Jesse Montgomery is Head of US Healthcare Customer Success & Value Engineering here at Shift Technology.
In this installment of the “Four Questions with” series we talk with Jesse about his career path, current challenges in the healthcare payment integrity landscape, and his best advice for health plans getting started with AI/GenAI in payment integrity.
Shift Technology: Tell us a little about your background, and what brought you to Shift?
Jesse Montgomery: Growing up, I couldn't decide between a couple of different career paths: computer science, nursing, and law enforcement. These fields sound very different, and they are, but each had a unique appeal to me. Nursing was ruled out because I wasn't a big fan of blood. My mom, a police officer, suggested law enforcement, but it didn't feel safe to me. So, computer science it was—something I had a passion for from an early age. I started teaching myself how to program and write my own code before it was cool. I got my first computer when I was 13, and we don’t need to talk about how old that computer was!
Throughout high school, my interest in computer science only grew. Moving in this direction felt like the right path. I initially began my healthcare career in the field of subrogation. A few years later, I had the opportunity to join a startup focused on innovative healthcare solutions. When I started there, my background in subrogation and application development was clear. During the interview process, I was transparent about not knowing much about healthcare, but I was eager to learn. They called me half an hour after the interview, offering me the job. This was the perfect blend, and I spent nine years helping them grow in the payment integrity and fraud, waste, and abuse space.
From there, I helped several other health plans advance their claims processing and payment integrity capabilities. I enjoyed helping plans build entirely new payment integrity departments and platform solutions. I’ve been passionate about figuring out how all the pieces come together, from solutions to analytics to operations.
What brought me to Shift was a series of discussions that highlighted their passion and vision for the industry. Meeting with Jeremy and Arnaud was a turning point. Their dedication to making a significant impact in healthcare was evident, and our initial hour-long meeting turned into a day-long conversation. Jeremy sought my input on where healthcare was going and what Shift could do differently, and I saw in him and Arnaud a shared passion. Working with people who are dedicated to making a change in the industry, especially in fraud, waste, and abuse detection, was a key factor in my decision.
Shift being an international organization offered the potential for global collaboration and access to new information, which was very intriguing. My research often involved reviewing different healthcare operations globally and exploring ways to integrate those insights into my work. Being part of an organization engaged in payment accuracy in healthcare and other spaces on a global scale was an opportunity I couldn’t pass up. It’s one thing to read about how things are done in different markets, but it’s entirely different to be part of an organization that's doing it and seeing it firsthand.
Shift Technology: What are the most significant challenges you see in the current healthcare payment integrity landscape, and how do you believe AI can address these issues for plans?
Jesse Montgomery: Great question. In AI, I see a lot of opportunities to evolve healthcare holistically. As these technologies evolve and interact with healthcare holistically, its role in payment integrity is going to become greater and greater. We're able to do new things and find new patterns. From a payment integrity perspective, AI helps plans move closer to real-time adjudication, allowing them to pay quickly. Without AI, we wouldn't be able to keep up.
AI, especially with Transformer models behind it, can find things faster and more efficiently. Outliers and anomalies that may have taken weeks or months to find can now be identified significantly faster, or even instantly, with the use of AI. This speed is crucial. As generative AI is used to fabricate things like medical records and claim data, finding and addressing these issues without generative AI would be impossible. We need AI to combat the misuse of AI, to ensure that we can detect and prevent fraud and abuse.
The biggest challenge is the rapid evolution of patterns and practices. Staying on top of these changes is very difficult for any payment integrity organization. There's a constant need for additional resources, and everyone is trying to do more with the same or less. Generative AI empowers organizations to do more with the same resources. It doesn’t replace clinicians, analysts, or investigators but enables them to work faster with higher accuracy and precision.
For example, in medical record reviews, AI helps target specific hospitals for DRG audits more precisely. Without AI, you might recover significant amounts but at the cost of reviewing many claims. Using AI, you can achieve the same results with more precision and less disruption. It's like using a precision tool instead of a sledgehammer—you get the same results but with less damage. This precision is crucial for maintaining good relationships with customers and networks.
Organizations face policy changes, industry changes, coding changes, and new procedures constantly. They want faster and more accurate claims payment. AI and generative AI will be the tools that enable us to achieve this efficiently.
Shift Technology: Where do you feel payment integrity is headed? What AI or other tech innovations do you think will be pivotal in shaping this future?
Jesse Montgomery: I think payment integrity is heading toward being near real-time. Some large national insurance organizations want to process claims and have payments ready by the time a member leaves the office. Payment integrity will have to evolve to make those real-time decisions about incorrectly coded or potentially fraudulent claims, similar to how credit card transactions are authorized on the spot.
Right now, many organizations have weeks or even months to ensure payment accuracy. But as we push for prepayment processing, we’ll need to be able to do this in seconds. This shift will require robust AI systems and significant improvements in underlying technology.
AI will play a big role, but we also need more data sharing, with things like fee schedules and other content becoming more accessible. The technology used by healthcare systems, claims processing platforms, and Electronic Medical Record solutions will need to evolve. The key will be interconnectivity across these solutions. Hospital systems will need to communicate directly with EMRs, and EMRs will need to connect seamlessly with payment integrity organizations.
As the space evolves, this level of connectivity will be crucial. It's about making sure all parts of the healthcare system can talk to each other in real-time, allowing for quick and accurate decisions on claims. This will not only improve payment integrity but also enhance the overall efficiency of healthcare delivery.
Shift Technology: What’s your best advice for health plans getting started with AI in payment integrity?
Jesse Montgomery: My recommendation for health plans or anyone looking to leverage AI for payment integrity is to understand the technology and its potential thoroughly. AI isn't a one-size-fits-all solution—it comprises various models and solutions that require careful consideration.
Begin by educating yourself and your team on AI's capabilities and applications. If necessary, seek out knowledgeable partners who can provide guidance tailored to your specific needs. Whether you're approaching payment integrity holistically or focusing on the use of generative AI, clarity and understanding are crucial.
Start with targeted use cases. Identify specific pain points within your payment integrity processes and pilot AI solutions to address them. This approach allows you to validate the technology's effectiveness in real-world scenarios and build momentum for further implementation.
Avoid the temptation to tackle everything at once. While AI can uncover insights and efficiencies, overwhelming your team with too much complexity too soon can hinder progress. Instead, use initial successes to inform and expand your AI initiatives strategically.
By taking a focused and gradual approach to integrating AI into payment integrity, health plans can maximize its benefits while minimizing risks and disruptions.
