Delivering the Best of AI for Clinicians
Artificial intelligence (AI) is not new in healthcare. AI has taken a foothold in the clinical domain, including digital pathology and AI-driven next generation sequencing analytics, as well as more recently in speech conversion to clinical notes.
Clinicians’ primary focus is on the delivery of healthcare services. Yet the administrative burden related to coding, claim processing, and ensuring that all billable services are appropriately collected are critical to funding their mission. Clinicians are also increasingly being pressed to reduce the cost of operations and maximize revenue growth while managing missing or incorrect information or payor requirements. These challenges are compounded by labor and supply shortages, which have fueled a demand for outsourced billing partnerships and for best-in-class revenue cycle management (RCM), according to the recent 2023 Black Book report, which rated healthcare information technology company XiFin in the top 10 percent of competitors in each of the 18 evaluation categories.
All too often, claims are rejected or can’t be processed because of missing or incorrect information that can take days and sometimes months to resolve. This phase of the RCM process is sometimes referred to as financial clearance and is an area ripe for AI. Consider for a moment, a patient who has Blue Cross Blue Shield insurance. They provide the subscriber number at the time of service. That number alone is not sufficient to confirm eligibility or benefits coverage and it is essential to providing an accurate estimate of their potential out-of-pocket expenses.
AI applied to this challenge can remove the onus on the patient and the physician by uncovering the underlying payor details. More specifically, to determine eligibility, coverage, and patient responsibility for a particular claim, AI can discover the payor plan details for that claim so that it can be processed without manual intervention.
Leading the AI transformation at XiFin is Senior Vice President of Engineering, Jeff Carmichael, and his Data Science team. Since 2018, Jeff has been leveraging various types of AI and building them into the industry-leading RCM platform.
Jeff and the XiFin team have invested significant effort in structuring the complex RCM data required to develop effective machine learning and AI models. Building upon XiFin workflows that determine if a claim is likely to be rejected because of incorrect or incomplete payor information or patient ineligibility and use automation to resolve most issues, XiFin’s rich and highly configurable AI can then quickly determine probability of reimbursement to help prioritize the claims that still require intervention, and then redirect those needing human attention to the best available team member.
Jeff knows that clinicians got into the lab business to help physicians and other providers solve problems. Saving time and money on these claims tasks means better insights, less expense, and more opportunities to take on additional workloads and deliver better results. Ultimately, XiFin’s AI-powered workflows help clients do more good for more people.
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