STAT44%

Caregiver cuts 25%

By Tara Bannow66%

7/13/2026, 4:46:24 AM

Keywords: Health Care

BS Summary: This article contains 18 faulty reasoning types, including False Dilemma, Negativity Bias, and Horn Effect, with Framing Effect as the most egregious example at 39.4% saturation with 397 hits. Analysis detected 885 faulty-reasoning hits from 1,007 analyzed words, generating a BS Score of 37.1% and a BS Rank of 25% (16,572 of 21,887 articles). This article is better (less manipulative) than 75.70% of the article peer group.

Caregivers brace for pay cuts, and maybe homelessness 
A game-changer in pancreatic cancer, a vaccine skeptical HHS nom, and more health news from Morning Rounds 
Kevin Dietsch/Getty Images 
Hospitals and Insurance Reporter 
Tara covers the business of health care. 
Her stories focus on hospitals, doctors, and how their business practices affect patients  especially when private equity gets involved. 
She also writes about health insurance and ideas for improving our broken health system. 
You can reach Tara on Signal at tarabannow.70. 
Want to stay on top of the science and politics driving biotech today? 
Sign up to get our biotech newsletter in your inbox. 
Good morning. 
In case you missed it, my pal Bob Herman got the Joe Kernan treatment on CNBC’s “Squawk Box” on Friday , where he discussed his excellent new series  Out of Pocket, Out of Reach .” 
Kernan got in a lot of digs at Democrats and Obamacare, but Bob kept his comments apolitical. 
A true professional! 
States are scrambling to trim their budgets ahead of major provisions of Republicans’ One Big Beautiful Bill Act , which cuts roughly $1 trillion from Medicaid over the coming decade. 
First up on the chopping block: programs states aren’t required to cover under federal law. 
My colleague, O. 
Rose Broderick, identified at least half a dozen states that either are or are trying to slash pay for family caregivers  often parents  of people with intellectual and developmental disabilities. 
Rose’s story exposes the truly devastating human toll of these cuts. 
Two mothers caring for their disabled sons now face losing their homes. 
Their kids’ needs are so high, they can’t work beyond caring for them. 
“It’s either I ride it out until the very last day until they kick us out of our home, or I put him in an institution,” one mother, fighting back tears, told Rose. 
A game-changer in pancreatic cancer? 
Organizers of a three-day pancreatic cancer conference in London didn’t plan for the event to revolve around a promising new drug, but it was all anyone wanted to talk about, my colleague, Andrew Joseph, reports . 
“It’s one of those moments,” one oncologist said during a hastily-added panel about the drug, Revolution Medicine’s daraxonrasib. 
She was referring to the drug’s striking clinical results, first presented at a conference in Chicago in May. 
Patients taking the drug lived nearly twice as long as those undergoing standard chemotherapy in a study of 500 people. 
The drug hasn’t yet gone through regulatory review, but patients are already clamoring for access. 
At the conference, clinicians said they’re bracing for new tensions that will inevitably crop up. 
It’ll probably be expensive. 
Access will be uneven. 
It may have side effects, and doctors may need to explain its limitations. 
Read Andrew’s story . 
Not taught in medical school 
The Department of Health and Human Services recently convened a two-day meeting with dozens of mental health professionals as the agency develops clinical guidance for weaning patients off antidepressants, STAT dream team Lizzy Lawrence and Chelsea Cirruzzo report . 
The meeting comes after HHS Secretary Robert F. 
Kennedy Jr. criticized what he referred to as overmedicalization using selective serotonin reuptake inhibitors, or SSRIs, drugs commonly used to treat depression and anxiety. 
A senior HHS official told my colleagues that the forthcoming guidance isn’t meant to discourage people from using SSRIs, it’s to help them understand what to expect and what to know about getting off of them. 
One clinician who attended told my colleagues that many doctors lack training in this area. 
“They say, ‘I wish I would have information on this, nobody taught me this in medical school.’ 
 “That’s where this guidance will fill that gap.” 
Read more . 
Another vaccine skeptic slotted for HHS 
The country’s response to public health crises could soon be led by the co-founder of a consulting firm who has publicly questioned the safety of vaccines, medications that are typically at the center of any such response, my colleague, Chelsea Cirruzzo, reports . 
Sean Kaufman, the Trump administration’s pick for Assistant Secretary for Preparedness and Response, wouldn’t be the only high-ranking HHS official who harbors vaccine skepticism, even as White House officials try to steer the conversation away from vaccine reform . 
Chelsea tracked down a handful of social media posts in which Kaufman linked the hepatitis B vaccine to autism and questioned the safety of Covid-19 vaccines, describing offering them as “reckless.” 
Kaufman still needs Senate confirmation, and we’ll be paying close attention to Senate health leader Bill Cassidy’s reaction at a hearing this week. 
Read more . 
Is there a doctor on board? 
Airlines have long relied on doctors being willing to help their fellow passengers during in-flight medical emergencies, Dr. 
Sriman Swarup writes in a new First Opinion column . 
He’d know. 
He has personally responded to these requests. 
Doctors do so, he said, out of professional obligation, human decency, and emergency ethics. 
But perhaps this multibillion-dollar industry has become too reliant on doctors’ altruism, Swarup posits. 
In-flight emergencies have financial implications if flights have to be diverted, and he questions the logic of outsourcing a business problem to customers’ professional ethics. 
Swarup doesn’t think paying doctors is the answer, but he does think airlines could come up with something between that and what they currently do, which is, well, nothing. 
Travel credits? 
Volunteer registries? 
Food for thought . 
Parents’ attachment to phone screens can lead to anxiety in children  study, The Guardian 
How a Boston doctor built a following as a ‘loud and unafraid’ voice in the Trump era, Boston Globe 
The gas is cheap. 
The Trump administration isn’t saying who’s paying for it, Politico 
They harvest the nation’s food, but a new rule may strip them of health insurance, KFF Health News 
Submit a correction request Reprints 
FDA quietly pushes back deadline on electric shock ban 
Who’s going to run the FDA? 
Another big premium hike on the horizon 
Ebola outbreak exposes a fractured outbreak response system 
The race for an Ebola therapy begins 
Article reasoning-pattern comparisonThis article: 0.0%Tara Bannow: 1.1%STAT: 3.4%Confirmation Bias0.0%This article: 0.0%Tara Bannow: 1.5%STAT: 1.3%Anchoring Bias0.0%This article: 3.6%Tara Bannow: 1.6%STAT: 3.9%Availability Heuristic3.6%This article: 0.0%Tara Bannow: 0.0%STAT: 1.0%Representativeness Heuristic0.0%This article: 1.5%Tara Bannow: 0.4%STAT: 0.4%Hindsight Bias1.5%This article: 0.0%Tara Bannow: 0.0%STAT: 1.3%Overconfidence Bias0.0%This article: 39.4%Tara Bannow: 22.4%STAT: 8.2%Framing Effect39.4%This article: 0.0%Tara Bannow: 1.5%STAT: 0.7%Loss Aversion0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.9%Status Quo Bias0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.2%Sunk Cost Effect0.0%This article: 2.0%Tara Bannow: 1.0%STAT: 3.3%Optimism Bias2.0%This article: 1.5%Tara Bannow: 0.7%STAT: 1.8%Pessimism Bias1.5%This article: 6.1%Tara Bannow: 8.3%STAT: 8.5%Negativity Bias6.1%This article: 0.0%Tara Bannow: 1.0%STAT: 1.1%Self-Serving Bias0.0%This article: 0.0%Tara Bannow: 0.3%STAT: 0.4%Fundamental Attribution Error0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Actor-Observer Bias0.0%This article: 3.9%Tara Bannow: 4.0%STAT: 0.4%In-Group Bias3.9%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Out-Group Homogeneity Bias0.0%This article: 3.9%Tara Bannow: 1.1%STAT: 1.3%Halo Effect3.9%This article: 4.3%Tara Bannow: 1.2%STAT: 0.1%Horn Effect4.3%This article: 0.0%Tara Bannow: 0.0%STAT: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Tara Bannow: 0.4%STAT: 1.6%Recency Bias0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.4%Primacy Effect0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Blind-Spot Bias0.0%This article: 4.3%Tara Bannow: 1.2%STAT: 0.4%Ad Hominem4.3%This article: 0.0%Tara Bannow: 0.0%STAT: 0.4%Straw Man0.0%This article: 2.0%Tara Bannow: 1.6%STAT: 4.7%Appeal to Authority2.0%This article: 6.2%Tara Bannow: 4.6%STAT: 1.5%False Dilemma6.2%This article: 0.0%Tara Bannow: 0.0%STAT: 1.2%Slippery Slope0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Circular Reasoning0.0%This article: 1.5%Tara Bannow: 2.3%STAT: 4.6%Hasty Generalization1.5%This article: 0.0%Tara Bannow: 0.0%STAT: 0.2%Red Herring0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.4%Bandwagon0.0%This article: 1.1%Tara Bannow: 3.9%STAT: 3.6%Appeal to Emotion1.1%This article: 0.0%Tara Bannow: 0.0%STAT: 0.9%Begging the Question0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 2.2%Post Hoc (False Cause)0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.0%Tu Quoque0.0%This article: 0.0%Tara Bannow: 0.5%STAT: 0.7%Burden of Proof0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.2%Appeal to Nature0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.3%Composition/Division0.0%This article: 1.2%Tara Bannow: 2.7%STAT: 3.3%Anecdotal1.2%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%No True Scotsman0.0%This article: 0.0%Tara Bannow: 1.5%STAT: 2.1%Ambiguity (Equivocation)0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.3%Middle Ground0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Personal Incredulity0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Special Pleading0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.1%Genetic Fallacy0.0%This article: 0.0%Tara Bannow: 1.3%STAT: 1.5%Unattributed Quote0.0%This article: 3.3%Tara Bannow: 1.7%STAT: 0.9%Quote-first Misdirection3.3%This article: 1.4%Tara Bannow: 8.7%STAT: 6.0%Biased Writer Voice1.4%This article: 0.0%Tara Bannow: 0.0%STAT: 2.1%Indoctrination0.0%This article: 0.0%Tara Bannow: 0.0%STAT: 0.9%Politically Left Leaning Bias0.0%This article: 0.0%Tara Bannow: 0.8%STAT: 0.2%Politically Right Leaning Bias0.0%This article: 1.0%Tara Bannow: 0.5%STAT: 3.3%Attempt to Sell a Product or S…1.0%

1007 words analyzed.

Speakers

1speaker1.4%attributed speech993writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 2 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 10 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 33 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 43 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageSriman Swarup • 14 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverage
Selected voice

Sriman Swarup

0%flagged-word coverage
14 attributed words100% of attributed speech68% writer coverage
0%2.5%5.0%Quote-first Misdirection-3.3 ptsWriter: 3.3%Sriman Swarup: 0.0%0.0%Biased Writer Voice-1.4 ptsWriter: 1.4%Sriman Swarup: 0.0%0.0%Attempt to Sell a Product -1.0 ptsWriter: 1.0%Sriman Swarup: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.