Maximizing Efficiency and Patient Care With Generative AI

Featuring Venkatgiri Vandali, President of Healthcare and Life Sciences, Firstsource

I'm Venkatgiri Vandali. I go by Giri. I'm the president of Healthcare and Life Sciences at Firstsource. I've been here for 4 years. Educationally, I'm an engineer by training. I grew up working in engineering before I fell in love with health care about 15 years ago. I love this part of the industry where we help patients access better care. 

What is generative AI and what role can it play in managing health care data? 

I’m very interested in what has happened with generative AI in the last year or so. Generative AI is a collaborative AI ecosystem where you work with technology to solve problems. This is changing how we work with data. It’s a phenomenal invention and probably one of the best inventions of the decade. 

In terms of delivering business results, how can generative AI positively impact the payer space? 

In many ways. The beauty of AI, and specifically generative AI, is the ability to bring in a tremendous amount of democratization to health care. If we examine the utilization levels of most providers today, generative AI could dramatically decrease the amount of time they spend in creating documentation. This is important because faulty documentation leads to inefficiency in the system. 

I've seen studies where providers or doctors report spending almost 60% of their time creating documentation and conducting required research. That time spent could dramatically come down once generative AI utilization goes up. This drives time saved on these mundane activities and make providers more available for patient care, which will create a lot more access to patients and a better health care system.  

At the same time, there's tremendous amount of work on the payer side which is administrative in nature such as prior authorizations, claim status reporting, benefit verification, and benefit explanation to members and providers. With AI tools, all of that can go into a “co-pilot mode”. People can get their questions answered by working with technology instead of waiting on a contact center or chatbot which take some time to get information, or the quality of information may be suspect because it is sourced from static data versus generate AI. The quality of outcomes will improve tremendously, which will drive a different level of efficiency for the entire ecosystem, which will make payers serve their members and providers a lot more than what they can do today. I personally believe this invention will change both lives of patients and, at the same point of time, profitability levels of payers or health plans. 

From a payer’s perspective, what would generative AI offer to help encourage medical coverage across plans? 

Today, the biggest pain for health plans is medication adherence. An inability to adhere to medication leads to patients being readmitted to hospitals and a tremendous amount of expenses. If a bunch of AI companions are created, this could increase wellness discipline for members. That alone drives a big amount of savings for health plans. 

How health plans will work with their members will change. AI can lend tremendous value to the entire care management ecosystem, whether it is case management and disease management. AI could help patients to better monitor their health and provide input for more timely interventions. This will drive a lower cost for providers as well as payers while also improving care. 

As data is accumulated and AI systems learn more and more, providers’ ability to personally treat patients differently based on their history, based on their genetics, based on constantly changing vitals and diagnostics, will lead to a very personalized level of care. The cost of care will come down, effectiveness of care will go up, and these changes wil improve accessibility of care for more and more people. That's a tremendous change that's in front of us. It's only a matter of time that we will start to see this playing out. 

What kind of overhaul is required to implement generative AI as a standard practice in health care settings to maximize patient care and ensure payer coverage for treatments? 

In my mind, the journey has just started. The biggest obstacle in the process of making generative AI successful is the quality and the quantum of data that is sitting out with in the ecosystem. Because of non-standardization of data, our quantity of data that is available in the system is limited. Until that data gets structured well, stored well, and made available for learning to AI models, it will be a struggle to get to an effective utilization of generative AI and make it successful.

The journey of investing in cleaning up the existing data and structuring it better will take time. Generative AI is all about how much data your AI models need to learn and how will you use it? Until that gets sorted out, I see it still as an inefficient system and that's the priority with which both providers and payers need to look at it, how they can structure their data better. 

What is one key takeaway you want the audience to walk away with from this interview? 

One takeaway I want to leave the audience with is that we have a tremendous amount of change that is coming soon. It's important in health care industry for us to adopt this new technology and it’s maximized value. It's a significant innovation that has happened in the last 18 months in front of us. This can change how we do things in health care and how we solve problems. The health care industry is going through a global transformation as the world is only getting older and sicker. It is important we prepare ourselves to the coming changes and adjust our ways of doing things so that we can be more efficient and effective.