Tips & Advices
How artificial intelligence controls your health insurance coverage
(The Conversation) – Over the past decade, health insurance companies have increasingly embraced the use of artificial intelligence algorithms. Unlike doctors and hospitals, which use AI to help diagnose and treat patients, health insurers use these algorithms to decide whether to pay for health care treatments and services that are recommended by a given patient’s physicians.
One of the most common examples is prior authorization, which is when your doctor needs to receive payment approval from your insurance company before providing you care. Many insurers use an algorithm to decide whether the requested care is “medically necessary” and should be covered.
These AI systems also help insurers decide how much care a patient is entitled to — for example, how many days of hospital care a patient can receive after surgery.
If an insurer declines to pay for a treatment your doctor recommends, you usually have three options. You can try to appeal the decision, but that process can take a lot of time, money and expert help. Only 1 in 500 claim denials are appealed. You can agree to a different treatment that your insurer will cover. Or you can pay for the recommended treatment yourself, which is often not realistic because of high health care costs.
As a legal scholar who studies health law and policy, I’m concerned about how insurance algorithms affect people’s health. Like with AI algorithms used by doctors and hospitals, these tools can potentially improve care and reduce costs. Insurers say that AI helps them make quick, safe decisions about what care is necessary and avoids wasteful or harmful treatments.
But there’s strong evidence that the opposite can be true. These systems are sometimes used to delay or deny care that should be covered, all in the name of saving money.
A pattern of withholding care
Presumably, companies feed a patient’s health care records and other relevant information into health care coverage algorithms and compare that information with current medical standards of care to decide whether to cover the patient’s claim. However, insurers have refused to disclose how these algorithms work in making such decisions, so it is impossible to say exactly how they operate in practice.
Using AI to review coverage saves insurers time and resources, especially because it means fewer medical professionals are needed to review each case. But the financial benefit to insurers doesn’t stop there. If an AI system quickly denies a valid claim, and the patient appeals, that appeal process can take years. If the patient is seriously ill and expected to die soon, the insurance company might save money simply by dragging out the process in the hope that the patient dies before the case is resolved.
This creates the disturbing possibility that insurers might use algorithms to withhold care for expensive, long-term or terminal health problems , such as chronic or other debilitating disabilities. One reporter put it bluntly: “Many older adults who spent their lives paying into Medicare now face amputation or cancer and are forced to either pay for care themselves or go without.”
Research supports this concern – patients with chronic illnesses are more likely to be denied coverage and suffer as a result. In addition, Black and Hispanic people and those of other nonwhite ethnicities, as well as people who identify as lesbian, gay, bisexual or transgender, are more likely to experience claims denials. Some evidence also suggests that prior authorization may increase rather than decrease health care system costs.
Insurers argue that patients can always pay for any treatment themselves, so they’re not really being denied care. But this argument ignores reality. These decisions have serious health consequences, especially when people can’t afford the care they need.
Moving toward regulation
Unlike medical algorithms, insurance AI tools are largely unregulated. They don’t have to go through Food and Drug Administration review, and insurance companies often say their algorithms are trade secrets.
That means there’s no public information about how these tools make decisions, and there’s no outside testing to see whether they’re safe, fair or effective. No peer-reviewed studies exist to show how well they actually work in the real world.
There does seem to be some momentum for change. The Centers for Medicare & Medicaid Services, or CMS, which is the federal agency in charge of Medicare and Medicaid, recently announced that insurers in Medicare Advantage plans must base decisions on the needs of individual patients – not just on generic criteria. But these rules still let insurers create their own decision-making standards, and they still don’t require any outside testing to prove their systems work before using them. Plus, federal rules can only regulate federal public health programs like Medicare. They do not apply to private insurers who do not provide federal health program coverage.
Some states, including Colorado, Georgia, Florida, Maine and Texas, have proposed laws to rein in insurance AI. A few have passed new laws, including a 2024 California statute that requires a licensed physician to supervise the use of insurance coverage algorithms.
But most state laws suffer from the same weaknesses as the new CMS rule. They leave too much control in the hands of insurers to decide how to define “medical necessity” and in what contexts to use algorithms for coverage decisions. They also don’t require those algorithms to be reviewed by neutral experts before use. And even strong state laws wouldn’t be enough, because states generally can’t regulate Medicare or insurers that operate outside their borders.
A role for the FDA
In the view of many health law experts, the gap between insurers’ actions and patient needs has become so wide that regulating health care coverage algorithms is now imperative. As I argue in an essay to be published in the Indiana Law Journal, the FDA is well positioned to do so.
The FDA is staffed with medical experts who have the capability to evaluate insurance algorithms before they are used to make coverage decisions. The agency already reviews many medical AI tools for safety and effectiveness. FDA oversight would also provide a uniform, national regulatory scheme instead of a patchwork of rules across the country.
Some people argue that the FDA’s power here is limited. For the purposes of FDA regulation, a medical device is defined as an instrument “intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease.” Because health insurance algorithms are not used to diagnose, treat or prevent disease, Congress may need to amend the definition of a medical device before the FDA can regulate those algorithms.
If the FDA’s current authority isn’t enough to cover insurance algorithms, Congress could change the law to give it that power. Meanwhile, CMS and state governments could require independent testing of these algorithms for safety, accuracy and fairness. That might also push insurers to support a single national standard – like FDA regulation – instead of facing a patchwork of rules across the country.
The move toward regulating how health insurers use AI in determining coverage has clearly begun, but it is still awaiting a robust push. Patients’ lives are literally on the line.
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When medical insurance provider Centene (CNC) opened its books to investors on Friday, the company reported a surprising loss and an uptick in usage.
The latter is a broader problem for the industry.
In the second quarter, Centene reported an adjusted loss of $79 million and a “health benefits ratio” of 93%. Its benefits ratio, or the amount of its revenue derived from premiums that it pays out for medical care, jumped from 87.6% in the same quarter last year.
Moves in that figure can have outsized effects on health insurers’ financial performance.
“Because of the narrow margins of our health plan business, relatively small changes in our HBR can create significant changes in our financial results,” Centene wrote in its Q2 earnings report.
And the problem is not isolated to Centene.
Elevance Health (ELV), which offers plans including Blue Cross and Blue Shield, reported a similar jump in its “benefit expense ratio” to 88.9% in the second quarter, up from 86.3% in the same quarter last year.
Both Centene and Elevance attributed the jump especially to their government-subsidized offerings under the Medicaid and Medicare programs.
Molina Healthcare (MOH), which reported Q2 earnings earlier this month, reported a similar outlook, attributing its lowered earnings guidance to the same trend facing other medical insurers.
“The short-term earnings pressure we are experiencing results from what we believe to be a temporary dislocation between premium rates and medical cost trend which has recently accelerated,” Molina CEO Joseph Zubretsky said in a statement.
Elevance stock dropped by roughly 12% after its report earlier this month, while Molina stock dropped by roughly 8%. Both stocks have remained depressed since.
Health Care (XLV) is the worst-performing sector in the S&P 500 this year.
Centene stock dropped by roughly 15% in premarket trading after its earnings release before recovering to a positive gain of roughly 6% by the closing bell on Friday.
The buoy was led by CEO Sarah London’s announcement that Centene was reinstating earnings guidance after pulling this forecast earlier in the month. The company also reported revenue of $48.7 billion, which topped estimates for $44.2 billion, and said it expects to be able to raise the payments it gets from states for Medicaid plans, which would improve its margins.
The premium-to-cost ratio will be closely watched at UnitedHealth Group (UNH), which refers to this measure as its “medical care ratio” (MCR) and is slated to release Q2 earnings next week.
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The number of complaints about pet and livestock insurance referred to the Financial Ombudsman Service (FOS) increased by more than a quarter over the past year, making it the fastest growing source of complaints in UK general insurance (UKGI) – according to exclusive analysis by market intelligence firm Insurance DataLab.
FOS data for the first quarter of 2025 showed that almost 600 complaints were made about pet related policies between January and March this year, up 26% from the same period in 2024, when fewer than 475 cases were recorded.
This means that pet and livestock insurance is now the fourth most complained about business line in UKGI, with complaints having grown by more than 146% over the last five years.
Another concerning development for the pet insurance market is that more than 52% of complaints were upheld in favour of the customer over the first three months of 2025. This is around 19 percentage points higher compared to the same quarter in 2024 and represents the highest upheld rate of any UKGI business line.
These data points suggest a broader issue beyond isolated service failings in the pet insurance arena – the findings hint at potential weaknesses in product design, policy wordings and claims processes across this marketplace.
“Pet insurance might still be a relatively niche product in terms of volume, but the direction of travel here is significant,” explained Insurance DataLab co-founder Dan King.
“It’s not just that complaints are rising – it’s that a growing number are being upheld. That should prompt some serious reflection from insurers about whether these products are delivering fair value and good customer outcomes.”
Insurance DataLab’s analysis found that while claims related complaints remain the most common issue – accounting for more than 70% of complaints made to the FOS for this line of business – pet insurance is seeing a widening range of concerns.
Indeed, complaints about sales and advice rose by 73% year-on-year and now account for nearly a fifth of all pet cover cases, up from just 14% in Q1 2024.
“This is not just about how claims are handled – it’s also about how products are sold and explained,” added King. “Customers are clearly finding themselves with policies that don’t perform as expected and that disconnect raises further questions under Consumer Duty.”
Individual firm impact
Travel insurance also recorded a year-on-year rise in complaints, with more than 1,050 cases referred to the FOS in Q1 2025 — up 6% year-on-year. The average upheld rate is 37% across these cases, although performance varied significantly between providers.
One firm accounted for nearly 30% of all travel insurance related complaints over the last 12 months – after cases against this specific provider doubled – with some 47% upheld in favour of the customer. This is 10 percentage points ahead of the market aggregate for travel insurance products.
“The fact that one provider can have such a disproportionate impact on the market shows the importance of forensic benchmarking,” King noted. “It’s not enough to look at the overall market – firms need to know how they compare to individual competitors and understand who the outliers are.”
High complaints
Despite the rising complaint volumes across the pet and travel markets, car and motorcycle insurance continues to account for the largest number of FOS cases overall.
Almost 3,150 motor related complaints were referred to the ombudsman in the first quarter of 2025 – down 27% from 4,325 a year earlier.
Motor insurance now represents 31% of all FOS complaints, down from 40% in Q1 2024. The average upheld rate has also fallen slightly to 38%, broadly in line with the market average across all business lines.
Buildings insurance was the second most complained about product line in Q1 2025, with 1,725 cases recorded – a slight decrease from the same period last year.
This business line also reported an improved upheld rate of 40%, down from 43% in Q1 2024 – although it is worth noting that this is still higher than the market aggregate across all business lines.
When it comes to claims related complaints – which accounted for approximately 81% of all buildings insurance complaints over the last five years – the upheld rate rose to 43%.
Continued claims challenges
The FCA’s recent review of claims handling in the home and travel market, published in July 2025, found issues around claims handling – particularly relating to storm damage.
The regulator noted that of the 118,890 claims classified as storm claims, around 32% saw a settlement payment being made. Meanwhile, 49% were rejected for reasons ranging from damage being linked to general wear and tear rather than a storm, or weather conditions not meeting the insurer’s definition of a storm.
A further 19% of policyholders decided to not continue with making their claim – King believes this indicated issues around the claims process itself.
“A significant number of customers are giving up on their claim partway through the process,” he said. “That should be a concern to any insurer – not just because of the potential compliance risk, but because of what it says about trust and clarity in the claims journey.”
The regulator’s aforementioned review also highlighted shortcomings in insurers’ management information (MI), particularly around customer outcomes.
It noted that some insurers lacked the data required to monitor performance effectively, especially when outsourcing claims functions, while others were not tracking outcomes at all. The FCA added that “this raises concerns about the quality of customer outcomes”.
The regulator also pointed out that MI was often “limited in detail and disproportionately focused on financial performance metrics”, indicating that more needs to be done to properly analyse and benchmark customer outcomes.
With regulatory expectations rising and complaints data offering increasingly detailed insights into customer outcomes, insurers will need to continually adapt how they monitor, benchmark and improve performance – particularly in areas like pet, travel and buildings insurance, where consumer dissatisfaction appears most acute.
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