U.S. sues major insurers, brokers over kickbacks and disability bias; NIH launches effort to curb animal testing; AI flags pain risks after knee replacement – Morning Medical Update

Author(s):

Austin Littrell

Fact checked by:

Keith A. Reynolds

Key Takeaways

Aetna, Elevance, and Humana face allegations of illegal kickbacks and discrimination against disabled beneficiaries in Medicare Advantage enrollments.
NIH's new initiative aims to reduce animal testing, emphasizing human-based research tools to enhance translational accuracy in disease research.
Machine learning identified risk factors for severe post-op pain after knee replacement, enabling personalized pain management strategies.
The NIH initiative aligns with FDA goals, promoting alternative research methods and improving grant review criteria.

The top news stories in medicine today.

U.S. sues Aetna, Humana, Elevance and brokers over Medicare Advantage kickbacks, disability bias

Federal prosecutors filed a False Claims Act complaint accusing Aetna, Elevance (formerly Anthem) and Humana of paying hundreds of millions in illegal kickbacks to major brokers — eHealth, GoHealth and SelectQuote — to steer Medicare Advantage enrollments. The U.S. also alleges Aetna and Humana colluded with brokers to discriminate against disabled beneficiaries, pushing brokers to avoid enrolling them due to lower profitability. The case, originally filed by a whistleblower, claims insurers prioritized profit over patients' best interests and violated federal anti-kickback laws.

NIH launches initiative to reduce animal testing, expand human-based research

The National Institutes of Health (NIH) announced a sweeping new initiative to reduce reliance on animal models and prioritize human-based research tools like organoids, tissue chips, computational models, and real-world data. A new NIH office — ORIVA — will coordinate agency-wide adoption of alternative methods, increase related funding and training, and integrate human-relevant criteria into grant reviews. The effort aligns with FDA goals to reduce animal testing and aims to improve translational accuracy in diseases like Alzheimer’s and cancer, where animal models often fall short.

AI predicts severe post-op pain after knee replacement

A machine learning study from the Hospital for Special Surgery has earned a Best of Meeting award from the American Society of Regional Anesthesia and Pain Medicine for identifying key risk factors linked to severe pain following knee replacement surgery. Analyzing data from over 17,000 patients, researchers found that younger age, high BMI, preoperative opioid or gabapentinoid use, and greater physical or mental impairment predicted worse pain outcomes. The AI classified patients into distinct pain archetypes, enabling more personalized pain management. Future HSS studies will examine longer-term pain trajectories to refine pre- and post-op strategies.