Compliance Alone Won’t Fix the Home Health Fraud Problem Presented by Cotiviti

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Featured Story   A Fresh New Slate for Migraine Drugs The deal Slate Medicines, a company that just emerged from stealth early this year, is now joining the public markets via a reverse merger with Nasdaq-listed Fulcrum Therapeutics. Slate’s lead migraine drug candidate, SLTE-1009, is being evaluated in a Phase 1 trial enrolling healthy volunteers. When the merger closes, Slate will raise $245 million form a concurrent private placement to finance that trial and a planned Phase 2 test in migraine patients. Fulcrum had been exploring strategic alternatives since its lead program for sickle cell disease ran into regulatory obstacles with the FDA. The drug Slate’s SLTE-1009 is an antibody designed to block PACAP and VIP, two neuropeptides associated with migraine pain. PACAP-blocking antibodies from Amgen and Eli Lilly fell short in the clinic. This drug class still includes an intravenously infused antibody from Lundbeck in mid-stage development and injectable antibodies from startup Vedana Therapeutics in preclinical development. Slate stands apart from potential competitors with a lead program designed to hit two targets. Why this matters The antibody drugs available for treating migraine block CGRP, a central nervous system protein. But many patients either don’t respond or inadequately respond to CGRP inhibitors. Drugs that block PACAP could give such patients a treatment alternative. Compared to Lundbeck’s intravenously infused PACAP inhibitor, Slate’s SLTE-1009 could pose less burdensome dosing. It's administered as subcutaneous injection monthly and offers the potential for dosing every three months. The merger deal comes six months after Slate launched with a mega-round of financing and ex-China rights to SLTE-1009, licensed from DartsBio Pharmaceuticals. Soundbite “PACAP blockade has shown encouraging clinical data in the prevention of migraine, and we believe the dual blockade of PACAP and VIP with a single monoclonal antibody offers the potential for enhanced efficacy relative to PACAP-only targeting therapeutics,” Slate CEO Gregory Oakes said. “SLTE-1009 was also engineered with half-life extension to enable subcutaneous dosing, with the potential to enable quarterly administration.” —By Frank Vinluan Sponsored   Compliance Alone Won’t Fix the Home Health Fraud Problem Presented by Cotiviti With home health fraud growing more sophisticated through AI, post-pay audits are no longer enough. Payers must shift to proactive, tech-driven prevention to catch improper claims before paying them. Click here to learn more! Top Stories   KFF: Insurers Denied 12%-18% of Prior Authorization Requests in 2025 The news In 2025, Medicare Advantage insurers denied 12% of standard prior authorization requests, Medicaid managed care insurers denied 14% and ACA Marketplace insurers denied 18%, according to a new analysis from KFF. The findings The analysis examined 14 insurers across Medicare Advantage, Medicaid managed care and ACA federally facilitated Marketplace plans, representing approximately 71 million enrollees. It comes after a 2024 CMS final rule that requires payers to publicly post prior authorization metrics like approval and denial rates on their websites. However, the data do not show which types of services are most often denied. KFF found that across all three markets, the median response time was about one day for standard prior authorization requests. For expedited requests, the median response time was about half a day for Medicare Advantage and approximately one day for Medicaid managed care and ACA Marketplace plans. The analysis also explained that denial rates for expedited requests were slightly lower than for standard requests. Denial rates also vary by insurer. For Medicare Advantage insurers, standard prior authorization denial rates ranged from 5% at Elevance to 17% at UnitedHealth Group. In Medicaid managed care, denial rates ranged from 2% at L.A. Care Health Plan to 23% at Independence Health Group, while ACA Marketplace insurers ranged from 3% at GuideWell to 25% at Centene. Prior authorization denials are rarely appealed, according to the report. However, when they are appealed, many are overturned. About 67% of prior authorization denials were overturned after an appeal in Medicare Advantage, compared to 47% in Medicaid managed care and 43% in ACA federally facilitated Marketplace. — By Marissa Plescia Healthcare Keeps Buying AI. But Nobody’s Building the Workforce to Run It. The shortage The conversation around healthcare AI remains heavily focused on algorithms and prediction. Far less attention is being paid to the people responsible for making these systems function safely and effectively in real healthcare environments — the architects, interoperability specialists, implementation leaders, data governance experts, integration teams, workflow designers, and digital infrastructure professionals who quietly sit underneath nearly every successful healthcare technology initiative. And right now, there are not nearly enough of them. A lack of awareness What makes this more concerning is that healthcare has done relatively little to build awareness around these careers at the exact moment demand for them is accelerating. Most younger professionals entering the workforce have little visibility into interoperability, digital health infrastructure, or healthcare data architecture as career pathways. Healthcare still tends to market itself through traditional clinical roles, while technology talent is aggressively recruited into industries like finance, cybersecurity, big tech, and consumer platforms. Meanwhile, healthcare is quietly creating enormous demand for a workforce capable of supporting connected, AI-enabled care environments. That gap will eventually become impossible to ignore. A broader conversation is needed This is why healthcare needs a broader conversation about workforce development in the age of AI. Not simply how many clinicians the industry needs, but what kinds of operational, interoperability, governance, and infrastructure expertise healthcare will require over the next decade, and whether enough people are being trained to support it. Because ultimately, the future of healthcare AI may depend less on what the technology is capable of doing and more on whether healthcare systems themselves are prepared to absorb it responsibly. — By MedCity Influencer Rachel Dunscombe Better Models Won’t Fix Pharma’s AI Problem — Better Terminology Will The bottleneck At a life sciences conference earlier this year, a pharma analytics lead pulled me aside with what sounded like a simple question: “Is there an ICD-10 code for the disease we’re studying?” There wasn’t. As many researchers know, the reality is that this is true for thousands of medical conditions and disease states. When a condition itself cannot be captured and indexed cleanly in the data, every AI-enabled analysis or decision built on top of that data starts to wobble. The bottleneck in AI-enabled real-world data analysis is not computation, model architecture, or training data volume. It is the semantic layer over which the AI is trying to reason – the place where precise clinical meaning lives. The challenge Most AI systems in real-world data analysis are built on standard code sets like ICD-10, SNOMED CT, and LOINC. Those standards create consistency across billing, documentation, and interoperability, but they were not designed for the kinds of research questions modern pharma teams are trying to answer. This challenge can be illustrated through three frequent failure points. Rare disease cohorts: In many cases, patients with rare diseases are effectively invisible in datasets because there is no precise code to identify them. Severity gradients and disease activity: Clinicians and patients care deeply about distinctions between early- and late-stage disease, or mild versus moderate versus severe presentation. Phenotyping and subtyping: Precision medicine increasingly depends on molecular and clinical specificity that billing-era terminology systems were never designed to carry. It’s a precision problem The conversation around trustworthy healthcare AI is increasingly less about the model itself and more about the clinical intelligence beneath it. A terminology layer that AI can reliably reason over has several defining characteristics: First, it must be curated and clinically validated by physicians, terminologists, and subject matter experts, not assembled passively or machine-learned by brute force from billing data alone. Next, it must be provenanced. Researchers should be able to trace concepts back to trusted clinical sources and understand why a patient was included in a cohort. Finally, it must function as a connected, evolving knowledge graph rather than a static lookup table, allowing researchers to reason consistently across EHR data, registries, claims, and literature without losing fidelity. That is the infrastructure layer that many healthcare AI deployments are still missing. This is not fundamentally a model problem. It is a precision problem. Pretending otherwise risks eroding trust in healthcare AI at exactly the moment the industry can least afford it. — By MedCity Influencer Joseph Zabinski Video   Video: What did UHC CEO say in unprecedented meeting with reporters? Debunked: UnitedHealthcare invited reporters and influencers to their Minnesota HQ. Why? Hear the exchange between MedCity editor and the UnitedHealthcare CEO.

In Other News

The Rise of Consumer Diagnostics and Emerging Trends Consumer diagnostics will be one of several discussions at the INVEST Digital Health conference focused on power shifting to the consumer in healthcare. The conference is scheduled for October 29 in Dallas at Pegasus Park, in partnership with Health Wildcatters. Healthcare Is Deploying AI Tools — It's Not Ready for AI Colleagues Most healthcare organizations are experimenting with AI. Few are preparing to manage AI agents as participants in everyday healthcare workflows. How Payers and Health Plans Think of Identity and the Risks of Fragmented Data [Sponsored] A recent webinar, sponsored by Verato, offered insights from executives at SCAN Health Plan and the Alliance of Community Health Plans on a wide range of tech challenges in healthcare from fragmented data to technology architecture to patient identity.

Podcast   MedCity Pivot: How Aetna is Adopting Agentic AI In this episode of the MedCity Pivot Podcast, CVS Health Aetna's chief digital and technology officer talks about how the insurance business is using AI, especially agentic AI, in healthcare. Point to note: AI is not used in automatic denials of coverage. Watch Now

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