| Feature Story |
Health Care’s Quest for a Clean Claim Experts weigh in on the power of AI and predictive analytics to improve denials. Revenue cycle professionals have prioritized claims accuracy and compliance as a process improvement priority for decades. Many agree that while the challenges associated with submitting clean claims haven’t changed much, they have certainly gotten more expensive. According to Raja Yogeshwarar, executive vice president of growth and strategy at ECLAT Health Solutions, denials resulting from documentation that doesn't fully support the billed code level, medical necessity gaps, missing prior authorizations, and coordination-of-benefits errors remain the usual suspects. The less obvious problem is inconsistent coding patterns across providers or departments that don't look like bad claims individually but eventually surface as a trend a payer algorithm flags. "The problem is that, traditionally, health systems find out about them in the denial or the audit letter, months after the patient encounter, when the medical record is cold and the staff who documented it may not remember the details," Yogeshwarar says. Featured Articles
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