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Forbes
30 minutes ago
- Forbes
Many Medicare Cancer Patients Now Have Much Lower Out-Of-Pocket Costs
Tens of thousands of Medicare beneficiaries who are cancer patients have substantially lower out-of-pocket costs for their prescription drugs, thanks to a key provision included in the Inflation Reduction Act. When people think about the IRA's drug pricing measures, they're more likely to be familiar with the Medicare price negotiation aspect than the redesign of Medicare's outpatient drug benefit. The former entails Medicare's ability to negotiate prices of a select number of drugs. But the prices that apply to the first round of ten pharmaceuticals won't be implemented until next year. It's the wholesale restructuring of the pharmacy benefit that's far more comprehensive and already having an impact on Medicare recipients, especially beneficiaries who prior to 2024 incurred more than $3,300 in annual out-of-pocket costs. These include many cancer patients. Under the IRA law, annual out-of-pocket costs were capped at $3,300 in 2024 and lower still at $2,000 in 2025. Upon enactment of the Medicare Modernization Act in 2006, the federal government health insurance program for seniors and disabled added a prescription drug benefit called Part D. This meant that Medicare beneficiaries who chose to purchase coverage from a prescription drug plan or a fully integrated insurer offering medical and pharmacy benefits under Medicare Advantage, could better afford their outpatient medicines. Nevertheless, problems emerged with respect to gaps in Part D coverage and relatively high out-of-pocket costs in the so-called catastrophic phase of the benefit, especially for beneficiaries taking expensive medications. The IRA, which passed in 2022, includes a provision that aims to decrease the out-of-pocket cost burden for Medicare recipients, putting a lid on annual expenses at $3,300 in 2024 and $2,000 in 2025. This means that after a patient has spent $2,000 out-of-pocket this year, they have $0 in co-payment. Because of how expensive most branded (and even some generic) cancer medications are, many patients may reach the $2,000 maximum as early as January in a given year. But unlike in the past, they won't incur any more out-of-pocket expenses the rest of the year. A recently released report reveals the importance of a cap on out-of-pocket beneficiary expenses. The figure below from IQVIA shows that until 2024 when Part D instituted a cap of $3,300, the proportion of claims with zero dollars in patient co-payments was very small and nearly constant. There was no maximum, and consequently patient co-payments could easily add up in a given year to many thousands of dollars. The IQVIA report also demonstrates how immediate the impact was of capping annual patient out-of-pocket expenses at $3,300 in 2024: Oncology prescription volumes rose 50% year-over-year between 2023 and 2024. In 2025, the cap lowers to $2,000, which will likely boost utilization further. At the same time, the management of costs in the catastrophic phase has shifted away from the federal government and towards plans that manage the pharmacy benefit as well as drug manufacturers. While patients nothing out-of-pocket once they reach the $2,000 threshold and the federal government only reinsures 20% of the cost rather than 80%, drug makers and insurers pick up the slack. Starting in 2025, pharmaceutical manufacturers must cover 20% of drug costs in the catastrophic phase of the pharmacy benefit—up from 0%. And Part D plans take on 60% of costs, up from 15%. The IRA has its share of detractors, in particular, regarding Medicare drug price negotiations which critics claim will lead to reduced levels of research and development expenditures and less pharmaceutical innovation. On Part D redesign, some analysts point to unintended consequences, such as driving up insurance premiums for Medicare recipients in Part D and an exodus of stand-alone prescription drug plans leading to reduced choice for some beneficiaries. There's also been an increase in the use of coverage restrictions, such as prior authorization, as payers attempt to control costs. Medicare Part D plans—managed by pharmacy benefit managers and Medicare Advantage insurers—receive a fixed payment per enrollee from the federal government and bear a portion of the financial risk for part of enrollees' drug expenditures. Accordingly, plan administrators are induced to control costs by managing drug utilization and negotiating lower net prices. IRA changes in the design of the pharmacy benefit have enhanced the incentives to contain costs as much as possible. However, because all cancer medications must be covered, plans have less leeway to impose restrictions. It's hard to argue that Medicare Part D redesign doesn't help oncology patients with high out-of-pocket costs. Medicare beneficiaries who were once heavily burdened financially and sometimes abandoned scripts due to cost are now able to (re)start and stay on their medication regimen.
Forbes
30 minutes ago
- Forbes
Medical School Grads Avidly Pursuing Psychiatry Despite Or Maybe Spurred By Rise Of AI Mental Health Apps
In today's column, I examine the latest headline news that medical school grads are avidly pursuing psychiatry as their career pathway, which seems somewhat contradictory to ongoing pronouncements that AI is going to take over as a mental health advisor and usurp the role of human therapists. Why would sharp-as-nails med school grads opt toward a presumably dead-end occupational route? Let's talk about it. This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here). AI And Mental Health Therapy As a quick background, I've been extensively covering and analyzing a myriad of facets regarding the advent of modern-era AI that produces mental health advice and performs AI-driven therapy. This rising use of AI has principally been spurred by the evolving advances and widespread adoption of generative AI. For a quick summary of some of my posted columns on this evolving topic, see the link here, which briefly recaps about forty of the over one hundred column postings that I've made on the subject. There is little doubt that this is a rapidly developing field and that there are tremendous upsides to be had, but at the same time, regrettably, hidden risks and outright gotchas come into these endeavors too. I frequently speak up about these pressing matters, including in an appearance last year on an episode of CBS's 60 Minutes, see the link here. If you are new to the topic of AI for mental health, you might want to consider reading my recent analysis of the field, which also recounts a highly innovative initiative at the Stanford University Department of Psychiatry and Behavioral Sciences called AI4MH; see the link here. Latest News Is Uplifting A recent news report noted that medical school graduates are increasingly pursuing psychiatry. In a posting entitled 'More Med School Grads Choose Psychiatry – Again' by Mark Moran, Psychiatric News, May 29, 2025, these key points were made (excerpts): The claimed overarching basis for this interest in psychiatry, as suggested in the last point, would be that we are daily bombarded with indications that mental health issues are becoming widespread. Thus, these younger generation grads are undoubtedly seeking to apply their acumen to solving this national and global dilemma. Good for them. One could also cynically observe that this also means that there ought to be a lot of business available for those grads. Namely, the rising demand for therapy will be strong and ensure a long-lasting livelihood for this chosen profession. Nothing is wrong with wanting to have a financially secure future. All seems glorious and upbeat. The AI Mental Health Takeover The hitch is this. There is an immense rise in the use of generative AI and large language models (LLMs) as a surrogate for seeking mental health guidance. Indeed, many predictions are that people often prefer AI since it easy to access on an anywhere anytime basis, it is super inexpensive if not free to use, it tends to be highly empathetic in appearance (see my discussion at the link here), and AI seems to be a kind of anonymous non-judgmental form of psychological analysis (this isn't the case but many falsely believe this to be true). All in all, the bottom line is that AI is predicted to gut the need for human therapists. Patients will angle toward using AI in lieu of seeing a mental health professional. Even if AI doesn't seem a suitable replacement from the perspective of the profession itself, clients are going to gravitate toward AI anyway. The alluring traits, as I've noted, are so compelling that it is hard to justify going toward the human therapist's direction. How could those savvy med school grads not somehow discern this emerging disruption and transformation of the mental health realm? It seems quite a vexing mystery. These are smart students who have painstakingly made their way in a herculean fashion through modern med school. Choosing their next step is bound to be something they have noodled on throughout the excruciating medical school experience. The odds of making a haphazard choice are exceedingly low. What gives? Eyes Wide Open Is The Case First, let's assume that they are generally cognizant of the looming takeover of AI in the mental health realm. I say this because some pundits would contend that they are unaware of this possibility. These newbie grads simply don't realize that AI is rapidly emerging in this domain. My interactions with med school students suggest otherwise. These are digital natives who embrace the latest online tools. Many of them leaned into generative AI and LLMs during their schooling, often doing so on their own since the university was either silent on the matter or was agonizingly trying to figure out what role AI should have in the medical education arena. Via grit and keen interest, these battle-hardened med school students have ventured into the AI side of things. The gist is that few of these grads seem to have their heads in the sand. Most tend to see clearly that AI is coming. They are not choosing a path that will catch them completely off-guard, which is a base assumption that some are saying is going to happen to them. Belief In The Human-To-Human Sanctity One logical basis for going the psychiatry direction is that they ardently believe in the sanctity of human-to-human interaction. People who use AI for their mental health pursuits will, at times, realize that it isn't the same as a truly human-to-human experience. They will rely partially on human-to-AI assistance but ultimately seek human pairing too. It isn't a one-size-fits-all solution. Instead, AI becomes part of a larger picture that still includes human therapists. I've coined the new arrangement of therapist-AI-patient as the triad, which is gradually supplanting the classic duo or dyad of therapist-patient; see my discussion at the link here. Med school grads readily grasp this evolving relationship. For them, adding AI into the mix provides no fear. They astutely perceive that AI has its place, as does the human-to-human element. Embracing AI Rather Than Sidelining It Another facet is that these med school grads are eager to embrace AI. Whereas some longstanding members of the profession are resistant to AI and insist that AI must be kept out of the loop, these eye-opening grads realize that there is little sense in tilting at windmills. You might as well accept that AI is going to be an integral part of the profession. It is career-limiting to try and simply wish that AI goes away. Advances in AI are going to radically expand how AI gets immersed in mental health advisement. This is a train that isn't going to stop. Recent grads aim to be on the train, rather than getting rolled over by the train. AI is already in the loop and will increasingly be in the loop. Period, end of story. Shaping AI In Mental Health This embracing of AI goes a step further. Some grads are hopeful of being pioneers in intertwining AI into the field of psychiatry. When the transformation of a domain is underway, great opportunities arise. For my recounting of the history of AI and the field of psychology as intertwined cousins, see the link here. Think of it this way. The golden age of therapist-AI-patient is going to inevitably emerge. We aren't there yet. If you want to make a difference, a big difference, the timing of doing so is almost ideal. AI will allow a reach of mental health guidance at a massive scale. We already know that, for example, ChatGPT by OpenAI already garners around 400 million weekly active users, and some proportion of those are indubitably leveraging AI for mental health advice (see my effort to calculate the population-level magnitude, at the link here). Now is the early stage of enormous change afoot, and these grads are going to be part of that new wave. In a given standalone career, there are only so many patients or clients that a solo therapist can help out. The number of patients is capped by the number of hours that a psychiatrist can muster on a weekly and annual basis. Time is precious. But by being instrumental in shaping AI for mental health, they can have a demonstrable impact on an immense scale. Their energy and enlightenment on how AI should undertake mental health guidance provides a strident possibility for establishing a legacy that will last their lifetimes and beyond. Money Making Too Let's revisit the earlier noted factor of an expanding demand for mental health advisement and the somewhat materialistic assumption that pursuing psychiatry will therefore ensure a long-lived livelihood for those in the psychiatry field on a demand/supply basis. Again, there's nothing wrong with picking a career path that provides sufficient monetary fulfillment along with professional fulfillment. Some of these grads are undoubtedly eyeing how they can avidly pursue an AI startup that weaves together the latest in AI and the AI-driven delivery of mental health advice. There are plenty of big bucks flowing from VCs and healthcare providers to this niche. Might as well jump into that lucrative pond. In essence, their forte provides insights into psychology and human mental health guidance, and they are primed and ready to aid in devising AI that can do a bang-up job, similarly. One angle is to pair up with erstwhile heads-down AI developers to figure out ways to get AI to do this. Especially getting the AI to act safely and suitably. You see, there are many weaknesses and concerns about how AI can actually undercut mental health by giving out lousy advice or even endangering guidance -- these are yet to be resolved concerns. See my analysis at the link here. Disruption As Challenge And Opportunity For those grads that might be behind the eight ball, perhaps they aren't foreseeing the upcoming disruption that is going to undeniably occur. If they want to have a conventional mental health practice, good luck with that. Ignoring AI won't make AI go away. At some juncture, their non-AI imbued practice will have to contend with AI or close its doors. I would wager that most of these grads are wise to the advent of AI in their profession. They aren't sure what way AI is going to go. They aren't quite sure what their role will be in the upcoming transformation of how mental health therapy takes place. They are certainly sure that they have the right stuff that will ensure they are primed to take on new ways of doing business. The final word for now goes to Carl Jung and his legendary remark: 'Who looks outside, dreams; who looks inside, awakes.' That's exactly what those new grads pursuing psychiatry already know to be true, particularly in an AI-based future.
Medscape
an hour ago
- Medscape
New Lyme Blood Test Bests Standard Diagnostics
A new blood test for Lyme disease outperforms standard diagnostic testing across all stages of the disease, according to new data presented at the 2025 Association for Diagnostics and Laboratory Medicine annual meeting in Chicago. The test, which pairs a multiplexed assay with a machine learning algorithm, showed over 90% accuracy in diagnosing Lyme disease in 308 human serum samples. The CDC estimates that about 476,000 individuals may be diagnosed and treated for Lyme disease each year in the US. The tick-borne disease, caused primarily by infection with Borrelia burgdorferi , is most treatable in the first few weeks of infection, but diagnosis during this early stage poses a challenge to clinicians. Barriers to Early Diagnosis The most common sign of early infection is a skin rash called erythema migrans (EM) that often occurs at the site of the tick bite. While a bull-eye-shaped rash is telltale sign of Lyme disease, this type of EM is actually not a common presentation, said Liz Horn, PhD, MBI, principal investigator of the Lyme Disease Biobank, a biorepository of samples from people with Lyme disease, headquartered in Portland, Oregon. She was not involved with the work. EMs can present in different forms, and about 30% of people with Lyme disease do not develop a rash. 'If you don't have a rash, you have to rely on serologic tests,' Horn said, which are notoriously insensitive in early disease, as antibodies can take weeks to develop. The CDC currently recommends a two-test format. Standard two-tier testing (STTT) involves an enzyme immunoassay as the first step, which, if positive or indeterminate, is followed by a Western Blot. In the first few weeks of disease, antibody levels can be too low to detect, leading to false negatives. In a recent study led by Horn using samples from individuals with signs and symptoms of early Lyme disease who were enrolled in the Lyme Disease Biobank, just 34% of patients presenting with EM > 5 cm tested positive on serologic tests. Among patients without EM, only 16% had positive results, and among those with EM ≤ 5 cm, the positivity rate dropped to just 5%. 'If we could get a serology test that works better in early disease, that could have great benefits for both patients and providers,' Horn said. Pairing AI With a Multiassay This new blood test, called LymeSeek, works differently by detecting 10 different antigens simultaneously. An algorithm developed using deep learning 'sorts through all of the responses,' explained Holly Ahern, MS, MT, the chief scientific officer of ACES Diagnostics, the company developing LymeSeek, in Paradise Valley, Arizona. 'That is what gives the test its very high sensitivity and specificity,' she said. Ahern is also an associate professor of microbiology at State University of New York at Adirondack (SUNY Adirondack) in Queensbury, New York. To validate the test, developers analyzed the human serum samples of 150 control individuals and 158 Lyme disease cases, across all phases of Lyme disease. Samples were provided by the Lyme Disease Biobank, the CDC, and the Johns Hopkins University Lyme Disease Research Center in Baltimore. The control samples were from patients in endemic and nonendemic areas and included individuals with non-Lyme look-like diseases, like mononucleosis and rheumatoid arthritis. The test correctly classified 281 samples as Lyme cases or control individuals, resulting in a test sensitivity of 91.7% and a specificity of 90.7%. In an additional analysis, the ACES diagnostics team also compared LymeSeek to STTT using samples from the Johns Hopkins Lyme Disease Research Center. In very early stages of disease (0-72 hours after appearance of an EM rash), LymeSeek diagnosed 100% of Lyme cases, whereas standard testing identified only 37% of cases. In samples taken 3-4 weeks after EM appearance, LymeSeek's results remained consistent, and standard testing identified 76% of cases. 'The observed seroconversion indicates the enrolled patients did have Lyme disease and is a confirmation that the test result given by LymeSeek is a true positive test result,' Ahern added. In patients with post-treatment Lyme disease (6 months or more after infection), LymeSeek identified 97% of cases, whereas standard testing identified less than half (46%). 'With this one single test, we can detect [Lyme] in the early stages, but we can also detect it across all stages of the disease' Ahern said, which includes through 1 year from first Lyme diagnosis. ACES Diagnostics is now working to develop a clinical trial plan with the FDA. The test has received a De Novo classification, meaning it's being evaluated on its own merits rather than compared to the current standard diagnostics. 'We're not just showing that we are as good as two-tier serology because what's the point of being as good as a test that really isn't very good?' Ahern said.
