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Community Post
Better use of data for medication safety in hospitals
Kenny Fraser posted a topic in Medicine management
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NHS hospital staff spend countless hours capturing data in electronic prescribing and medicines administration systems. Yet that data remains difficult to access and use to support patient care. This is a tremendous opportunity to improve patient safety, drive efficiencies and save time for frontline staff. I have just published a post about this challenge and Triscribe's solution. I would love to hear any comments or feedback on the topic... How could we use this information better? What are hospitals already doing? Where are the gaps? Thanks- Posted
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Content Article
Better use of data for medication safety in hospitals
Kenny Fraser posted an article in Medicine management
NHS hospital staff spend countless hours capturing data in electronic prescribing and medicines administration systems. Yet that data remains difficult to access and use to support patient care. This is a tremendous opportunity to improve patient safety, drive efficiencies and save time for frontline staff. In this blog, Kenny Fraser, CEO of Triscribe, explains why we need to deliver quick, low-cost improvement using modern, open source software tools and techniques. We don’t need schemes and standards or metrics and quality control. The most important thing is to build software for the needs and priorities of frontline pharmacists, doctors and nurses. -
Content ArticlePatient satisfaction surveys rely largely on numerical ratings, but applying artificial intelligence (AI) to analyse respondents’ free-text comments can yield deeper insights. AI presents the ability to reveal insights from large sets of this type of unstructured data. The authors’ analysis here presents AI-enabled insights into what different racial and ethnic groups of patients say about physicians’ courtesy and respect. This analysis illustrates one method of leveraging AI to improve the quality and value of care.
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News ArticleThe adoption of artificial intelligence (AI) by the NHS should be faster, and more frameworks should be in place to get emerging technologies to as many patients as possible, experts have told MPs. A number of senior figures from medicine and biotechnology gave evidence to the Health and Social Care Committee as part of its inquiry into cancer technology. Stephen Duffy, a professor of cancer screening at the Wolfson Institute of Population Health at Queen Mary University of London, told MPs there is “strong potential” for AI, particularly in areas such as reading mammograms for the breast screening programme. However, he warned that there will be “staff issues in terms of the number of staff needed to double-read mammograms”. He added: “Those issues aren’t going away. It seems to me that AI systems have already been shown to be very good in terms of detection of cancer on from mammograms, so they’re safe in that respect. Read full story Source: The Independent, 19 July 2023
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Content ArticleGenerative AI is being heralded in the medical field for its potential to ease the burden of medical documentation by generating visit notes, treatment codes and medical summaries. Doctors and patients might also turn to generative AI to answer medical questions about symptoms, treatment recommendations or potential diagnoses. This article in JAMA Network looks at the liability implications of using AI to generate health information, highlighting that no court in the US has yet considered the question of liability for medical injuries caused by relying on AI-generated information.
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News ArticleCheshire and Merseyside won Gold in the ‘Supporting Elective Recovery Through Digital’ category, at the HSJ Digital Awards, alongside technology partner C2-Ai, after transforming how waiting lists are managed with the help of an AI-backed waiting list model. The tool helps surgical teams identify previously hidden high-risk patients, and to make informed decisions on how, when and where to treat patients to achieve the best outcomes. NHS England, who commissioned the project, reported that within six weeks patient waiting lists dropped by nearly 30%, as well as a 66% decrease in intensive care needs for high-risk patients, saved about 2,500 hospital bed-days across 20,000 patients, and cut emergency admissions to the waiting list by 8%. Read full story Source: NHS Cheshire and Merseyside, 3 July 2023
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Content ArticleWhat exactly is machine learning and how is it being used in healthcare? Are machines always better than a person? How do we know? In this interview, Patient Safety managing editor, Caitlyn Allen asks these questions of artificial intelligence healthcare researcher Dr Avishek Choudhury.
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News Article
AI cuts treatment time for cancer radiotherapy
Patient Safety Learning posted a news article in News
A new type of artificial-intelligence technology that cuts the time cancer patients must wait before starting radiotherapy is to be offered at cost price to all NHS trusts in England. It helps doctors calculate where to direct the therapeutic radiation beams, to kill cancerous cells while sparing as many healthy ones as possible. Researchers at Addenbrooke's Hospital trained the AI program with Microsoft. For each patient, doctors typically spend between 25 minutes and two hours working through about 100 scan cross-sections, carefully "contouring" or outlining bones and organs. But the AI program works two and a half times quicker, the researchers say. When treating the prostate gland, for example, medics want to avoid damage to the nearby bladder or rectum, which could leave patients with lifelong continence issues. Read full story Source: BBC News, 27 June 2023 -
News Article
AI to be deployed more widely across the NHS as new funding announced
Patient Safety Learning posted a news article in News
Artificial intelligence (AI) is set to be rolled out more widely across the NHS in a bid to diagnose diseases and treat patients faster. The Government has announced a £21 million funding pot that NHS trusts can apply for to implement AI tools for the likes of medical imaging and decision support. This includes tools that analyse chest X-rays in suspected cases of lung cancer. AI technology that can diagnose strokes will also be available to all stroke networks by the end of 2023 – up from 86% – and could help patients get treated faster and lead to better health outcomes. The Department of Health and Social Care (DHSC) said the technology could help cut NHS waiting lists ahead of winter. Read full story Source: The Independent, 23 June 2023 -
Event
Ethics and regulation for AI in health
Patient Safety Learning posted an event in Community Calendar
untilAs the adoption of artificial intelligence (AI) in health and care continues to progress rapidly, it's essential that clinicians ensure this technology is used for the benefit of patients and to assist us in providing equitable and high-quality care both now and in the future. However, it's also crucial that we are aware of the potential risks and unintended consequences of using AI. This month, the RSM will delve into the development of machine learning (ML) and AI and their applications to healthcare. It will also debate the need for ethical guidelines and regulation in this field. By attending this event, you will understand: What is machine learning and artificial intelligence. How AI is being currently applied to healthcare and the potential future uses. How data drives AI and the potential bias within the data. The way ML and AI can lead to errors and harm. The ethical issues surrounding the use of AI in healthcare. The need for regulations and governance, both in healthcare and the broader society. Register -
Content ArticleThe widespread adoption of effective hybrid closed loop systems would benefit people living with type 1 diabetes by improving the amount of time spent within target blood glucose range. Hybrid closed loop systems (also known as 'artificial pancreas' typically utilise simple control algorithms to select the best insulin dose for maintaining blood glucose levels within a healthy range. Online reinforcement learning has been utilised as a method for further enhancing glucose control in these devices. Previous approaches have been shown to reduce patient risk and improve time spent in the target range when compared to classical control algorithms, but are prone to instability in the learning process, often resulting in the selection of unsafe actions. This study in the Journal of Biomedical Informatics presents an evaluation of offline reinforcement learning for developing effective dosing policies without the need for potentially dangerous patient interaction during training.
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News Article
How chatbots are helping doctors be more human and empathetic
Patient Safety Learning posted a news article in News
Despite the drawbacks of turning to artificial intelligence in medicine, some US physicians find that ChatGPT improves their ability to communicate with patients. Last year, Microsoft and OpenAI released the first free version of ChatGPT. Within 72 hours, doctors were using the artificial intelligence-powered chatbot. Experts expected that ChatGPT and other A.I.-driven large language models could take over mundane tasks that eat up hours of doctors’ time and contribute to burnout, like writing appeals to health insurers or summarising patient notes. However, they found that doctors were asking ChatGPT to help them communicate with patients in a more compassionate way. Dr Michael Pignone, the chairman of the department of internal medicine at the University of Texas at Austin, has no qualms about the help he and other doctors on his staff got from ChatGPT to communicate regularly with patients. However, skeptics like Dr Dev Dash, who is part of the data science team at Stanford Health Care, are so far underwhelmed about the prospect of large language models like ChatGPT helping doctors. In tests performed by Dr Dash and his colleagues, they received replies that occasionally were wrong but, he said, more often were not useful or were inconsistent. If a doctor is using a chatbot to help communicate with a patient, errors could make a difficult situation worse. Read full story (paywalled) Source: New York Times, 12 June 2023 -
Content ArticleWhen people don't feel their actions will make a difference because of the vast scale of a problem, they are less likely to act, and this has implications for attempts to improve patient safety and reduce avoidable harm. In this article, Brian Resnick, science and health editor at Vox, interviews psychologist Paul Slovic, who has been researching human responses to risk and compassion since the 1970s. They discuss the psychological impact of large numbers of people on our ability and willingness to respond compassionately and to act on that compassion. They look at Slovic's research into the concepts of psychic numbing and the prominence effect, focusing on the global refugee crisis and why individuals and governments fail to act in the face of immense suffering.
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Content ArticleHealthcare systems rely on self-advocacy from service users to maintain the safety and quality of care. Systemic bias, service pressures and workforce issues often deny agency to patients at times when they need to have most control over representation of their story. This drives diagnostic error, treatment delay or failure to treat important conditions. In maternal care, perinatal mental health and thrombosis are significant challenges. With funding from SBRI Health care, Ulster University and Southern Health and Social Care Trust are developing an NLP powered platform that will empower mothers to be more active agents in their perinatal care. Download the poster below.
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News Article
Untested AI-based tools could harm patients, WHO warns
Patient Safety Learning posted a news article in News
As excitement builds throughout health and information systems worldwide over the rich potential benefits of new tools generated by artificial intelligence (AI), the World Health Organization (WHO) has called for action to ensure that patients are properly protected. Cautionary measures normally applied to any new technology are not being exercised consistently with regard to large language model (LLM) tools, which use AI for crunching data, creating content, and answering questions, WHO warned. “Precipitous adoption of untested systems could lead to errors by healthcare workers, cause harm to patients, erode trust in AI, and thereby undermine or delay the potential long-term benefits and uses of such technologies around the world,” the agency said. As such, WHO proposed that these concerns are addressed and clear evidence of benefits are measured before their widespread use in routine health care and medicine. Read full story Source: United Nations News, 16 May 2023 -
Content ArticleThis article looks at the experience of Tammy Dobbs, who has cerebral palsy and requires extensive support from home carers to carry out daily tasks. In 2016, Tammy's care needs were reassessed by the state of Arkansas where she lives, and the hours of support she was eligible to receive were cut in half. The change in eligibility was due to a new state-approved algorithm that had calculated her support needs in a new way, in spite of the fact that there was no change to her level of need. The situation caused Tammy much distress and resulted in drastic life changes. The article highlights the issues associated with the use of algorithms to determine need and allocate resources in health and social care. It also raises questions about what transparency means in an automated age and highlights concerns about people’s ability to contest decisions made by machines.
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News Article
Artificial intelligence could ‘transform’ heart attack diagnosis, scientists say
Patient Safety Learning posted a news article in News
Artificial intelligence (AI) could be “transformational” in improving heart attack diagnosis to reduce pressure on emergency departments, a new study suggests. Doctors could soon use an algorithm developed using AI to diagnose heart attacks with better speed and accuracy than ever before, the research from the University of Edinburgh indicates. It could also help tackle dangerous inequalities in diagnosing the condition, scientists suggest. Researchers found that, compared to current testing methods, the algorithm called CoDE-ACS was able to rule out a heart attack in more than double the number of patients, with an accuracy of 99.6%. Nicholas Mills, British Heart Foundation (BHF) professor of cardiology at the Centre for Cardiovascular Science, University of Edinburgh, who led the research, said: “For patients with acute chest pain due to a heart attack, early diagnosis and treatment saves lives. “Unfortunately, many conditions cause these common symptoms, and the diagnosis is not always straight forward. “Harnessing data and artificial intelligence to support clinical decisions has enormous potential to improve care for patients and efficiency in our busy emergency departments.” Read full story Source: The Independent, 11 May 2023 -
Content ArticleMany AI models are being developed and applied to understand opioid use. However, authors of this paper, published in BMJ Innovations, found there is a need for these AI technologies to be externally validated and robustly evaluated to determine whether they can improve the use and safety of opioids.
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News ArticleA breakthrough AI model can determine a person's risk of developing pancreatic cancer with staggering accuracy, research suggests. Using medical records and information from previous scans, the AI was able to flag patients at a high risk of developing pancreatic cancer within the next three years with great accuracy. There are currently no full-proof scans for pancreatic cancer, with doctors using a combination of CT scans, MRIs and other invasive procedures to diagnose it. This keeps many doctors away from recommending these screenings. Over time, they also hope these AI models will help them develop a reliable way to screen for pancreatic cancer — which already exists for other types of the diseases. "One of the most important decisions clinicians face day to day is who is at high risk for a disease, and who would benefit from further testing, which can also mean more invasive and more expensive procedures that carry their own risks," Dr Chris Sander, a biologist at Harvard who contributed to the study, said. "An AI tool that can zero in on those at highest risk for pancreatic cancer who stand to benefit most from further tests could go a long way toward improving clinical decision-making." Read full story Source: Mail Online, 9 May 2023
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News Article
AI poses existential threat and risk to health of millions, experts warn
Patient Safety Learning posted a news article in News
AI could harm the health of millions and pose an existential threat to humanity, doctors and public health experts have said as they called for a halt to the development of artificial general intelligence until it is regulated. Artificial intelligence has the potential to revolutionise healthcare by improving diagnosis of diseases, finding better ways to treat patients and extending care to more people. But the development of artificial intelligence also has the potential to produce negative health impacts, according to health professionals from the UK, US, Australia, Costa Rica and Malaysia writing in the journal BMJ Global Health. The risks associated with medicine and healthcare “include the potential for AI errors to cause patient harm, issues with data privacy and security and the use of AI in ways that will worsen social and health inequalities”, they said. One example of harm, they said, was the use of an AI-driven pulse oximeter that overestimated blood oxygen levels in patients with darker skin, resulting in the undertreatment of their hypoxia. Read full story Source: The Guardian, 10 May 2023 -
News Article
New artificial intelligence tool can accurately identify cancer
Patient Safety Learning posted a news article in News
Doctors, scientists and researchers have built an artificial intelligence (AI) model that can accurately identify cancer in a development they say could speed up diagnosis of the disease and fast-track patients to treatment. Cancer is a leading cause of death worldwide. It results in about 10 million deaths annually, or nearly one in six deaths, according to the World Health Organization. In many cases, however, the disease can be cured if detected early and treated swiftly. The AI tool designed by experts at the Royal Marsden NHS foundation trust, the Institute of Cancer Research, London, and Imperial College London can identify whether abnormal growths found on CT scans are cancerous. The algorithm performs more efficiently and effectively than current methods, according to a study. The findings have been published in the Lancet’s eBioMedicine journal. “In the future, we hope it will improve early detection and potentially make cancer treatment more successful by highlighting high-risk patients and fast-tracking them to earlier intervention,” said Dr Benjamin Hunter, a clinical oncology registrar at the Royal Marsden and a clinical research fellow at Imperial. Read full story Source: The Guardian, 30 April 2023- Posted
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Content ArticleIn this article, published by Inflect Health, ER doctor Josh Tamayo-Sarver explains what happened when he asked artificial intelligence chatbot ChatGPT to provide possible diagnoses based on his case notes.
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Content ArticleTechnologies abstract intelligence and provide predictor and precision insight in workflows that manage disorders, similar to cardiology and hematological disease. Positive perceptions of Artificial Intelligence (AI) that support Machine Learning (ML) and Deep Learning (DL) manage transformations with a safe system that improves wellbeing. In sections, workflow introduces an eXamination (X = AI) as an end-to-end structure to culture workstreams in a step-by-step design to manage populace health in a governed system. The author undertook structure and practice reviews and appraised perspectives that impact the management of AI in public health and medicine.
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Content ArticleThis article looks at how Sheba Medical Center in Tel Aviv, one of the largest health systems in the region, has used artificial intelligence to turn around statistics on patient safety. In 2016, the Accelerate Redesign Collaborate Innovation Center at Sheba launched a an AI solution called Aidoc to read CT scans. It is being used to more accurately predict stroke and pulmonary embolism, allowing healthcare professionals to offer preventative treatment more quickly that when CT scans are read purely manually.
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News ArticleArtificial intelligence could help NHS surgeons perform 300 more transplant operations every year, according to British researchers who have designed a new tool to boost the quality of donor organs. Currently, medical staff must rely on their own assessments of whether an organ may be suitable for transplanting into a patient. It means some organs are picked that ultimately do not prove successful, while others that might be useful can be disregarded. Now experts have developed a pioneering method that uses AI to effectively score potential organs by comparing them to images of tens of thousands of other organs used in transplant operations. The project is being backed by NHS Blood and Transplant (NHSBT), which has almost 7,000 people in the UK on its waiting list for a transplant. “We at NHSBT are extremely committed to making this exciting venture a success,” said Prof Derek Manas, the organ donation and transplantation medical director of NHSBT. “This is an exciting development in technological infrastructure that, once validated, will enable surgeons and transplant clinicians to make more informed decisions about organ usage and help to close the gap between those patients waiting for and those receiving lifesaving organs.” Read full story Source: The Guardian, 1 March 2023
