How Xsolis Is Turning Provider-Payer Tension into Teamwork with AI

In healthcare, the tug-of-war between payers and providers often leaves patients caught in the middle. Xsolis is flipping the script with its AI-driven platform designed to bring payers and providers onto the same page. Here’s how.

The complex relationship between payers and providers has long been a friction point in healthcare, leading to administrative waste and delays in patient care. At the ViVE2025 event (#ViVEvent), Zach Evans, Chief Technology Officer at Xsolis, showcased how the company’s real-time AI insights are creating measurable improvements in efficiency, care quality, and cost management.

Tangible Results

Three standout case studies were presented by Evans to highlight the positive impact the company’s AI-platform, Dragonfly – drviving efficiences and reducing friction.

By integrating Xsolis’s AI platform, MultiCare Health System, for example, reduced the time to complete case reviews by an impressive 150% and saved $8 million in just one year.

West Tennessee Healthcare saw similar gains. Since implementing Xsolis, they have saved $5.1 million and reclaimed 205 hours in administrative time in just six months. But perhaps the biggest win was the transformation in their payer relationships. Instead of constant back-and-forth, there is now better alignment, letting both sides focus on improving outcomes rather than arguing over paperwork.

Finally, there was Beacon Health System, where Xsolis delivered a jaw-dropping 22x return on investment, fostered stronger ties with health plans, and boosted the number of daily patient reviews by 140%.

Care Level Score

Xsolis’s approach uses AI, machine learning, and data science capabilities in its Dragonfly platform to sreamline decision throughout the care continuum. The guiding force is Xsolis’ Care Level Score™ – an AI-driven prediction that objectively gauges a patient’s need for inpatient versus outpatient care.

To arrive at a patient’s Care Level Score, Xsolis analyzes clinical data from the EHR and other data sources in real time. An AI algorithm consumes the data to generate a numerical score between 0 and 157. The higher the score, the stronger the alignment with inpatient care – versus, the lower the score, the stronger the alignment with outpatient care.

The Care Level Score helps providers and payers align on the appropriate level of care from the start, minimizing the need for manual reviews and reducing medical necessity denials. “It’s about connecting the dots between clinical data and payer requirements in real time,” explained Evans.

For example, by looking at historical data – what have been clear inpatient versus observation determinations that both parties agreed on – payers and providers together can decide on Care Level Score thresholds that do not require review. This process is described as Precision UM, automating appropriate cases to save time and create more clinical focus on the outlier cases. The Care Level Score also provides a common language for payers and providers, easing negotiations.

Better Collaboration = Better Care

Xsolis’s AI approach is pragmatic and addresses a true need. Their solution is an example of how AI can meaningfully reduce friction, improve patient experiences, and drive real financial results. With its Care Level Score enabling better alignment on medical neccsity decisions as well as other predictive models designed to improve Length of Stay and transitions of care, Xsolis is helping healthcare organizations move away from administrative tug-of-war to genuine collaboration. When payers and providers collaborate, better care is the result.

Learn more about Xsolis at https://www.xsolis.com/