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Why so many Americans are using AI for health guidance

Why so many Americans are using AI for health guidance

A new poll reveals one-quarter of U.S. adults are turning to AI tools for quick, affordable health guidance and research.
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Kansas Enacts Law to Protect Nurses from Clerical Errors Affecting Careers

Kansas Enacts Law to Protect Nurses from Clerical Errors Affecting Careers

Kansas has passed House Bill 2528, a new law aimed at protecting nurses from career-damaging disciplinary actions due to clerical errors. The law redefines 'unprofessional conduct' to focus on actions that directly impact patient care, rather than administrative mistakes. This change comes in response to cases like that of Amy Siple, a nurse who faced severe professional consequences after her license lapsed due to an unpaid fee. The law, effective July 1, will expunge previous 'unprofessional conduct' notes related to minor errors from nurses' records, allowing them to continue their careers without undue hindrance. The Kansas Board of Nursing (KSBN) will also improve the license renewal process by sending multiple reminders to prevent such oversights.
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Mass General Brigham Study Reveals Generative AI Chatbots Struggle with Differential Diagnoses

Mass General Brigham Study Reveals Generative AI Chatbots Struggle with Differential Diagnoses

A study conducted by Mass General Brigham has found that generative AI models, specifically large language models (LLMs), often fail to accurately navigate differential diagnoses in clinical settings. The research evaluated 21 different LLMs on 29 standardized clinical cases, revealing that while these models can achieve a correct final diagnosis over 90% of the time, they struggle significantly with generating differential diagnoses. The study highlights a consistent gap between the AI's processing of information and the iterative refinement process used by clinicians. Despite improvements in AI models, the study concludes that these systems are not yet ready for unsupervised clinical-grade deployment.
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AI Tools Provide Flawed Medical Advice to Millions of Americans, Raising Concerns

AI Tools Provide Flawed Medical Advice to Millions of Americans, Raising Concerns

A recent survey by the West Health-Gallup Center on Healthcare in America reveals that approximately 66 million American adults are turning to AI chatbots like ChatGPT for medical advice. This trend is concerning as many users are foregoing traditional medical consultations in favor of AI-generated advice. The survey indicates that 14% of these individuals, equating to over nine million people, have opted not to see a healthcare provider they would have otherwise consulted. The study highlights the significant risks associated with relying on AI for critical health advice, as these tools often provide inaccurate or potentially unsafe recommendations. Despite advancements in AI technology, large language models (LLMs) still struggle with clinical-grade decision-making, often collapsing onto single answers without considering the full clinical picture.
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AI Misuse in Healthcare: A Cautionary Tale from Seattle

AI Misuse in Healthcare: A Cautionary Tale from Seattle

Ben Riley, an AI-skeptic, is raising awareness about the dangers of relying on artificial intelligence for critical health decisions following the death of his father, Joe Riley. Joe, a retired neuroscientist from Seattle, ignored his doctors' advice on leukemia treatment after consulting AI tools like Perplexity. These tools provided misleading information, leading Joe to believe he knew better than his medical team. Despite his tech-savvy background, Joe's reliance on AI resulted in a delay in treatment, ultimately contributing to his death in late 2025. Ben now advocates for caution in using AI for medical advice, emphasizing the need for human oversight.
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Seqster Unveils New Data Tool to Enhance Clinical Research Capabilities

Seqster Unveils New Data Tool to Enhance Clinical Research Capabilities

Seqster Unveils New Data Tool to Enhance Clinical Research Capabilities
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CMS ACCESS Model Raises Concerns Over Participant Diversity and Impact on Healthcare

CMS ACCESS Model Raises Concerns Over Participant Diversity and Impact on Healthcare

The Centers for Medicare & Medicaid Services (CMS) has released a list of over 150 participants in its ACCESS model, aimed at delivering measurable clinical outcomes for patients with chronic conditions. The model includes a diverse range of organizations, from those experienced in Medicare Advantage and ACOs to newer entrants from consumer tech and analytics sectors. This diversity is intentional, as CMS seeks to encourage innovation by lowering barriers to entry. However, the mix of experience has raised concerns among industry leaders about the ability of all participants to positively influence patient outcomes. The ACCESS model requires coordination with a provider ecosystem facing financial and technological pressures, posing challenges for newer entrants.
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UK Healthtech Sector Boosted by £100M Investment from British Business Bank

UK Healthtech Sector Boosted by £100M Investment from British Business Bank

The British Business Bank has committed £100 million to a new healthcare fund launched by Apposite Capital, aimed at supporting innovative UK companies in the life sciences sector. The Apposite Healthcare Growth I fund targets companies involved in medical products, diagnostics, digital health, and pharmaceutical services. This investment is the bank's largest to date and seeks to address the capital shortage for companies at a growth inflection point. The initiative aligns with the UK's Life Sciences Sector Plan, aiming to position the UK as a leading life sciences hub by 2030.
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Hippocratic AI Introduces Voice AI Tools to Enhance Patient and Nurse Interaction

Hippocratic AI Introduces Voice AI Tools to Enhance Patient and Nurse Interaction

Hippocratic AI has launched two innovative Voice AI products aimed at improving healthcare interactions: AI Front Door and Nurse Co-Pilot. AI Front Door is designed to streamline patient interactions by consolidating scheduling, lab results, billing, and care follow-ups into a single, continuous conversation. This tool aims to replace traditional fragmented call centers and digital front doors, offering a more personalized and seamless experience. Nurse Co-Pilot, co-developed with healthcare institutions like Cleveland Clinic and Cincinnati Children’s, focuses on automating repetitive tasks for bedside nurses, such as admission education and medication adherence. This tool is expected to return significant time to nurses, allowing them to focus more on direct patient care.
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Fake Disease 'Bixonimania' Exposes AI Vulnerabilities in Medical Research

Fake Disease 'Bixonimania' Exposes AI Vulnerabilities in Medical Research

A fake disease called 'bixonimania' was created by Swedish researcher Almira Osmanovic Thunström as part of an experiment to test AI systems. The disease, which supposedly causes pink eyelids from screen exposure, was detailed in fake preprint papers filled with obvious jokes. Despite this, several AI models, including Microsoft Copilot and Google Gemini, treated the disease as real, with some even providing medical advice. The prank escalated when a real medical journal cited the fake disease in a published paper, highlighting the potential for AI-generated misinformation to infiltrate scientific literature.
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Intermountain Health Hospitals Recognized Among Top 100 in 2026

Intermountain Health Hospitals Recognized Among Top 100 in 2026

Nine hospitals within the Intermountain Health system have been named to the 2026 list of the 100 Top Hospitals by Modern Healthcare and Premier. This recognition is based on a national quality analysis that evaluates clinical, operational, financial, and patient experience measures. Intermountain Medical Center in Murray, Utah, was highlighted as one of the nation's top teaching hospitals. Other hospitals, including Intermountain St. George Regional, McKay-Dee, and Utah Valley, were recognized in the Large Community Hospital category. Additionally, Intermountain Layton Hospital was noted in the Small Community Hospital category. The recognition underscores the dedication of Intermountain Health's caregivers to providing high-quality care.
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AI Tool SIDISH Identifies High-Risk Cells in Aggressive Cancers

AI Tool SIDISH Identifies High-Risk Cells in Aggressive Cancers

Researchers have developed an AI tool named SIDISH, which stands for semi-supervised iterative deep learning for identifying single-cell high-risk populations. This tool is designed to pinpoint small groups of cells within tumors that are most responsible for driving aggressive cancers. By identifying these high-risk cells, SIDISH offers a new approach to designing targeted cancer therapies. The tool was tested on pancreatic, breast, and lung cancers, successfully identifying cells linked to poor patient outcomes. SIDISH also simulates how these cells respond to genetic changes, aiding in the identification of potential drug targets.