for members who have failed Medicaid redetermination.

Another interesting – and, in our opinion, critical – solution is the Digital Prior Authorization offering for Care Management. It uses generative AI to generate prior authorization requests or recommendations based on natural language processing (NLP) analysis; checks if prior authorization is needed and initiates requests; makes recommendations for documents needed; retrieves the prior authorization status; and even suggests alternate treatments or medications that would have a higher likelihood of approval or that are more affordable. The benefits include an enhanced member experience and reductions in claim denials — and the accompanying administrative burden — for healthcare providers. The solution that we are rolling out for provider networks addresses the challenges of choosing the right contract. It harnesses AI and NLP to recommend the most suitable contract model based on factors such as type, specialty, location, line of business, network type, and past performance. Returns on this solution are both tangible and intangible, with reduced cycle time, improved negotiation effectiveness, and better payer-provider relationships.

We are also exploring new ways of driving engagement with members using AI and ML-driven models to manage new member onboarding, create personalized health recommendations, generate bespoke telehealth plans, and generate personalized health education materials. The goal is to enable members to be proactive about their health and well-being and drive customer satisfaction in the process.

These are just a few examples of how we’re using generative AI to reshape experiences across the value chain. In the life sciences arena too, we are exploring new ways of consolidating data across geographies, formats, and languages to accelerate discovery, using generative AI to empower healthcare providers to track and proactively address patient needs, and working to empower patients themselves to be able to take their health into their hands. There’s certainly much more to come in the not-too-distant future, as the diagram below shows.

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