In the United States, health insurance companies are increasingly facing litigation — not just over traditional policy or claim disputes, but over the use of algorithms and automation in claim-decisions. A recent example: a lawsuit against UnitedHealth Group alleges that a so-called AI algorithm (named “nH Predict”) was used to deny or prematurely end medically-necessary care for elderly beneficiaries under Medicare Advantage plans. CBS News+1

What’s going on?

• The complaint claims the algorithm overrode doctors’ judgments, resulting in coverage denials and forcing patients or families to bear large out‐of‐pocket costs. Health Exec+1
• The use of such automated decision‐systems raises issues of transparency, fairness, medical ethics, and whether policyholders were properly informed.
• These cases echo older litigation about “usual, customary and reasonable” (UCR) reimbursement rates and out‐of‐network payments: e.g., use of flawed data by Ingenix, Inc. (a subsidiary of UnitedHealth) which led to under-reimbursement suits. Health Capital+1

Why it matters

• For policy-holders: If an insurer uses an algorithm to deny or reduce a claim, you may have fewer avenues of recourse, or not know how the decision was made.
• For insurers & providers: This is a legal risk zone — as more claim‐decisions are automated, the potential for errors (or allegations thereof) rises.
• For regulators & consumers: It raises a broader question of algorithmic accountability in healthcare services.

📌 Hypothetical Role of “Hertus Algorix”
(Note: I couldn’t find a credible reference to an entity named “Hertus Algorix” in publicly-available sources. If this is a hypothetical or internal name, here’s how the role might be described.)

Imagine “Hertus Algorix” is a company that builds or supplies algorithmic decision‐systems for insurers (or reinsurers) to evaluate health‐insurance claims. Their role in this context might include:

• Developing a model that predicts the likelihood a claim is valid or the patient’s need for post-acute care.
• Implementing that model into the insurer’s claim‐workflow so the algorithm either flags claims for manual review or automatically denies/approves them.
• Providing analytics & dashboards to the insurer to monitor performance, error‐rates, and appeal outcomes.
• Potentially, improving cost‐control by reducing payouts for care deemed “not medically necessary” based on historical data.

If under legal scrutiny, the questions for Hertus Algorix (or a similar vendor) would include:

• Was the algorithm validated with appropriate medical oversight?
• Did the insurer disclose to policy‐holders that algorithms would influence claim decisions?
• What were the error‐rates, appeal‐outcomes and oversight mechanisms?
• Did the algorithm unfairly disadvantage certain populations (e.g., older patients, complex care)?
• Was there human‐override possible, or did the algorithm make binding decisions?

🔍 Takeaway
Health insurance litigation in the U.S. is entering a new phase where algorithmic decision‐making is under the spotlight. For consumers, this means:

• Ask: Was my claim reviewed by an algorithm? Can I appeal it? Was I given explanation of denial?
• Keep documentation: doctor’s notes + insurer’s decision letters.
• If you suspect unfair algorithm‐based denial, consult a consumer‐rights or healthcare attorney.

For insurers & vendors like algorithm-builders: transparency, medical validation, and fair operations are becoming not just “nice‐to‐have” but potentially legally required.