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News Article
60% of US patients uncomfortable with AI in healthcare settings, survey finds
Patient Safety Learning posted a news article in News
The adoption of AI tools to simplify processes and workflows is slowly occurring across all industries, including healthcare — though patients largely disagree with clinicians using those tools when providing care, the Pew Research Center survey found. The potential for AI tools to diminish personal connections between patients and providers is a key concern, according to the survey, which included responses from over 11,000 adults in the USA collected in December. Patients also fear their health records could become less secure. Respondents, however, acknowledged potential benefits, including that AI could reduce the number of mistakes providers make. They also expressed optimism about AI’s potential impact on racial and ethnic biases in healthcare settings, even as the technology has been criticised for exacerbating those issues. Among respondents who believe racial biases are an issue in healthcare, about half said they think the tools would reduce the problem, while 15% said it would make it worse and about 30% said it would stay the same. Read full story Source: Healthcare Dive, 23 February 2023 -
Content ArticleThe pandemic has highlighted several longstanding, systemic issues in healthcare, and clinician burnout is chief among them. From regulatory-related constraints to inefficient EHR workflows, a day in the life of a provider looks very different than what many envisioned when deciding to pursue a career in medicine. Additionally, the rate of staff departures and early retirements has put even more pressure on overburdened care teams. No single solution can solve this complex issue. In this Becker's Hospital Review eMagazine, experts share actionable strategies and industry trends that can help healthcare organizations support the providers. How to recognize early signs of burnout. Three ways AI can reduce providers’ administrative burdens. Using human-centered design to address burnout. How a 'platform of health' can dismantle burnout and increase collaboration. You will need to fill out the form on Becker's Hospital Review website to download the whitepaper.
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News Article
Technology can help the NHS, says AstraZeneca boss
Patient Safety Learning posted a news article in News
The chairman of Covid vaccine giant AstraZeneca has said that investment in technology can help the NHS cut costs. Leif Johansson said more spending on areas such as artificial intelligence and screening could prevent illness and stop people going to hospital. The NHS is under severe pressure, with A&E waits at record levels and strike action exacerbating ambulance delays. Mr Johansson said about 97% of healthcare costs come from "when people present at the hospital". He said only the remaining 3% is made up of spending on vaccination, early detection or screening. Mr Johansson told the BBC at the World Economic Forum in Davos: "If we can get into an investment mode in health for screening or prevention or early diagnostics on health and see that as an investment to reduce the cost of sickness then I think we have a much better model over time that would serve us well." Commenting on the UK, he said: "All countries have different systems and the NHS is one which we have learned to live with and I think the Brits, in general, are quite appreciative about it." He said he was not talking about "breaking any healthcare systems down". Rather, he said, "we should embrace technology and science". Read full story Source: BBC News, 23 January 2023 -
News ArticleTechnology that accurately predicts when patients will be ready to leave hospital upon their arrival in A&E is being introduced to solve the NHS bed-blocking crisis. The artificial intelligence (AI) software analyses data including age, medical conditions and previous hospital stays to estimate how long a patient will need to remain. Hospital managers can then alert social care services in advance about the date when patients are expected to be discharged, allowing care home beds or community care packages to be prepared. Nurses said the technology had “revolutionised” their ability to discharge patients on time, meaning people who would otherwise have been stuck in hospital had got home for Christmas. The new technology, developed by the British AI company Faculty, is being tested at four NHS hospitals in Wales belonging to the Hywel Dda health board. Analysis suggests that the tool will save NHS trusts 3,000 bed days and £1.4 million a year by speeding up discharges, which in turn frees beds for elective procedures such as hip replacements. Read full story (paywalled) Source: The Times, 26 December 2022
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Content ArticleAfter a prolonged battle with the COVID-19 pandemic, healthcare providers now face the next crisis that has been brewing even longer: staff shortages and an increasingly exhausted workforce. In early 2022, almost one in two (47%) healthcare professionals reported feeling burned out, up from 42% last year. Many consider leaving the field, adding to the worries of employers who see growing demand for care without enough hands at the bedside to cater for their patients. Can AI be part of the solution by helping healthcare professionals reclaim the joy in their work? An article by Philips.
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News ArticleVoices offer lots of information. Turns out, they can even help diagnose an illness — and researchers in the USA are working on an app for that. The National Institutes of Health is funding a massive research project to collect voice data and develop an AI that could diagnose people based on their speech. Everything from your vocal cord vibrations to breathing patterns when you speak offers potential information about your health, says laryngologist Dr. Yael Bensoussan, the director of the University of South Florida's Health Voice Center and a leader on the study. "We asked experts: Well, if you close your eyes when a patient comes in, just by listening to their voice, can you have an idea of the diagnosis they have?" Bensoussan says. "And that's where we got all our information." Someone who speaks low and slowly might have Parkinson's disease. Slurring is a sign of a stroke. Scientists could even diagnose depression or cancer. The team will start by collecting the voices of people with conditions in five areas: neurological disorders, voice disorders, mood disorders, respiratory disorders and pediatric disorders like autism and speech delays. This isn't the first time researchers have used AI to study human voices, but it's the first time data will be collected on this level — the project is a collaboration between USF, Cornell and 10 other institutions. The ultimate goal is an app that could help bridge access to rural or underserved communities, by helping general practitioners refer patients to specialists. Long term, iPhones or Alexa could detect changes in your voice, such as a cough, and advise you to seek medical attention. Read full story Source: NPR, 10 October 2022
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News ArticleA new report published by the NHS AI Lab and Health Education England (HEE) has advocated for training and education for providers in how they deliver and develop AI guidance for staff. The report, entitled ‘Developing healthcare workers’ confidence in AI (Part 2)’, is the second of two reports in relation to this research and follows the 2019 Topol Review recommendation to develop a healthcare workforce “able and willing” to use AI and robotics. It is also part of HEE’s Digital, AI and Robotics Technologies in Education (DART-ED) programme, which aims to understand the impact of advances of these technologies on the workforce’s education and training requirements. In the previous report, the AI Lab and HEE found that many clinicians and staff were unaccustomed to the use of AI technologies, and without the suitable training patients would not be able to experience and share the advantages. The new report has set out recommendations for education and training providers in England to support them in planning, resourcing, developing and delivering new training packages in this area. It notes that specialist training will also be required depending on roles and responsibilities such as involvement in implementation, procurement or using AI in clinical practice. Brhmie Balaram, Head of AI Research and Ethics at the NHS AI Lab, added: “This important new research will support those organisations that train our health and care workers to develop their curriculums to ensure staff of the future receive the training in AI they will need. This project is only one in a series at the NHS AI Lab to help ensure the workforce and local NHS organisations are ready for the further spread of AI technologies that have been found to be safe, ethical and effective.” Read full story Source: Health Tech Newspaper, 25 October 2022
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Content ArticleThis research is a collaboration between the NHS AI Lab and Health Education England. Its primary aim is to inform the development of education and training to develop healthcare workers’ confidence in artificial intelligence (AI).
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Content ArticleThis open access book addresses the future of work and industry by 2040—a core interest for many disciplines inspiring a strong momentum for employment and training within the industrial world. The future of industrial safety in terms of technological risk-management, although of obvious concern to international actors in various industries, has been quite sparsely addressed. This brief reflects the viewpoints of experts who come from different academic disciplines and various sectors such as oil and gas, energy, transportation, and the digital and even the military worlds, as expressed in debates and discussions during a two-day international seminar. 'Managing future challenges for safety' will interest and influence researchers considering the future effects of a number of currently developing technologies and their practitioner counterparts working in industry and regulation.
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News Article
AI eye checks can predict heart disease risk in less than minute, finds study
Patient Safety Learning posted a news article in News
An artificial intelligence (AI) tool that scans eyes can accurately predict a person’s risk of heart disease in less than a minute, researchers say. The breakthrough could enable ophthalmologists and other health workers to carry out cardiovascular screening on the high street using a camera – without the need for blood tests or blood pressure checks – according to the world’s largest study of its kind. Researchers found AI-enabled imaging of the retina’s veins and arteries can specify the risk of cardiovascular disease, cardiovascular death and stroke. They say the results could open the door to a highly effective, non-invasive test becoming available for people at medium to high risk of heart disease that does not have to be done in a clinic. “This AI tool could let someone know in 60 seconds or less their level of risk,” the lead author of the study, Prof Alicja Rudnicka, told the Guardian. If someone learned their risk was higher than expected, they could be prescribed statins or offered another intervention, she said. Speaking from a health conference in Copenhagen, Rudnicka, a professor of statistical epidemiology at St George’s, University of London, added: “It could end up improving cardiovascular health and save lives.” Read full story Source: The Guardian, 4 October 2022 -
Content ArticleA digital transformation is underway in healthcare and health technology. But what exactly do the smart hospitals of the future look like? Are we heading for a fully virtual health experience? Whether it’s AI and machine learning, or another form of innovation – it’s clear to see that health tech, and healthcare, is changing drastically. The words “smart hospital” and “virtual hospital wards” have eased their way into our vocabulary – and they will soon be the driving force of healthcare everywhere. So what would smart hospitals look like? And what should we be expecting between now and 2050? Health Tech World asked some of the leading experts in the field to give us their predictions as well as their expertise on what the healthcare of the next few decades will look like.
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Content ArticleThis report by the consultancy firm Deloitte looks at patient safety across biopharmaceutical (biopharma) value chains, arguing that change is needed to make medications safer for patients and add value to pharmaceutical products. The authors highlight that there is currently great potential for strategies to increase safety, improve equity and enhance patient engagement and experience. Advances in artificial intelligence (AI) technologies and data analytics, combined with increased incidence of adverse event reports (AERs) and increasing expectation of more personalised, preventative, predictive and participatory (4P) medicine, present an opportunity to improve pharmacovigilance.
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News Article
NHS to use AI to identify people at higher risk of hepatitis C
Patient Safety Learning posted a news article in News
The NHS is to use artificial intelligence to detect, screen and treat people at risk of hepatitis C under plans to eradicate the disease by 2030. Hepatitis C often does not have any noticeable symptoms until the liver has been severely damaged, which means thousands of people are living with the infection – known as the silent killer – without realising it. Left untreated, it can cause life-threatening damage to the liver over years. But with modern treatments now available, it is possible to cure the infection. Now health chiefs are launching a hi-tech screening programme in England in a fresh drive to identify thousands of people unaware they have the virus. The scheme, due to begin in the next few weeks, aims to help people living with hepatitis C get a life-saving diagnosis and access to treatment before it is too late. The NHS will identify people who may have the virus by using AI to scan health records for a number of key risk factors, such as historical blood transfusions or an HIV diagnosis. Anyone identified through the new screening process will be invited for a review by their GP and, if appropriate, further screening for hepatitis C. Those who test positive for the virus will be offered treatment available after NHS England struck a deal with three major pharmaceutical companies. Prof Graham Foster, national clinical chair for NHS England’s hepatitis C elimination programmes, said the scheme “marks a significant step forward” in the fight to eliminate the virus before 2030. It will “use new software to identify and test patients most at risk from the virus – potentially saving thousands of lives”, he added. Read full story Source: The Guardian, 31 July 2022 -
News Article
County Durham and Darlington improves patient safety with AI
Patient Safety Learning posted a news article in News
County Durham and Darlington NHS Foundation Trust has created and implemented an artificial intelligence (AI) model to protect patients from acute kidney injury (AKI). The trust’s AI-driven model helps healthcare staff to identify patients who are at risk from AKI and to swiftly respond with treatment. The technology uses risk stratification digital tools that staff are able to access through an app. These are combined with care processes developed at the trust and which involve a new specialist nurse team, preventive specialist intervention, assessment and follow-up. Its implementation at County Durham and Darlington has led to a reduction in both hospital-acquired and community AKI. Overall, the incidence of AKI within the trust fell from 6.5% between March and May 2020, to 3.8% during the same period in 2021. The most significant reduction was seen in hospital-acquired AKI – which fell by more than 80%. Jeremy Cundall, medical director for County Durham and Darlington NHS Foundation Trust and executive lead for the project, said: “The partnership has resulted in patients being detected earlier – preventing AKI from occurring or mitigating the worsening of existing AKI. Accordingly, patients have been more effectively triaged to the right pathways of care including referral and transfer to tertiary renal units where appropriate.” Claire Stocks, early detection, resuscitation and mortality lead nurse for County Durham and Darlington NHS Foundation Trust, said: “This work has been a project very much about using collaborative partnerships to enhance patient safety and quality. An idea that was developed in a ‘cupboard conversation’ is now a fully operational specialist nurse service. Utilising digital innovations supports rapid triage, early detection and treatment to improve outcomes.” In addition to the improvements in patient safety, the technology has delivered cost savings for the trust too. County Durham and Darlington saved more than £2million in direct costs from reductions in AKI incidence. The improved transfer of patients has also released ICU capacity, vital at a time when the NHS is dealing with a growing national backlog for elective surgery. Read full story Source: Digital Health, 27 July 2022 -
Content ArticleAn increasing number of healthcare artificial intelligence (AI) applications are in development or already in use, but the safety impact of using AI in healthcare is largely unknown. This qualitative study in the journal Safety Science aimed to explore how different stakeholders (patients, hospital staff, technology developers and regulators) think about safety and the safety assurance of healthcare AI. Through a series of interviews, the authors assessed stakeholder perceptions of an AI-based infusion pump in the intensive care unit. Participants expressed perceptions about: the potential impact of healthcare AI requirements for human-AI interaction safety assurance practices and regulatory frameworks for AI and the gaps that exist how incidents involving AI should be managed. The authors concluded that there is currently a technology-centric focus on AI safety, and a wider systems approach is needed. They also identified a need for greater awareness of existing standards and best practice among technology developers.
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Content Article
This is part of our series of Patient Safety Spotlight interviews, where we talk to people working for patient safety about their role and what motivates them. Clive talks to us about the important role of digital technologies in tackling the big issues healthcare faces, the need for digital tools and records to be joined-up and interoperable, and how his experiences as a carer have shaped how he sees patient safety. -
News ArticleArtificial intelligence (AI) could lead to UK health services that disadvantage women and ethnic minorities, scientists are warning. They are calling for biases in the systems to be rooted out before their use becomes commonplace in the NHS. They fear that without that preparation AI could dramatically deepen existing health inequalities in our society. A new study has found that AI models built to identify people at high risk of liver disease from blood tests are twice as likely to miss disease in women as in men. The researchers examined the state of the art approach to AI used by hospitals worldwide and found it had a 70% success rate in predicting liver disease from blood tests. But they uncovered a wide gender gap underneath – with 44% of cases in women missed, compared with 23% of cases among men. “AI algorithms are increasingly used in hospitals to assist doctors diagnosing patients. Our study shows that, unless they are investigated for bias, they may only help a subset of patients, leaving other groups with worse care,” said Isabel Straw, of University College London, who led the study. “We need to be really careful that medical AI doesn’t worsen existing inequalities.” Read full story Source: iNews, 9 July 2022
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Content ArticleThe Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require scrutiny for potential biases. Isabel Straw and Honghan Wu address this overlooked issue by investigating ILPD models for sex bias. They demonstrated a sex disparity that exists in published ILPD classifiers. In practice, the higher false negative rate for females would manifest as increased rates of missed diagnosis for female patients and a consequent lack of appropriate care. Our study demonstrates that evaluating biases in the initial stages of machine learning can provide insights into inequalities in current clinical practice, reveal pathophysiological differences between the male and females, and can mitigate the digitisation of inequalities into algorithmic systems. An awareness of the potential biases of these systems is essential in preventing the digital exacerbation of healthcare inequalities.
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News Article
Wrist-worn trackers can detect Covid before symptoms, study finds
Patient Safety Learning posted a news article in News
Health trackers worn on the wrist could be used to spot Covid-19 days before any symptoms appear, according to researchers. Growing numbers of people worldwide use the devices to monitor changes in skin temperature, heart and breathing rates. Now a new study shows that this data could be combined with artificial intelligence (AI) to diagnose Covid-19 even before the first tell-tale signs of the disease appear. “Wearable sensor technology can enable Covid-19 detection during the presymptomatic period,” the researchers concluded. The findings were published in the journal BMJ Open. The discovery could lead to health trackers being adapted with AI to detect Covid-19 early, simply by spotting basic physiological changes. This could help provide an early warning system to users that they may be infected, which may in turn help to prevent the spread of the disease more widely. Read full story Source: The Guardian, 21 June 2022 -
Content Article
This is part of our series of Patient Safety Spotlight interviews, where we talk to people working for patient safety about their role and what motivates them. Mark talks to us about how he came to work in healthcare, the vital role of safety scientists and human factors specialists in improving patient safety, and the challenges involved in integrating new technologies into the health system. -
Content ArticleThis report explores the factors influencing healthcare workers’ confidence in AI-driven technologies. A second report will detail how their confidence can be developed through education and training.
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Content ArticleHuge numbers of patients suffer avoidable harm in US hospitals each year as a result of unsafe care. In this blog, published in the Harvard Business Review, the authors argue that these numbers could be greatly reduced by taking four actions: Make patient safety a top priority in hospitals’ practices and cultures, establish a National Patient Safety Board, create a national patient and staff reporting mechanism, and turn on EHRs machine learning systems that can alert staff to risky conditions.
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Content Article
The medical algorithmic audit (5 April 2022)
Mark Hughes posted an article in Artificial Intelligence
Artificial intelligence systems for healthcare, like any other medical device, have the potential to fail. In this article, published in The Lancet: Digital Health, the authors recommend a medical algorithmic audit framework as a tool that can be used to better understand the weaknesses of an artificial intelligence system and put in place mechanisms to mitigate their impact. They propose that this framework should be the joint responsibility of users and developers who can collaborate to ensure patient safety and correct performance of the system in question. -
News Article
New algorithm will improve bowel-cancer patient care
Patient Safety Learning posted a news article in News
An algorithm which can predict how long a patient might spend in hospital if they’re diagnosed with bowel cancer could save the NHS millions of pounds and help patients feel better prepared. Experts from the University of Portsmouth and the Portsmouth Hospitals University NHS Trust have used artificial intelligence and data analytics to predict the length of hospital stay for bowel cancer patients, whether they will be readmitted after surgery, and their likelihood of death over a one or three-month period. The intelligent model will allow healthcare providers to design the best patient care and prioritise resources. Bowel cancer is one of the most common types of cancer diagnosed in the UK, with more than 42,000 people diagnosed every year. Professor of Intelligent Systems, Adrian Hopgood, from the University of Portsmouth, is one of the lead authors on the new paper. He said: “It is estimated that by 2035 there will be around 2.4 million new cases of bowel cancer annually worldwide. This is a staggering figure and one that can’t be ignored. We need to act now to improve patient outcomes. “This technology can give patients insight into what they’re likely to experience. They can not only be given a good indication of what their longer-term prognosis is, but also what to expect in the shorter term. “If a patient isn’t expecting to find themselves in hospital for two weeks and suddenly they are, that can be quite distressing. However, if they have a predicted length of stay, they have useful information to help them prepare. “Or indeed if a patient is given a prognosis that isn’t good or they have other illnesses, they might decide they don’t want a surgical option resulting in a long stay in hospital.” Read full story Source: University of Plymouth, 30 March 2022 -
News Article
AI software predicting daily A&E admissions rolled out in 100 NHS hospitals
Patient Safety Learning posted a news article in News
New artificial intelligence software being rolled-out in NHS hospitals will be able to predict daily A&E admissions weeks in advance. The software, which launched in 100 hospitals across England on Monday, analyses data, including Covid infections rates, 111 calls and traffic to predict the number of patients that will seek emergency care. It also takes into consideration public holidays, such as New Year’s Eve, when A&E is more likely to be busy. The AI software is being rolled after trials showed an “impressive” ability to forecast admissions up to three weeks in advance. The NHS believes it will help tackle the record waiting list and allow hospitals to more easily manage their patient and bed capacity, prepare for busier days and staff up when needed. Nine trusts were given the software to use during the pandemic which notified them of expected spikes in cases, staff levels and numbers of beds and equipment necessary. However, hospitals receiving the new equipment have also been warned uncertainties within the data mean the system should be used as a “starting point to consider an operational response, not as a definite signal for action.” Read full story Source: The Independent, 28 March 2022
