HHS confirms what all hospital revenue cycle leaders have known for years!
In April, The Office of the Inspector General (OIG) at the Department of Health and Human Services released a disappointing but unsurprising report. HHS has determined that Medicare Advantage payers (MAOs) inappropriately delay or deny Medicare Advantage beneficiaries' access to services and delay or deny payments to providers for billed services, even though the requests met Medicare coverage rules.
We have a clear view of these inappropriate and confounding denials at Sift. Sift's granular view of the data paints a frustrating picture, even beyond what the OIG identifies. The OIG notes that advanced imaging and inpatient rehabilitation services are the top categories for pre-authorization denials. However, using back-end payments denial data, Sift observes that trends in back-end Medicare Advantage prior authorization denials are rooted in surgery or treatment room charges associated with ED-inpatient admissions but do not necessarily correlate to outpatient procedural services like vein ablation, rhinoplasty, etc., impacted by the expanded 2020 OPPS Final Rule (CMS-1717-FC).
Even more frustrating than the MA payers’ irregular application of inpatient authorization determination from Medicare is their inconsistent use of appropriate CARC codes. Some of these payers use CARC 50 [Medical Necessity]. In contrast, others use CARC 197/198 [Precert/auth missing/exceeded] to deny for the same issue. This makes it incredibly hard to manage coding.
Healthcare providers need to be better equipped to track MA payer trends. The biggest challenge for providers in determining whether or not their contracted MA payers are deploying payment delay tactics is the inability to adequately connect denials data with subsequent payments. Which denials resulted in overturn (both counts and dollars)? Which services are being upheld upon appeal vs being overturned? A clear view of denials and payments trends has become essential for healthcare providers.
Sift’s Payment Intelligence Platform employs machine learning that follows patient accounts from scheduling to payment. Sift scores encounters for their likelihood of denying and provides prescriptive claim predictions with recommended actions to prevent denials while also prioritizing denial follow-up workqueues around ROI. Sift's denials prevention and prioritization are coupled with detailed analytics that equip healthcare organizations to track and respond to denial trends. Sift's analytics identify the root causes of denials, empower functional teams and enable more informed discussions with payer representatives to help improve incorrect adjudications.
To learn more about recent denials trends Sift has been tracking or for a demo of Sift's Payments Intelligence Platform, contact our denials experts at email@example.com.