t’s no secret that the lack of shared resources and communication between health providers and payers presents a major challenge to the delivery of quality healthcare. Nashville-based startup XSOLIS (pronounced similarly to “excellence”) uses machine learning to support the administrative side of healthcare — something known to keep medical providers and support staff away from the parts of their jobs patients actually pay to receive.
The SaaS platform provides predictive analytics derived from cognitive learning to determine medical necessity and revenue risk for patients in real time. This information helps caregivers deliver what CEO and co-founder Joan Butters calls “unbiased, efficient care determinations and streamlined utilization management processes.”
“Through the application of tech and analytics, XSOLIS manages the financial side so clinicians can get back to the appropriate care necessary to the patient,” says Butters.
XSOLIS identifies gaps and improves efficiency via utilization management, or the assessments made before and during provision of care in order to measure its necessity, appropriateness, and management of cost. By providing records to both payer and provider in a digital form, rather than handwritten documents, processes become more transparent and move more quickly as a result.