By Venkatgiri Vandali, president of healthcare and life sciences, Firstsource.
AI is a natural fit in multiple functions across the health plan value chain. In 2025, more plans will deploy generative AI in claims operations, the contact center, quality assurance, training and more.
These areas will become more efficient. In addition, health plans that use AI tools to solve perennial pain points, make employees more productive and deliver better member and provider experiences will start to pull away from competitors.
Why are generative AI and related tools such as machine learning able to deliver more value?
In the past, it took a long time for people to refine their requests to get the data they required. It often meant asking IT for help and could take days. Now AI makes it possible to essentially talk to machines and receive content in real time. This creates tremendous efficiency that will lead to cost reduction and ultimately more value for payers and members.
As an example, generative AI tools quickly extract relevant content from emails, claims, contracts, medical records and more. That minimizes the need for staff to look up information, expedites service processes and increases opportunities for automation. These efficiencies can net considerable time and cost savings while improving services.
What are AI copilots and AI agents and how do they help?
AI copilots work alongside humans, looking up information, flagging potential errors and suggesting next best actions. AI agents run in the background. Multiple autonomous AI agents can work together to exchange information and act based on business rules in “agentic workflows.”
An AI copilot could oversee an agentic workflow in which AI agents verify member data on a claim is accurate; check and correct edit codes; then evaluate whether the claim will adjudicate successfully. If the agentic workflow determines there’s an issue with the claim, the AI co-pilot will flag the potential issue for an expert human associate to mitigate.
What are some of the major efficiency gains payers can expect from AI?
Generative AI has the ability to manage massive amounts of data and yet also find a needle in that data haystack. This capability did not exist before generative AI and is invaluable to any operation that requires analytics and where resolution speed is critical. For example, things can go wrong in five million claims for a variety of reasons. Before AI, a payer would have to retroactively identify and correct the issue. Today, generative AI can constantly be talking to the system, monitoring claims, following up, ensuring claims are routed and processed correctly. Generative AI can also recognize when something is wrong. Then it routes the claim back to human stakeholders and alerts them to the problem.
By Venkatgiri Vandali, president of healthcare and lifesciences, Firstsource.
Solving the challenge of containing costs while improving revenue cycle operations despite labor shortages has a direct impact on a health system’s financial health and ability to serve patients. The good news is that automation solutions exist to streamline revenue operations, enabling revenue professionals to work at the top of their skill sets and giving patients better financial experiences.
Here’s a quick look at where and why automation can strengthen cash flow and revenue streams while patients and revenue professionals experience greater satisfaction.
Why should providers be concerned about the financial experience they deliver to patients?
Patients are now responsible for more of their health costs than ever. That means providers collect a higher percentage of revenue from patients. Other service providers—think credit cards, mortgage lenders, online retailers—have trained consumers (aka patients) to expect easy, seamless, digital payment processes. Healthcare payment processes are not easy or streamlined. That makes it difficult for providers to collect from patients, slowing revenues. Patients increasingly will choose healthcare organizations that make it easy for them to understand and pay their bills.
How can healthcare providers improve financial experiences with continuing staffing and cost containment pressure?
Many hospital revenue professionals spend most of their time on tasks that don’t require much skill, such as looking up data in a payer portal or calling payers to check on prior authorizations. Automation can take over those tasks, freeing time for revenue professionals to work directly with patients, offering financial counseling, helping them understand their insurance coverage and calculating their financial responsibility. Automation can also assist professionals in high value activities, such as by checking claims for accuracy before submission and flagging potential errors for review.
What’s the difference between robotic process automation and AI and machine learning?
Robotic process automation (RPA) is proven, cost-effective technology that automates time-sucking repetitive tasks. Using software bots, RPA mimics the keystrokes of human operators—including those needed to switch between applications and systems–and makes simple if/then rule-based decisions. A software bot can usually be trained and deployed in a matter of weeks.
AI and machine learning based automation is more sophisticated and often built on top of the processes and data accuracy improved by RPA. AI/ML solutions manage complex tasks that involve following business rules and making decisions based on the models’ data analysis. Such solutions often are more expensive and take longer to implement than RPA. They are best suited for providers that already have standardized processes and cleaner data from existing automation.
By Venkatgiri Vandali, president of healthcare, Firstsource.
A new generation of health insurers has appeared in recent years, gradually gaining momentum in key markets in part by claiming to offer a more modern, digital consumer experience.
The advent of these modern, tech-driven upstarts bodes well for members of plans new and old alike, who are looking for health insurers to finally begin to offer the levels of customer experience, personalization and convenience they have long experienced in other markets like finance and consumer goods.
Consumers clearly want and expect their health insurance provider to offer the same quality of experience they enjoy in other areas of their lives, and plans that can meet that expectation will enjoy a significant competitive advantage.
They are growing fast, expanding their coverage areas (Oscar has recently expanded to cover 22 states), and successfully creating the impression that they leverage modern technologies, process automation and business cultures in ways that traditional health insurers have not.
However, the reality is that their customer experience innovations have not been particularly sophisticated, and many of the advantages they claim today – such as adopting mobile first strategies for member engagement — can be replicated by incumbent plans.
In fact, large health plans have been moving quickly to adopt new, digital customer experience technologies and business process automation (BPA), and the small- to mid-sized plans are poised to follow suit. Cultural change will likely be the toughest area for traditional health plans to transform, but technology may have a role to play there as well.