Addressing Payer/Provider burden with new AI tools
Utilization management (UM) is a key component in patient care and the approval process between providers and payers. Often this process is a source of friction between providers and payers when prescribed care is denied by a payer. In these cases, the process can result in increased administrative burden and frustrations for all stakeholders involved. In this white paper, we examine the role of AI in automating part of the UM process that not only decreases the administrative burden, resulting in time savings, but can help facilitate trust between payers and providers.
The XSOLIS platform deploys machine learning in a manner where patients exhibiting risk scores below a certain threshold can be automated while UM reviewers can devote time to higher risk cases. The result is savings in terms of time and costs, as well as alleviating some of the human resource challenges when clinical care resources for UM processes are a scarce resource.
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