The Future of Collaboration: Building Bridges Between Payers and Providers in the Age of Healthcare AI

One big problem for healthcare providers is that claim denials have been rising. This affects how money comes in. From 2020 to 2023, denial rates went up from 10.15% to 11.99%. Inpatient hospital care denials were even higher, reaching 14.07% by late 2023. This shows that payers are checking claims more closely using AI to handle and standardize the process.

Hospitals and health systems have lost a lot of money because of these denials. About 35% of these groups report losing more than $50 million due to denied claims. These denials slow down or stop payments for services already given.

Medical practice administrators and IT managers have more work now. They must handle resubmissions and appeals. The time it takes payers to answer claims grew from around 14-30 days to between 14 and 60 days. This causes problems with cash flow and budgeting.

Healthcare Providers’ Response: Investing in AI and Automation

To fight rising denials, many healthcare providers plan to use AI themselves. Nearly two-thirds of healthcare groups say they will spend more on AI in the next three years. They want AI to help with tasks like clean claim submissions, prior authorization, and denial handling.

For example, Luminis Health used robotic process automation and machine learning to cut their work queues by 15% to 20%. Care New England used AI bots to notify payers during patient admission. This helped reduce authorization denials by 55%. They saved labor and reached nearly 83% clean submissions for prior authorizations after one year.

Corewell Health saved $2.5 million by using AI to improve revenue cycle tasks. Mayo Clinic found that AI bots can do manual work like writing appeal letters and checking claim statuses. This frees up staff to focus on harder problems and lowers staff needs.

These examples show a trend: AI is helping balance the work between providers and payers by automating denial management and authorization tasks.

The Importance of Strategic Collaboration and Communication

Even with AI’s power, experts say technology alone can’t fix everything. Good communication inside healthcare groups and between payers and providers is very important.

Krysten Blanchette, Vice President of Revenue Cycle at Care New England, says that AI is used to help people, not replace them. She says, “The message to our team has always been that we use AI to supplement our work because we can’t do it all.”

Nikki Harper from Mayo Clinic also stresses clear communication. She says teams need to talk about expectations, results, and how to keep improving. Both provider and payer staff must be trained and informed about changes in workflows.

Being open with payers matters too. Since payers use AI to apply stricter rules that increase claim denials, sharing data and feedback clearly can reduce misunderstandings and align goals between the groups.

Mayo Clinic created the Mayo Clinic Platform to connect providers, payers, technology makers, and researchers. This platform offers data safety, testing, and tools that help AI meet healthcare needs safely and well.

The platform puts people first. It aims to give clinicians more time to care for patients instead of doing admin tasks. This kind of teamwork shows that AI needs partnerships and trust, not just technology.

AI and Workflow Automations: Enhancing Efficiency in Revenue Cycle Management

AI is very useful in automating work in revenue cycle management, especially in front offices. This includes automating phone calls, prior authorization, checking claim status, and handling denials.

Companies like Simbo AI offer ways to automate answering phone calls in medical offices. This lowers the burden on staff so they can focus on patients. These AI systems can handle appointments, check insurance, and answer patient questions, making things easier for patients and staff.

Automated prior authorization systems help cut down denials. Care New England’s AI bots that notify payers during admissions cut denials by more than half. This shows automation can make one of the hardest parts of revenue cycle work faster and better.

Also, robotic process automation and machine learning check claims before sending them. This finds errors and makes claims cleaner, lowering resubmissions and denials from mistakes.

AI bots also help with writing appeal letters and tracking claims in real time. Mayo Clinic says their AI tools replaced work equal to about 30 full-time staff members, saving costs.

IT managers and practice leaders must add AI carefully to current systems. This means choosing tech that works well with practice software and electronic health records, while following laws like HIPAA.

Corewell Health plans to use new tools like generative AI to predict which claims might be denied. This way, providers can fix problems before sending claims and save money.

Using AI with regular staff training and working well with payers helps improve revenue cycle management over time.

Bridging the Gap: Collaboration as the Key to Future Healthcare AI Success

Providers face many problems now, like more denied claims and tougher payer checks. These issues need more than technology alone to fix.

The way forward is through better teamwork between providers and payers supported by AI and shared tools.

The Mayo Clinic Platform shows this idea. It brings together health systems, payers, and researchers to help AI grow in healthcare responsibly. It offers data sharing and testing to support providers in using AI safely with help from different groups.

Other healthcare groups also use AI to cut admin work and losses, while improving talk and teamwork with payers. When AI helps humans instead of replacing them, and savings go back into improving AI, the industry can better handle denied claims and money risks.

Even though payers use AI to tighten controls, providers have ways to fight back. Investing in automation, better workflows, and partnerships helps manage risks.

Medical practice administrators and IT managers in the U.S. should know that success needs both technology use and clear communication inside teams and with payers. Working this way helps keep money steady and ensures patients get good care without interruption.

This changing healthcare world is complex but workable using AI and team approaches. For providers in the U.S., using AI automation and working well with payers offers a way to have smoother revenue cycles, less denied claims, and better patient results.