'Don't be a child in Ludlow,' councillor warns
The midwife-led birthing unit at Ludlow Community Hospital shut in 2018, with the closure said to be a temporary measure. But it has not reopened, leaving Princess Royal Hospital, an acute site in Telford, as the only alternative for expectant mothers in Shropshire. In 2019, the local NHS proposed a maternity hub plan but no birthing units at the county's rural hospitals.Harris, who represents Labour on the local authority, is calling for more children's services to be based at Ludlow's hospital. She said the town was promised a new hospital in 2012 and an urgent care unit in 2015, but "neither has happened".Her Children's Health Care in Ludlow survey is backed by Ludlow Health Campaign, which fights service cuts.
'Battle for parents'
Health visitors and school nurse numbers were down, with Ludlow "missing out" as a result, Harris said. "It shouldn't be a battle for parents to get the care their children need."[Parents] shouldn't have to give up half a day for an appointment."STW ICS said Telford provided birthing care and the option of homebirth was available.It added families were going to Telford for a children's audiology service from The Shrewsbury and Telford Hospital NHS Trust and it was expected to return to Royal Shrewsbury Hospital following construction work.Health and care providers had worked to deliver new services and initiatives in and around Ludlow, STW ICS stated, including developing a community and family hub.This included community health clinics, health visitor drop-in clinics and an early help team, providing advice with infant feeding and breastfeeding and special educational needs and disability.There were also services commissioned by NHS Shropshire, Telford and Wrekin and Shropshire Council, delivered across health, education, social care and the voluntary sector.Shropshire Community Health trust provided services in people's homes, within schools and through clinics, including health visiting and school nursing, STW ICS said.
Follow BBC Shropshire on BBC Sounds, Facebook, X and Instagram.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Reuters
2 minutes ago
- Reuters
UnitedHealth jumps after 'vote of confidence' from Warren Buffett
Aug 15 (Reuters) - Shares of UnitedHealth Group (UNH.N), opens new tab surged more than 11% in premarket trading on Friday after a fresh investment from billionaire Warren Buffett's Berkshire Hathaway (BRKa.N), opens new tab boosted investor confidence in the troubled health conglomerate. The company is dealing with multiple challenges that have emerged in the last two years, including rising costs, a federal investigation into its government-backed health plans, a cyberattack at its technology unit that affected the personal information of over 192 million Americans, and the murder of its insurance unit chief in December. Long hailed as a reliable earnings performer, UnitedHealth missed Wall Street's profit expectations for the last two quarters, and its shares have dropped nearly 46% in 2025, making it the worst-performing stock on the blue-chip Dow Jones Industrial Average (.DJI), opens new tab this year. The shares were last up 11% at $301.42 in premarket trading. Buffett has swooped in with big investments in companies, in which he sees a long-term strategic value, during their periods of struggle. He invested heavily in Occidental Petroleum (OXY.N), opens new tab in 2019 as it tried to finance a merger with Anadarko Petroleum and has kept adding to his stake despite the company's weak stock performance. He famously took a stake in investment bank Goldman Sachs (GS.N), opens new tab at the height of the global financial crisis in 2008. "Buffett's purchase is a psychological reassurance to many investors that saw UnitedHealth as 'untouchable,' given the massive turbulence in the stock over the past few months," said Kevin Gade, chief operating officer at UnitedHealth investor Bahl & Gaynor. Berkshire owned 5.04 million UnitedHealth shares worth about $1.57 billion as of June 30, it said in a U.S. Securities and Exchange Commission filing on Thursday. Several other prominent hedge funds, including David Tepper's Appaloosa Management, Lone Pine Capital and Two Sigma Investments, also bought UnitedHealth's shares, regulatory filings showed on Thursday. While the "vote of confidence" from Buffett's investment validates the long-term value of UnitedHealth shares, the "management needs to regain trust and credibility with investors, and get back to its beat and raise reputation of the past," said James Harlow, senior vice president at Novare Capital Management. In May, CEO Andrew Witty abruptly stepped down amid rising operational and financial pressures, and Stephen Hemsley, who had run the company from 2006 to 2017, took over. Last month, the company projected full-year adjusted earnings per share of at least $16, well short of analysts' already lowered estimate of $20.91. UnitedHealth's shares are currently trading at about 15.8 times forward earnings estimates, below their five-year average of 19. "While UnitedHealth still faces elevated uncertainty, it is good to see that this renowned investment firm also believes the market is discounting assumptions that are too pessimistic for the long term, which is similar to our view," said Morningstar analyst Julie Utterback. Shares of rivals Centene (CNC.N), opens new tab, Humana (HUM.N), opens new tab and Molina Healthcare (MOH.N), opens new tab gained between 1.5% and 4% in premarket trading. Berkshire on Thursday also disclosed new stakes in steel maker Nucor (NUE.N), opens new tab, security products provider Allegion (ALLE.N), opens new tab and outdoor advertiser Lamar Advertising (LAMR.O), opens new tab. Nucor jumped 5.8% to $152.80.
Coin Geek
4 hours ago
- Coin Geek
Studies in US, UK warn of flaws in AI-powered health guidance
Getting your Trinity Audio player ready... Two recently published studies have revealed that generative artificial intelligence (AI) tools, including large language models (LLMs) ChatGPT and Gemini, produce misinformation and bias when used for medical information and healthcare decision-making. In the United States, researchers from a medical school at Mount Sinai published a study on August 2 showing that LLMs were highly vulnerable to repeating and elaborating on 'false facts' and medical misinformation. Meanwhile, across the Atlantic, the London School of Economics and Political Science (LSE) published a study shortly afterward that found AI tools used by more than half of England's councils are downplaying women's physical and mental health issues, creating a risk of gender bias in care decisions. Medical AI LLMs, such as OpenAI's ChatGPT, are AI-based computer programs that generate text using large datasets of information on which they are trained. The power and performance of such technology have increased exponentially over the past few years, with billions of dollars being spent on research and development in the area. LLMs and AI tools are now being deployed across almost every industry, to different extents, not least in the medical and healthcare sector. In the medical space, AI is already being used for various functions, such as reducing the administrative burden by automatically generating and summarizing case notes, assisting in diagnostics, and enhancing patient education. However, LLMs are prone to the 'garbage in, garbage out' problem, relying on accurate, factual data making up their training material or they may reproduce the errors and bias in the datasets. This results in what is often known as 'hallucinations,' which is the generation of content that is irrelevant, made-up, or inconsistent with the input data. In a medical context, these hallucinations can include fabricated information and case details, invented research citations, or made-up disease details. US study shows chatbots spreading false medical information Earlier this month, researchers from the Icahn School of Medicine at Mount Sinai published a paper titled 'multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support.' The study aimed to test a subset of AI hallucinations that arise from 'adversarial attacks,' in which made-up details embedded in prompts lead the model to reproduce or elaborate on the false information. 'Hallucinations pose risks, potentially misleading clinicians, misinforming patients, and harming public health,' said the paper. 'One source of these errors arises from deliberate or inadvertent fabrications embedded in user prompts—an issue compounded by many LLMs' tendency to be overly confirmatory, sometimes prioritizing a persuasive or confident style over factual accuracy.' To explore this issue, the researchers tested six LLMs: DeepSeek Distilled, GPT4o, llama-3.3-70B, Phi-4, Qwen-2.5-72B, and gemma-2-27b-it, with 300 pieces of text similar to clinical notes written by doctors, but each containing a single fake laboratory test, physical or radiological sign, or medical condition. They were tested under 'default' (standard settings) as well as with 'mitigating prompts' designed to reduce hallucinations, generating 5,400 outputs. If a model elaborated on the fabricated detail, the case was classified as a 'hallucination.' The results showed that hallucination rates ranged from 50% to 82% across all models and prompting methods. The use of mitigating prompts lowered the average hallucination rate, but only from 66% without to 44% with a mitigating prompt. 'We find that the LLM models repeat or elaborate on the planted error in up to 83% of cases,' reported the researchers. 'Adopting strategies to prevent the impact of inappropriate instructions can half the rate but does not eliminate the risk of errors remaining.' They added that 'our results highlight that caution should be taken when using LLM to interpret clinical notes.' According to the paper, the best-performing model was GPT-4o, whose hallucination rates declined from 53% to 23% when mitigating prompts were used. However, with even the best-performing model producing potentially harmful hallucinations in almost a quarter of cases—even with mitigating prompts—the researchers concluded that AI models cannot yet be trusted to provide accurate and trustworthy medical data. 'LLMs are highly susceptible to adversarial hallucination attacks, frequently generating false clinical details that pose risks when used without safeguards,' said the paper. 'While prompt engineering reduces errors, it does not eliminate them… Adversarial hallucination is a serious threat for real‑world use, warranting careful safeguards.' The Mount Sinai study isn't the only recent paper published in the U.S. medical space that has brought into question the use of AI. In another damaging example, on August 5, the Annals of Internal Medicine journal reported a case of a 60-year-old man who developed bromism, also known as bromide toxicity, after consulting ChatGPT on how to remove salt from his diet. According to advice from the LLM, the man swapped sodium chloride (table salt) for sodium bromide, which was used as a sedative in the early 20th century, resulting in the rare condition. But it's not just the stateside that AI advice is taking a PR hit. UK study finds gender bias in LLMs While U.S. researchers were finding less-than-comforting results when testing whether LLMs reproduce false medical information, across the pond a United Kingdom study was turning up equally troubling results related to AI bias. On August 11, a research team from LSE, led by Dr Sam Rickman, published their paper on 'evaluating gender bias in large language models in long-term care,' in which they evaluated gender bias in summaries of long-term care records generated with two open-source LLMs, Meta's (NASDAQ: META) Llama 3 and Google's (NASDAQ: GOOGL) Gemma. In order to test this, the study created gender-swapped versions of long-term care records for 617 older people from a London local authority and asked the LLMs to generate summaries of male and female versions of the records. While Llama 3 showed no gender-based differences across any metrics, Gemma displayed significant differences. Specifically, male summaries focused more on physical and mental health issues. Language used for men was also more direct, while women's needs were 'downplayed' more often than men's. For example, when Google's Gemma was used to generate and summarize the same case notes for men and for women, language such as 'disabled,' 'unable,' and 'complex' appeared significantly more often in descriptions of men than women. In other words, the study found that similar care needs in women were more likely to be omitted or described in less severe terms by specific AI tools, and that this downplaying of women's physical and mental health issues risked creating gender bias in care decisions. 'Care services are allocated on the basis of need. If women's health issues are underemphasized, this may lead to gender-based disparities in service receipt,' said the paper. 'LLMs may offer substantial benefits in easing administrative burden. However, the findings highlight the variation in state-of-the-art LLMs, and the need for evaluation of bias.' Despite the concerns raised by the study, the researchers also highlighted the benefits AI can provide to the healthcare sector. 'By automatically generating or summarizing records, LLMs have the potential to reduce costs without cutting services, improve access to relevant information, and free up time spent on documentation,' said the paper. It went on to note that 'there is political will to expand such technologies in health and care.' Despite flaws, UK's all-in on AI British Prime Minister Keir Starmer recently pledged £2 billion ($2.7 billion) to expand Britain's AI infrastructure, with the funding targeting data center development and digital skills training. This included committing £1 billion ($1.3 billion) of funding to scale up the U.K.'s compute power by a factor of 20. 'We're going to bring about great change in so many aspects of our lives,' said Starmer, speaking to London Tech Week on June 9. He went on to highlight health as an area 'where I've seen for myself the incredible contribution that tech and AI can make.' 'I was in a hospital up in the Midlands, talking to consultants who deal with strokes. They showed me the equipment and techniques that they are using – using AI to isolate where the clot is in the brain in a micro-second of the time it would have taken otherwise. Brilliantly saving people's lives,' said the Prime Minister. 'Shortly after that, I had an incident where I was being shown AI and stethoscopes working together to predict any problems someone might have. So whether it's health or other sectors, it's hugely transformative what can be done here.' It's unclear how, or if, the LSE study and its equally AI-critical U.S. counterparts may affect such commitments from the government, but for now the U.K. at least seems set on pursuing the advantages AI tools such as LLMs can provide across the public and private sector. In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek's coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI. Watch: Demonstrating the potential of blockchain's fusion with AI title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen="">
The Sun
4 hours ago
- The Sun
Major diabetes breakthrough as world-first drug that STOPS the condition gets green light in the UK
A GROUNDBREAKING drug that slows down the development of type 1 diabetes has been licensed for use in the UK. Teplizumab can allow diabetes patients to live 'normal lives' without the need for insulin injections. 1 The decision by the Medicines and Healthcare Regulatory Agency (MHRA) has been hailed by experts as a 'breakthrough moment' that represents a 'turning point' in how the condition is treated. About 400,000 people in the UK have type 1 diabetes, a lifelong condition which causes the immune system to attack insulin-producing cells in the pancreas. Insulin helps the body use sugar for energy, and without this hormone, blood sugar levels can become dangerously high. Unlike type 2 diabetes, where the body is unable to make enough insulin or the insulin you do make doesn't work properly, the cause is less clear. And while type 2 diabetes can be improved through some simple lifestyle changes, type 1 diabetes requires lifelong treatment through insulin injections or pumps. Teplizumab trains the immune system to stop attacking pancreatic cells. It's taken by an IV drip for a minimum of 30 minutes over 14 consecutive days. The drug, which is already approved in the US, has been authorised for use by the MHRA to delay the onset of stage three type 1 diabetes in adults and children aged eight or over by an average of three years. Ahmed Moussa, general manager of general medicines UK and Ireland at Sanofi, which makes teplizumab, said: 'One hundred years ago the discovery of insulin revolutionised diabetes care. Today's news marks a big step forward.' The UK is the first country in Europe to be granted a licence. I'm a doctor and here are the six diabetes myths you need to know Type 1 diabetes develops gradually in three stages over months or years. Stage three is usually when people start to experience blood sugar problems and are diagnosed with the condition. According to the MHRA, teplizumab is used in people with stage two type 1 diabetes, which is an earlier stage of the disease during which patients are at a high risk of progressing to stage three. Parth Narendran, a professor of diabetes medicine at the University of Birmingham and The Queen Elizabeth Hospital Birmingham, said: 'Teplizumab essentially trains the immune system to stop attacking the beta cells in the pancreas, allowing the pancreas to produce insulin without interference. 'This can allow eligible patients to live normal lives, delaying the need for insulin injections and the full weight of the disease's daily management by up to three years. It allows people to prepare for disease progression rather than facing an abrupt emergency presentation.' Following the decision by the MHRA, the cost-effectiveness of teplizumab will be assessed by NHS spending watchdog the National Institute for Health and Care Excellence (Nice) to determine if it can be rolled out on the health service. Karen Addington, chief executive of the charity Breakthrough T1D, said: 'I am personally delighted and welcome the MHRA's approval of teplizumab. 'After years of research, clinical trials and drug development, we have an incredible breakthrough.' Reacting to the announcement, Dr Elizabeth Robertson, director of research and clinical at Diabetes UK, said: 'Today's landmark licensing of teplizumab in the UK marks a turning point in the treatment of type 1 diabetes. 'For the first time, we have a medicine that targets the root cause of the condition, offering three precious extra years free from the relentless demands of managing type 1 diabetes.' Dr Robertson added that the 'next steps are critical'. 'To ensure teplizumab reaches everyone who could benefit, we need it to be made available on the NHS, and the rollout of a screening programme to identify those with early-stage type 1 diabetes,' she said. How do you know if you have type 1 diabetes? The most common symptoms of type 1 diabetes are: peeing more than usual feeling very thirsty feeling very tired losing weight quickly without trying to Other symptoms can include: The symptoms develop quickly, over a few days or weeks. If it's not treated, it can lead to a serious condition called diabetic ketoacidosis. The condition usually starts in children and young adults, but it can happen at any age. You're more likely to get it if you have other problems with your immune system (autoimmune conditions), or if others in your family have type 1 diabetes or other autoimmune conditions. The symptoms are similar to type 2 diabetes, but type 2 diabetes usually develops more slowly and is more common in older people. Source: NHS
