#screening — Public Fediverse posts on home.social

Österreich @[email protected] · 2026-05-12 · 07:43 UTC

https://www.europesays.com/at/153735/ EQS-News: Bone Index Finland Ltd.: Bindex bringt Osteoporose-Screening in Boots-Apotheken #apotheken #AT #Austria #Bindex #Bone #Boots #bringt #Finland #Gesundheit #Health #Index #News #Osteoporose #Österreich #Screening

#screening #osterreich #osteoporose #news #index #health

Africa @[email protected] · 2026-05-10 · 11:45 UTC

https://www.europesays.com/africa/227751/ 30-year-old APC aspirant passes screening for Kaduna Reps #APC #HouseOfRepresentatives #KadunaState #MahmudSadisBuba #Nigeria #NigerianPolitics #PoliticalAspirant #PoliticalScreening #SabonGariFederalConstituency #screening #Tinubu–UbaSaniAgenda #YoungAspirants #YouthInPolitics

#youthinpolitics #youngaspirants #tinubu #screening #sabongarifederalconstituency #politicalscreening

Ireland @[email protected] · 2026-04-27 · 21:18 UTC

https://www.europesays.com/ie/456786/ Breast Cancer Screening Tool Avoids Radiation, Compression, Contrast #BreastCancerScreeningToolAvoidsRadiation #cancer #CDC #Compression #Éire #Health #IE #Ireland #mammography #MRI #Screening #US #Women'sHealth

#women #us #screening #mri #mammography #ireland

David Boles @[email protected] · 2026-04-26 · 14:50 UTC

When the Radiologist Becomes the Expense

On March 25, 2026, at a Crain’s New York Business panel discussion of the city’s hospital sector, Mitchell H. Katz, MD, president and CEO of NYC Health + Hospitals, told the assembled executives what cost-cutting now sounds like in the largest public hospital system in the United States. “We could replace a great deal of radiologists with AI at this moment, if we are ready to do the regulatory challenge.” Sandra Scott, MD, who runs One Brooklyn Health, one of the city’s safety-net institutions operating on tight margins, replied that the move would be “a game-changer.” The exchange appeared in Crain’s coverage of the panel and was picked up by the radiology trade press within forty-eight hours.

The proposal reads as the second move in a strategy whose first move has been documented for fifteen years. American hospital systems built imaging volume on the back of a preventative-medicine apparatus that the American College of Cardiology’s own Choosing Wisely campaign identified in 2012 as substantially overused, with up to 45% of stress cardiac imaging in low-risk asymptomatic patients flagged as inappropriate by the ACC’s own appropriate-use criteria. That volume produced revenue. The same hospital systems now propose to automate away the labor cost of interpreting the revenue-producing volume. Imaging continues, billing continues, the radiologist disappears from the ledger, and the patient pays the same copay for a scan whose ordering was already questionable, now read by an algorithm whose performance varies by manufacturer, training data, patient population, and deployment context.

The strongest evidence base for AI in radiology supports a use case that the Katz proposal does not describe. The Mammography Screening with Artificial Intelligence trial, called MASAI, randomized over 100,000 Swedish women to either standard double reading by two radiologists or AI-supported single reading by one radiologist with the Transpara system from ScreenPoint Medical. Lead author Kristina Lång and colleagues at Lund University reported in The Lancet Oncology in 2023 that the AI-supported arm reduced radiologist workload by 44% while modestly increasing cancer detection. Follow-up data published in The Lancet in 2026 showed a 12% reduction in interval cancers, meaning cancers that emerge between screenings and that carry worse prognosis, with AI-supported screening compared to standard double reading. First author Jessie Gommers of Radboud University Medical Centre was direct in the press release: “Our study does not support replacing healthcare professionals with AI as the AI-supported mammography screening still requires at least one human radiologist to perform the screen reading.”

That distinction matters. AI-assisted reading, where a human radiologist works alongside an algorithm that flags suspicious findings and triages low-risk cases for single rather than double review, has been validated in randomized trials with hard outcome measures. The validation extends to AI as a triage and detection support, where one human radiologist remains in the loop. AI-only reading, where no human reviews the image unless the algorithm flags an abnormality, has not been tested to the same standard. A Stanford working paper on so-called “AI mirages” in medical imaging, which describes algorithms that perform well on benchmark datasets and fail in clinical deployment because the training distribution does not match the deployment distribution, was circulating at the time of the Katz panel and was awaiting peer review. Mohammed Suhail, MD, a radiologist at North Coast Imaging quoted in coverage of the Katz statement, said that any attempt to implement AI-only reads “would immediately result in patient harm and death, and only someone with zero understanding of radiology would say something so naive.” That is a strong claim from a working radiologist, but the structural point underneath it is conservative. The trial that would justify AI-only reading on a population basis has not been run. The trial that would justify AI-assisted reading has been run, and it requires the radiologist.

Set the safety question aside for a moment and consider what the proposal does to the labor market. The radiologist has been a high-margin specialist for the same reason all specialists are high-margin: the supply is constrained by the length of training and the licensing apparatus, and the demand is set by imaging volume. Katz’s proposal substitutes capital for labor. If New York State relaxes the regulation requiring radiologist review, NYC Health + Hospitals saves the salary of every radiologist whose reads can be displaced to the algorithm; the imaging machine still runs, still bills, still produces a chargeable encounter on the patient’s account. Generalized, the same logic applies to dermatology, where machine-learning skin lesion classifiers have shown strong retrospective performance, and to pathology, ophthalmology, and any imaging-heavy specialty whose work product is a classification task on a digital image. A worsening shortage of breast imaging specialists, particularly in rural and underserved markets, is the legitimate operational pressure Katz is responding to, and the American College of Radiology has documented this shortage at length. Using that pressure to license a deployment model the trial evidence has not endorsed is the illegitimate response.

Two profits accrue to the hospital system. The first is the original imaging revenue, generated by the appropriate-use-violating ordering patterns that produced the screening volume in the first place. The second is elimination of the labor cost of reading the imaging. A patient pays the copay, the insurer pays the technical fee, and the AI vendor takes a per-read or subscription fee that comes in well below the radiologist’s salary equivalent. Vendor and hospital split the gain. Radiologists are unemployed or shifted to abnormality review only, which substantially compresses earnings since the volume of abnormal reads is a fraction of total reads. Care delivered to the patient may be equivalent in accuracy under the AI-supported model and inferior in accuracy under the AI-only model, with no individual professional license held responsible for the read.

The regulatory politics will determine which model gets deployed. Katz himself flagged the regulatory challenge at the Crain’s panel, asking the assembled CEOs whether there was any reason they should not be lobbying New York State to permit AI-only reads. Lobbying for the relaxation is the hospital system facing margin pressure. Lobbying against is the American College of Radiology and the radiologists themselves, organized through their professional society. New York State legislators will decide. Patients do not have a seat at this table. A patient learns about the change when the mammogram comes back from the screening center read by Transpara version whatever and the bill arrives in the mail with no indication of who, if anyone, looked at the image.

Liability shifts. Under current regulation, a missed cancer on a mammogram exposes the reading radiologist to malpractice litigation, which is why the radiologist carries professional liability insurance and why the radiologist’s professional license is on the line for every read. Under a proposed AI-only model with radiologist confirmation only of flagged abnormalities, the missed cancer that occurred when the algorithm scored the image low and no human looked at it produces a liability question with no individual defendant. The plaintiff sues the institution, the institution sues the AI vendor, the AI vendor sues the training data licensor or invokes the FDA clearance as a shield. Many degrees of separation now sit between the patient and the party with deep pockets. The structural change resembles the shift from the family doctor to the corporate practice in primary care: personal accountability disappears into the institutional defendant, and the patient learns that the system is the system.

The preventative-medicine apparatus that produced excess imaging volume and the AI-radiology apparatus that proposes to read it without human review are two faces of the same financial logic. Both extract value from patient bodies through technical interventions whose individual benefit is small or unproven on a population basis, both produce steady recurring revenue, and both depend on the patient being a passive substrate rather than an active agent in the care chain. One creates the imaging. The other eliminates the labor cost of reading it. The hospital system, which is the only party that crosses both moves, captures the margin on both.

AI-assisted radiology is a real technology with real performance data. The MASAI trial demonstrated that the right deployment, with the right oversight, in the right population, produces better cancer detection at lower radiologist workload. That is a legitimate technological gain and the trial is one of the cleaner pieces of clinical evidence for AI in medicine to date. The question is who controls deployment, under what oversight, and to what end. If AI becomes a tool that radiologists use to read more imaging more accurately at lower cost per read, with patient outcomes that match or exceed the current standard, that is medicine. If AI becomes a license to eliminate the radiologist altogether, with the institutional savings flowing to hospital margins and the patient losing the only party in the imaging chain whose individual professional license is on the line for the read, that is bookkeeping. Mitchell Katz proposed the second model at a panel in March. The trial evidence supports the first. The next move belongs to the New York State legislature, which is to say, to whoever lobbies hardest in Albany.

#ai #health #healthcare #living #medicine #patient #radiologists #radiology #revenue #safety #screening #tech #trainingData

#ai #health #healthcare #living #medicine #patient

David Boles @[email protected] · 2026-04-25 · 15:28 UTC

Preventative Medicine, or the Manufacture of Patients?

There is a sentence every American patient has heard at the dentist’s chair, the cardiologist’s office, the primary-care visit, and the pharmacy counter. It arrives in a tone of grave responsibility: We caught this early. What follows is a crown, an echocardiogram, a statin, a stress test, a referral, a follow-up appointment, and a copay. The word “preventative” has come to function as a moral shield around a billing code. To question whether the recommended intervention is necessary is treated as ingratitude toward a profession that, the implication goes, only wants to keep you alive.

The trouble is that the evidence for many of these interventions is weaker than the assured tone of the recommending clinician suggests, and the financial structure of American medicine rewards the recommendation regardless of whether the evidence supports it. A 2019 JAMA review by Shrank and colleagues estimated annual waste in U.S. health spending at $760 billion to $935 billion, roughly a quarter of total expenditures, with overtreatment and low-value care alone accounting for $76 billion to $101 billion of that figure. Administrative complexity contributes another $266 billion. Pricing failures contribute $230 to $241 billion. These are the numbers in the system’s own peer-reviewed literature, produced by health-services researchers reading their own data.

Consider the dental crown. A 2020 study by Holden and colleagues, published in Community Dentistry and Oral Epidemiology, surveyed dentists who reported widespread peer-observed overtreatment driven by what the authors called the “selling culture” of practice-management courses that teach acceptance-rate optimization. KFF Health News documented Medicaid reimbursement structures that pay three to six times more for nickel-chromium steel crowns than for fillings, an obvious incentive to crown rather than restore. Two of the largest American dental chains, operating under the Kool Smiles and Small Smiles brands, settled federal whistleblower lawsuits alleging unnecessary root canals on Medicaid-enrolled children for roughly $24 million each. The pattern is documented in the Department of Justice settlement record. A three-year-old boy named Gregory, examined by a North American Dental Group office in Ohio, was diagnosed with seven needed root canals; four of the teeth treated were later extracted. The Medicaid bill came to $1,273 against the $61 a check-up and cleaning would have cost. Gregory paid in tooth count. The chain paid a settlement years later, after the journalism caught up with the billing.

Echocardiograms tell the same story in higher-resolution format. The American College of Cardiology, through the Choosing Wisely campaign launched in 2012, listed five cardiac procedures routinely overused, three of which concerned imaging and stress-testing patients without symptoms. The American Society of Echocardiography itself recommends against repeat echocardiograms in stable, asymptomatic patients with a previously normal exam, against echocardiography for preoperative assessment in patients with no cardiac history, and against stress echocardiograms in low-risk asymptomatic adults. A multicenter trial cited by the Journal of Nuclear Cardiology found that 15% of cardiac SPECT studies were inappropriate by the ACC’s own appropriate-use criteria, with the largest single category being detection of coronary artery disease in asymptomatic low-risk patients. A Choosing Wisely Canada review found that asymptomatic low-risk patients account for up to 45% of unnecessary cardiac screening. The professional society of the field that performs the test acknowledges that close to half of its screening volume should not occur. The volume occurs because the equipment is amortized, the slot is scheduled, and the reimbursement code clears.

Salt deserves a more careful answer because the original advice was honest, the science evolved, and the medical establishment has not communicated the evolution well to patients trained to fear the salt shaker. A 2026 systematic review and meta-analysis in Cureus by Alqurain and colleagues, drawing on twenty studies and 306,019 participants, found that sodium restriction reduces mortality risk in patients with essential hypertension, which confirms the original logic for that population. In observational cohorts, however, low sodium intake associates with increased mortality, supporting a J-shaped relationship at the lower extreme. In heart-failure populations specifically, aggressive restriction shows a non-significant trend toward harm. The 2024 European Society of Cardiology guidelines responded to this evidence by setting the sodium target at less than 2 grams per day, framed as realistic and sustainable, and acknowledged that the J-curve effect appears at intakes below that threshold. The honest answer to the question is that the old blanket prohibition was overdrawn, the current evidence supports moderation rather than minimization, and the simplistic counter-claim that “more salt is better” is also wrong. Hypertensives still benefit from reduction. Severely sodium-depleted patients on aggressive diuretics may be harmed by it. Medicine has walked back a categorical claim quietly, without retracting the decades of advice that produced an entire processed-food category labeled “low sodium” and a generation of patients trained to feel guilty about a pinch.

Threshold creep is the marketing arm of preventative medicine, and the documentation of it is now its own academic literature. In May 2003, the Joint National Committee’s seventh report introduced “prehypertension” as a diagnostic category covering blood pressure between 120 and 139 systolic or 80 and 89 diastolic, redrawing the line of disease in a single committee meeting and producing millions of new patients overnight without anyone’s actual blood pressure changing. The American Diabetes Association lowered the hemoglobin A1c threshold for prediabetes to 5.7% in 2010, expanding the population eligible for diabetic surveillance and pharmaceutical preprescription by tens of millions. AbbVie spent more than $75 million on AndroGel marketing in 2012, running an unbranded “Is It Low T?” awareness campaign that, according to a 2017 JAMA Internal Medicine analysis, drove measurable rises in testosterone testing in regions with heavier advertising exposure. The company’s claimed hypogonadism prevalence climbed from roughly one million American men at AndroGel’s FDA approval in 2000 to twenty million at the peak of the campaign, a twentyfold inflation in twelve years that left the actual incidence of medical hypogonadism unchanged and reached well past it into the population of aging men whose declining testosterone is part of normal physiology. JAMA itself published the takedown under the title “Low T as a Template: How to Sell a Disease.” GlaxoSmithKline ran the parallel campaign for restless legs syndrome beginning in 2003, two years before Requip’s FDA approval; sales doubled within a year, climbing from $165 million in 2005 to $330 million in 2006, and the Restless Legs Syndrome Foundation received roughly 45% of its 2005 revenue from the drug companies whose products it was positioned to validate. Ray Moynihan and Alan Cassels named the framework in 2005 in Selling Sickness, which the April 2006 special issue of PLoS Medicine on disease mongering then developed across eleven peer-reviewed articles. The phenomenon is not exotic. The eye doctor who tells the patient with stable elevated intraocular pressure that the chart now reads “pre-glaucoma” is following the same logic, and the rest of the chain follows automatically: category extends, patient enrolls, visit recurs. Nothing about the patient has changed except the box checked on the form.

Colonoscopy is the case where every thread in the argument crosses. The U.S. Preventive Services Task Force recommended initiating screening at age 50 from its 1996 guideline through 2020, then lowered the threshold to 45 in May 2021 in response to documented rises in younger-onset colorectal cancer; the American Cancer Society had already moved earlier, in 2018. The threshold change added roughly 21 million newly eligible Americans to the screening pool. Modeling cited in the USPSTF’s own evidence review estimated that lowering the screening age from 50 to 45 requires 810 additional colonoscopies per 1,000 persons screened in a colonoscopy-based strategy. The procedural revenue for the gastroenterology specialty is substantial, and the financial alignment with maintaining colonoscopy as the preferred modality is direct, even though the USPSTF itself lists fecal immunochemical testing, stool DNA testing (Cologuard from Exact Sciences), and, since the FDA approval of Guardant Health’s Shield in July 2024, plasma-based screening as recommended alternatives. Patients dislike colonoscopy for documented reasons that the marketing apparatus does not address: the day-long bowel preparation is psychologically and physically demanding, the procedure itself requires sedation and a driver, and the complication rate, while small in absolute terms at roughly four perforations and eight major bleeding events per ten thousand procedures, is non-zero on a population that now includes twenty million additional people. Most consequentially, the randomized trial evidence underwriting the marketing is more modest than the marketing suggests. The Nordic-European Initiative on Colorectal Cancer trial, called NordICC, published in the New England Journal of Medicine in October 2022 by Bretthauer and colleagues, randomized 84,585 adults aged 55 to 64 in Poland, Norway, and Sweden either to receive a one-time invitation to colonoscopy or to receive no invitation. At ten years, the intention-to-screen analysis found an 18% relative reduction in colorectal cancer incidence, considerably less than the 50% the trialists had originally hypothesized, and the reduction in colorectal cancer-specific mortality was not statistically significant, with a relative risk of 0.90 and a confidence interval that crossed one. Per-protocol analyses of those who actually attended their colonoscopy were more favorable, but the trial’s headline finding sent a different signal than the volume of screening recommendation would suggest. None of this argues against any individual person choosing colonoscopy. The mass-screening case for choosing colonoscopy at age 45 over the non-invasive alternatives, on a procedure patients dislike with a complication profile that scales with volume, is weaker than the gastroenterology revenue stream depending on it would suggest.

Statins offer a sharper case because the harm signal is undisputed within the literature, including the manufacturers’ own pooled trial data. The 2024 individual-participant-data meta-analysis published in The Lancet Diabetes & Endocrinology by the Cholesterol Treatment Trialists’ Collaboration confirmed what previous summary-level analyses had shown: statin therapy produces a moderate, dose-dependent increase in new diagnoses of type 2 diabetes. The earlier Sattar meta-analysis, with 91,140 participants across thirteen trials, put the relative risk increase at 9%. Preiss and colleagues, comparing high-intensity to moderate-intensity statins across five trials with 32,752 participants, found a 12% increase. Cai and colleagues stratified by LDL-c target and found that when the target was set below 1.8 millimoles per liter, the risk of new-onset diabetes rose by 33%. The Diabetes Prevention Program Outcomes Study, with 3,234 high-risk participants followed for ten years, recorded a 36% cumulative incidence of diabetes among statin users compared with 20% in placebo. Observational meta-analyses, which capture longer follow-up and broader populations than the trials, place the increase as high as 44 to 55%. Statins lower cardiovascular events in patients with established disease. They also produce diabetes in a measurable fraction of users, with the risk concentrated in patients who already carry metabolic risk factors. Both statements are true. Weighing them honestly per patient is the clinical task. The marketing posture, which presented the drugs as harmless tools to be deployed broadly on the basis of a single number called LDL-c, was always incomplete. As the LDL-c target was driven downward more aggressively, the regimen produced more diabetes. This is on record. It has not produced a corresponding pullback in prescribing volume because the prescribing volume is shaped by guideline thresholds, quality metrics tied to insurer reimbursement, and patient anxiety, none of which respond directly to the diabetes incidence data.

The structural question follows from the four clinical cases. Is the American medical system broken, or did it never work? The honest answer is the second. The system was assembled from incompatible parts during the postwar period: a tax-deductible employer-insurance model designed during wartime wage controls, a Medicare program designed to extend Blue Cross logic to the elderly, a Medicaid program designed as charity for the poor, a private fee-for-service architecture designed for solo practitioners, and a hospital-based academic medicine designed for rare disease and surgery. None of these components were designed together. None share an objective function. The result is an apparatus that bills with great competence, codes with great competence, and produces health outcomes that are mediocre by every international comparison the United States has been willing to publish. Life expectancy at birth in the United States is below that of Costa Rica. Maternal mortality runs more than 50% higher than in the next closest wealthy nation. The system is performing as designed; the design has always rewarded volume of billable encounters, and the financial structure pays out for that volume regardless of whether the volume corresponds to improved health.

This is where the moral question becomes unavoidable. Should there be profit in having a healthy body? Some forms of profit are morally legible. A surgeon who removes a tumor has earned compensation. A pharmaceutical firm that develops a drug from molecule to market has earned a return on capital. An infectious-disease specialist who diagnoses a rare presentation has earned the consultation fee. These are professional earnings against a discrete service rendered. The trouble is that American medicine has migrated, over four decades, from the model of compensated service toward the model of recurring revenue extraction. A patient enters a clinical panel. The panel is screened on a schedule. Screening reveals an incidental finding, which generates a workup, which generates a procedure, which generates a follow-up, which generates a maintenance medication, which generates a side effect, which generates a referral. At no point in this chain does anyone need to act in bad faith for the patient to be subjected to a sequence of interventions whose net benefit, as measured by years of life or quality of life, is negligible or negative. The clinician is paid by relative-value-unit production, the hospital by case-mix index, the insurer by per-member-per-month premiums, the drug company by prescription volume. The patient pays a copay at every node and a premium at the front of the chain.

Consider how the mechanism operates without anyone choosing it. The dentist who recommends a crown the tooth does not require is rarely acting in bad faith. The practice-management system quantifies daily production targets and benchmarks the doctor’s work against peer averages, and a clinician below the benchmark has uncomfortable conversations with the practice owner. A cardiologist who orders surveillance echocardiograms in stable asymptomatic patients follows a referral pattern that the practice’s billing coordinator built into the appointment template. A primary-care physician who titrates a statin to a more aggressive LDL-c target works from a quality measure that determines a portion of the practice’s reimbursement. None of these clinicians wakes up wanting to harm the patient. The structure does the harming for them, by making the path of least resistance the path of maximum billing. Preventative medicine, in the modern American sense, has become a euphemism for a procedure pipeline disguised as moral concern.

The technologies themselves have legitimate uses. Statins prevent secondary cardiovascular events in patients who have already had a heart attack, and the evidence for that use case is strong. Echocardiograms in symptomatic patients are diagnostic instruments without which cardiology could not function. Crowns on actually fractured teeth save the tooth and the bite. The correct critique is of population-level deployment without symptom-based indication, of marketing the diagnostic machinery as a moral good when it operates as a revenue mechanism, and of presenting the patient with a recommendation that the system has produced before the clinician walked into the room.

Real prevention exists, and it is recognizable by the absence of profit attached to it. Hand-washing prevents postsurgical infection. Vaccines reduce measles, pertussis, and cervical cancer to historical curiosities. Smoking cessation lowers lung-cancer, stroke, and heart-disease risk. Exercise interrupts nearly every chronic-disease cascade. Sleep allows metabolic recovery. Adequate nutrition starves the inflammatory base state on which most chronic disease feeds. None of these interventions generates significant revenue for the medical system, which is why none of them receives the marketing attention that statins and stress tests and crowns receive. The cheapest preventive measures, which are also the most effective, sit unmarketed because no one profits from them. The most expensive interventions, which range from genuinely beneficial to actively harmful depending on the patient, are heavily marketed because the entire revenue chain depends on their continued use.

A patient who walks into an American clinical encounter today operates in an information environment in which the recommending professional has financial reasons to recommend, the institution has financial reasons to perform, the insurer has financial reasons to negotiate, and no one in the room has direct financial reasons to leave the patient alone. The patient is the only party in the room without a billing code, the substrate on which the codes are inscribed. Until the financial structure changes, the recommendation to question every preventative procedure deserves to be called sober self-interest, supported by the system’s own published evidence about its own published failures. The question to ask the dentist, the cardiologist, the primary-care physician, and the pharmacy counter is the one the system makes hardest to ask: What happens to me if I do nothing? The answer is sometimes serious, sometimes neutral, and sometimes far better than the answer that follows the recommended intervention. Knowing the difference is the work of an adult patient in a system that prefers the patient remain a child.

#bloodPressure #cardiac #dentist #doctor #echocardiogram #glaucoma #health #healthcare #healthyBody #preventativeMedicine #screening #statins

#bloodpressure #cardiac #dentist #doctor #echocardiogram #glaucoma