Latest news with #UWMedicine
Yahoo
25-05-2025
- Health
- Yahoo
Medical errors are still harming patients. AI could help change that.
John Wiederspan is well aware of how things can go wrong in the high-pressure, high-stakes environment of an operating room. 'During situations such as trauma, or a patient doing poorly, there's a real rush to try and get emergency drugs into the patient as fast as possible,' said Wiederspan, a nurse anesthetist at UW Medicine in Seattle. 'And that's when mistakes can occur, when you're flustered, your adrenaline's rushing, you're drawing up drugs and you're trying to push them.' Despite ongoing efforts to improve patient safety, it's estimated that at least 1 in 20 patients still experience medical mistakes in the health care system. One of the most common categories of mistakes is medication errors, where for one reason or another, a patient is given either the wrong dose of a drug or the wrong drug altogether. In the U.S., these errors injure approximately 1.3 million people a year and result in one death each day, according to the World Health Organization. In response, many hospitals have introduced guardrails, ranging from color coding schemes that make it easier to differentiate between similarly named drugs, to barcode scanners that verify that the correct medicine has been given to the correct patient. Despite these attempts, medication mistakes still occur with alarming regularity. 'I had read some studies that said basically 90% of anesthesiologists admit to having a medication error at some point in their career,' said Dr. Kelly Michaelsen, Wiederspan's colleague at UW Medicine and an assistant professor of anesthesiology and pain medicine at the University of Washington. She started to wonder whether emerging technologies could help. As both a medical professional and a trained engineer, it struck her that spotting an error about to be made, and alerting the anesthesiologists in real time, should be within the capabilities of AI. 'I was like, 'This seems like something that shouldn't be too hard for AI to do,'' she said. 'Ninety-nine percent of the medications we use are these same 10-20 drugs, and so my idea was that we could train an AI to recognize them and act as a second set of eyes.' Michaelsen focused on vial swap errors, which account for around 20% of all medication mistakes. All injectable drugs come in labeled vials, which are then transferred to a labeled syringe on a medication cart in the operating room. But in some cases, someone selects the wrong vial, or the syringe is labeled incorrectly, and the patient is injected with the wrong drug. In one particularly notorious vial swap error, a 75-year-old woman being treated at Vanderbilt University Medical Center in Tennessee was injected with a fatal dose of the paralyzing drug vecuronium instead of the sedative Versed, resulting in her death and a subsequent high-profile criminal trial. Michaelsen thought such tragedies could be prevented through 'smart eyewear' — adding an AI-powered wearable camera to the protective eyeglasses worn by all staff during operations. Working with her colleagues in the University of Washington computer science department, she designed a system that can scan the immediate environment for syringe and vial labels, read them and detect whether they match up. 'It zooms in on the label and detects, say, propofol inside the syringe, but ondansetron inside the vial, and so it produces a warning,' she said. 'Or the two labels are the same, so that's all good, move on with your day.' Building the device took Michaelsen and her team more than three years, half of which was spent getting approval to use prerecorded video streams of anesthesiologists correctly preparing medications inside the operating room. Once given the green light, she was able to train the AI on this data, along with additional footage — this time in a lab setting — of mistakes being made. 'There's lots of issues with alarm fatigue in the operating room, so we had to make sure it works very well, it can do a near perfect job of detecting errors, and so [if used for real] it wouldn't be giving false alarms,' she said. 'For obvious ethical reasons, we couldn't be making mistakes on purpose with patients involved, so we did that in a simulated operating room.' In a study published late last year, Michaelsen reported that the device detected vial swap errors with 99.6% accuracy. All that's left is to decide the best way for warning messages to be relayed and it could be ready for real-world use, pending Food and Drug Administration clearance. The study was not funded by AI tech companies. 'I'm leaning towards auditory feedback because a lot of the headsets like GoPro or Google Glasses have built-in microphones,' she said. 'Just a little warning message which makes sure people stop for a second and make sure they're doing what they think they're doing.' Wiederspan has tested the device and said he's optimistic about its potential for improving patient safety, although he described the current GoPro headset as being a little bulky. 'Once it gets a bit smaller, I think you're going to get more buy-in from anesthesia providers to use it,' Wiederspan said. 'But I think it's going to be great. Anything that's going to make our job a little bit easier, spot any potential mistakes and help bring our focus back to the patient is a good thing.' Patient safety advocates have been calling for the implementation of error-preventing AI tools for some time. Dr. Dan Cole, vice chair of the anesthesiology department at UCLA Health and president of the Anesthesia Patient Safety Foundation, likened their potential for reducing risk to that of self-driving cars and improving road safety. But while Cole is encouraged by the UW study and other AI-based research projects to prevent prescribing and dispensing errors in pharmacies, he said there are still questions surrounding the most effective ways to integrate these technologies into clinical care. 'The UW trial idea was indeed a breakthrough,' he said. 'As with driverless taxis, I'm a bit reluctant to use the technology at this point, but based on the potential for improved safety, I am quite sure I will use it in the future.' Melissa Sheldrick, a patient safety advocate from Ontario who lost her 8-year-old son Andrew to a medication error in 2016, echoed those thoughts. Sheldrick said that while technology can make a difference, the root cause of many medical errors is often a series of contributing factors, from lack of communication to vital data being compartmentalized within separate hospital departments or systems. 'Technology is an important layer in safety, but it's just one layer and cannot be relied upon as a fail-safe,' she said. Others feel that AI can play a key role in preventing mistakes, particularly in demanding environments such as the operating room and emergency room, where creating more checklists and asking for extra vigilance has proved ineffective at stopping errors. 'These interventions either add friction or demand perfect attention from already overburdened providers in a sometimes chaotic reality with numerous distractions and competing priorities,' said Dr. Nicholas Cordella, an assistant professor of medicine at Boston University's Chobanian & Avedisian School of Medicine. 'AI-enabled cameras allow for passive monitoring without adding cognitive burden to clinicians and staff.' AI tools are likely to be deployed to prevent errors in an even broader range of situations. At UW Medicine, Michaelsen is considering expanding her device to also detect the volume of the drug present in a syringe, as a way of preventing underdosing and overdosing errors. 'This is another area where harm can occur, especially in pediatrics, because you've got patients [in the same department] where there can be a hundredfold difference in size, from a brand-new premature baby to an overweight 18-year-old,' she said. 'Sometimes we have to dilute medications, but as you do dilutions there's chances for errors. It isn't happening to every single patient, but we do this enough times a day and to enough people that there is a possibility for people to get injured.' Wiederspan said he can also see AI-powered wearable cameras being used in the emergency room and on the hospital floor to help prevent errors when dispensing oral medications. 'I know Kelly's currently working on using the system with intravenous drugs, but if it can be tailored to oral medications, I think that's going to help too,' Wiederspan said. 'I used to work in a cardiac unit, and sometimes these patients are on a plethora of drugs, a little cup full of all these pills. So maybe the AI can catch errors there as well.' Of course, broader uses of AI throughout a hospital also come with data protection and privacy concerns, especially if the technology happens to be scanning patient faces and screens or documents containing their medical information. In UW Medicine's case, Michaelsen said this is not an issue as the tool is only trained to look for labels on syringes, and does not actively store any data. 'Privacy concerns represent a significant challenge with passive, always-on camera technology,' Cordella said. 'There needs to be clear standards with monitoring for breaches, and the technology should be introduced with full transparency to both patients and health care staff.' He also noted the possibility of more insidious issues such as clinicians starting to excessively rely on AI, reducing their own vigilance and neglecting traditional safety practices. 'There's also a potential slippery slope here,' Cordella said. 'If this technology proves successful for medication error detection, there could be pressure to expand it to monitor other aspects of clinician behavior, raising ethical questions about the boundary between a supportive safety tool and intrusive workplace monitoring.' But while the prospect of AI entering hospitals on a wider basis certainly presents the need for stringent oversight, many who work in the operating room feel it has enormous potential to do good by keeping patients safe and buying medical professionals valuable time in critical situations. 'Time is of the essence in an emergency situation where you're trying to give blood, lifesaving medications, checking vital signs, and you're trying to rush through these processes,' Wiederspan said. 'I think that's where this kind of wearable technology can really come into play, helping us shave off vital seconds and create more time where we can really focus on the patient.' This article was originally published on
NBC News
25-05-2025
- Health
- NBC News
John Wiederspan puts on an AI-powered wearable camera designed to detect medication errors. David Jaewon Oh for NBC News Health news Medical errors are still harming patients. AI could help change that. Medication mistakes — where the wrong drug or the wrong dosage is given to a patient — are among the most common errors in medicine.
May 25, 2025, 5:00 AM EDT By David Cox John Wiederspan is well aware of how things can go wrong in the high-pressure, high-stakes environment of an operating room. 'During situations such as trauma, or a patient doing poorly, there's a real rush to try and get emergency drugs into the patient as fast as possible,' said Wiederspan, a nurse anesthetist at UW Medicine in Seattle. 'And that's when mistakes can occur, when you're flustered, your adrenaline's rushing, you're drawing up drugs and you're trying to push them.' Despite ongoing efforts to improve patient safety, it's estimated that at least 1 in 20 patients still experience medical mistakes in the health care system. One of the most common categories of mistakes is medication errors, where for one reason or another, a patient is given either the wrong dose of a drug or the wrong drug altogether. In the U.S., these errors injure approximately 1.3 million people a year and result in one death each day, according to the World Health Organization. In response, many hospitals have introduced guardrails, ranging from color coding schemes that make it easier to differentiate between similarly named drugs, to barcode scanners that verify that the correct medicine has been given to the correct patient. Despite these attempts, medication mistakes still occur with alarming regularity. 'I had read some studies that said basically 90% of anesthesiologists admit to having a medication error at some point in their career,' said Dr. Kelly Michaelsen, Wiederspan's colleague at UW Medicine and an assistant professor of anesthesiology and pain medicine at the University of Washington. She started to wonder whether emerging technologies could help. As both a medical professional and a trained engineer, it struck her that spotting an error about to be made, and alerting the anesthesiologists in real time, should be within the capabilities of AI. 'I was like, 'This seems like something that shouldn't be too hard for AI to do,'' she said. 'Ninety-nine percent of the medications we use are these same 10-20 drugs, and so my idea was that we could train an AI to recognize them and act as a second set of eyes.' The study Michaelsen focused on vial swap errors, which account for around 20% of all medication mistakes. All injectable drugs come in labeled vials, which are then transferred to a labeled syringe on a medication cart in the operating room. But in some cases, someone selects the wrong vial, or the syringe is labeled incorrectly, and the patient is injected with the wrong drug. In one particularly notorious vial swap error, a 75-year-old woman being treated at Vanderbilt University Medical Center in Tennessee was injected with a fatal dose of the paralyzing drug vecuronium instead of the sedative Versed, resulting in her death and a subsequent high-profile criminal trial. Michaelsen thought such tragedies could be prevented through 'smart eyewear' — adding an AI-powered wearable camera to the protective eyeglasses worn by all staff during operations. Working with her colleagues in the University of Washington computer science department, she designed a system that can scan the immediate environment for syringe and vial labels, read them and detect whether they match up. 'It zooms in on the label and detects, say, propofol inside the syringe, but ondansetron inside the vial, and so it produces a warning,' she said. 'Or the two labels are the same, so that's all good, move on with your day.' Building the device took Michaelsen and her team more than three years, half of which was spent getting approval to use prerecorded video streams of anesthesiologists correctly preparing medications inside the operating room. Once given the green light, she was able to train the AI on this data, along with additional footage — this time in a lab setting — of mistakes being made. 'There's lots of issues with alarm fatigue in the operating room, so we had to make sure it works very well, it can do a near perfect job of detecting errors, and so [if used for real] it wouldn't be giving false alarms,' she said. 'For obvious ethical reasons, we couldn't be making mistakes on purpose with patients involved, so we did that in a simulated operating room.' In a study published late last year, Michaelsen reported that the device detected vial swap errors with 99.6% accuracy. All that's left is to decide the best way for warning messages to be relayed and it could be ready for real-world use, pending Food and Drug Administration clearance. The study was not funded by AI tech companies. 'I'm leaning towards auditory feedback because a lot of the headsets like GoPro or Google Glasses have built-in microphones,' she said. 'Just a little warning message which makes sure people stop for a second and make sure they're doing what they think they're doing.' Wiederspan has tested the device and said he's optimistic about its potential for improving patient safety, although he described the current GoPro headset as being a little bulky. 'Once it gets a bit smaller, I think you're going to get more buy-in from anesthesia providers to use it,' Wiederspan said. 'But I think it's going to be great. Anything that's going to make our job a little bit easier, spot any potential mistakes and help bring our focus back to the patient is a good thing.' It isn't a fail-safe Patient safety advocates have been calling for the implementation of error-preventing AI tools for some time. Dr. Dan Cole, vice chair of the anesthesiology department at UCLA Health and president of the Anesthesia Patient Safety Foundation, likened their potential for reducing risk to that of self-driving cars and improving road safety. But while Cole is encouraged by the UW study and other AI-based research projects to prevent prescribing and dispensing errors in pharmacies, he said there are still questions surrounding the most effective ways to integrate these technologies into clinical care. 'The UW trial idea was indeed a breakthrough,' he said. 'As with driverless taxis, I'm a bit reluctant to use the technology at this point, but based on the potential for improved safety, I am quite sure I will use it in the future.' Melissa Sheldrick, a patient safety advocate from Ontario who lost her 8-year-old son Andrew to a medication error in 2016, echoed those thoughts. Sheldrick said that while technology can make a difference, the root cause of many medical errors is often a series of contributing factors, from lack of communication to vital data being compartmentalized within separate hospital departments or systems. 'Technology is an important layer in safety, but it's just one layer and cannot be relied upon as a fail-safe,' she said. Others feel that AI can play a key role in preventing mistakes, particularly in demanding environments such as the operating room and emergency room, where creating more checklists and asking for extra vigilance has proved ineffective at stopping errors. 'These interventions either add friction or demand perfect attention from already overburdened providers in a sometimes chaotic reality with numerous distractions and competing priorities,' said Dr. Nicholas Cordella, an assistant professor of medicine at Boston University's Chobanian & Avedisian School of Medicine. 'AI-enabled cameras allow for passive monitoring without adding cognitive burden to clinicians and staff.' AI is only going to be used more AI tools are likely to be deployed to prevent errors in an even broader range of situations. At UW Medicine, Michaelsen is considering expanding her device to also detect the volume of the drug present in a syringe, as a way of preventing underdosing and overdosing errors. 'This is another area where harm can occur, especially in pediatrics, because you've got patients [in the same department] where there can be a hundredfold difference in size, from a brand-new premature baby to an overweight 18-year-old,' she said. 'Sometimes we have to dilute medications, but as you do dilutions there's chances for errors. It isn't happening to every single patient, but we do this enough times a day and to enough people that there is a possibility for people to get injured.' Wiederspan said he can also see AI-powered wearable cameras being used in the emergency room and on the hospital floor to help prevent errors when dispensing oral medications. 'I know Kelly's currently working on using the system with intravenous drugs, but if it can be tailored to oral medications, I think that's going to help too,' Wiederspan said. 'I used to work in a cardiac unit, and sometimes these patients are on a plethora of drugs, a little cup full of all these pills. So maybe the AI can catch errors there as well.' Of course, broader uses of AI throughout a hospital also come with data protection and privacy concerns, especially if the technology happens to be scanning patient faces and screens or documents containing their medical information. In UW Medicine's case, Michaelsen said this is not an issue as the tool is only trained to look for labels on syringes, and does not actively store any data. 'Privacy concerns represent a significant challenge with passive, always-on camera technology,' Cordella said. 'There needs to be clear standards with monitoring for breaches, and the technology should be introduced with full transparency to both patients and health care staff.' He also noted the possibility of more insidious issues such as clinicians starting to excessively rely on AI, reducing their own vigilance and neglecting traditional safety practices. 'There's also a potential slippery slope here,' Cordella said. 'If this technology proves successful for medication error detection, there could be pressure to expand it to monitor other aspects of clinician behavior, raising ethical questions about the boundary between a supportive safety tool and intrusive workplace monitoring.' But while the prospect of AI entering hospitals on a wider basis certainly presents the need for stringent oversight, many who work in the operating room feel it has enormous potential to do good by keeping patients safe and buying medical professionals valuable time in critical situations. 'Time is of the essence in an emergency situation where you're trying to give blood, lifesaving medications, checking vital signs, and you're trying to rush through these processes,' Wiederspan said. 'I think that's where this kind of wearable technology can really come into play, helping us shave off vital seconds and create more time where we can really focus on the patient.' David Cox David Cox is a freelance journalist focusing on all aspects of health, from fitness and nutrition to infectious diseases and future medicines. Prior to becoming a full-time journalist, he was a neuroscientist attempting to understand how and why the brain goes wrong.
14-05-2025
- Health
Climber who survived 400-foot fall that killed 3 others was unconscious before seeking pay phone
A rock climber in Washington who survived a fall of hundreds of feet that killed his three companions lay unconscious for hours before waking in the dark, trekking out with internal bleeding and driving to a pay phone to summon help, authorities said he told them on Wednesday. Speaking from a Seattle hospital, Anton Tselykh, 38, confirmed investigators' theory that an anchor, called a piton, that he and his companions were using Saturday evening to rappel down the Early Winters Spires in the North Cascade Range had ripped out of the rock. Tselykh was in satisfactory condition Wednesday morning at Harborview Medical Center, meaning he was not in the intensive care unit, Susan Gregg, media relations director for UW Medicine, said in an email. One climber was rappelling off the piton — a metal spike pounded into rock cracks or ice that climbers anchor their ropes to — and the three others were tied into it and waiting to descend, said Cristina Woodworth, who leads the sheriff's search and rescue team and spoke with Tselykh by phone. When the piton tore out of the rock, all four plunged roughly 200 feet (60 meters) past sheer mountainside, landing in a gully and tumbling another 200 feet (60 meters) before coming to a rest, said Woodworth. It's still unclear if they had a backup anchor to the piton, which is a common practice for rock climbers, said Joshua Cole, a guide and co-owner of North Cascades Mountain Guides who has been climbing in the area for about 20 years. Tselykh lost consciousness for several hours, awaking in the dark in a tangle of ropes and gear, suffering from internal bleeding and head trauma, said Woodworth. It took Tselykh eight hours to disentangle himself, work his way down the rough terrain of rock and snow — with help from a pick-like ice tool — to his car, where he drove for some 40 miles (67 kilometers) to the unincorporated community of Newhalem and called for help, authorities said. The four climbers were friends, some of whom had climbed together before and appeared fairly experienced, Woodworth said, adding that Tselykh was 'obviously very much affected by this.' The climbers who were killed were Vishnu Irigireddy, 48; Tim Nguyen, 63; and Oleksander Martynenko, 36, the county coroner said. Olga Martynenko, Martynenko's wife, said Tuesday in a Facebook post that her husband, whom she referred to as Alex, also left behind their son. She shared a link to a fundraiser to help 'during the most devastating time of our lives.' 'I still cannot believe that you are gone, my love,' she said. Fluke Corporation, a test equipment manufacturing company, shared in a statement Wednesday that Irigireddy was the manufacturer's vice president of engineering. 'Vishnu was an extraordinary leader, and his loss is felt profoundly across our organization,' the statement read.
Yahoo
19-03-2025
- Health
- Yahoo
Expensive eggs: What are the protein alternatives?
Egg prices are skyrocketing across Washington as the Avian Flu infects millions of laying hens across the country. KIRO 7 has investigated which grocery stores are selling the most affordable eggs. Our team has also looked at whether renting chickens could save you some cash. Now we're looking at protein alternatives. One nutritionist at UW Medicine is offering up some ideas. Morgan Chojnacki says some affordable options include chicken, tuna, and even plant-based sources such as beans, seeds, and grains. 'I am always advocating for beans,' Chojnacki says. 'You can buy a can of beans for 89 cents. There are three servings in a can, and you're getting 8, 10, 15 grams of protein, depending on the bean.' Chojnacki also says nontraditional sources like teff flour, often used in dishes like injera, a pancake-like flatbread used in Ethiopian cuisine, and lentils, which are rich in both protein and fiber. For breakfast, Chojnacki says to consider alternatives to sugary cereals. 'Some of my favorite breakfast items are either like cottage cheese or yogurt with maybe some granola or nuts. I also really like oatmeal,' she says. She also advises focusing on accessible, nutrient-rich options to fuel the body's many essential processes.
Yahoo
28-02-2025
- Health
- Yahoo
World's Most Common Painkiller During Pregnancy Linked to ADHD
Very few painkillers are safe to use during pregnancy, and yet one of the only available options has become embroiled in an international debate in recent years. Acetaminophen, also known as paracetamol, is generally considered to be the safest painkiller to use during pregnancy, and yet emerging research that has linked the drug to attention deficit hyperactivity disorder (ADHD) suggests there may be overlooked risks to early brain development. In a small new study, researchers in the United States tracked bloodstream levels of acetaminophen in 307 Black women during their pregnancy. They found those who used acetaminophen later gave birth to children more than three times as likely to receive an ADHD diagnosis. For daughters, exposure to acetaminophen in the womb was linked to a more than six-fold increase in the risk of ADHD within the first ten years of life. While that sounds concerning on the surface, these initial results are not conclusive and should not scare off the large percentage of people who rely on acetaminophen during pregnancy for pain or fever. Especially since robust evidence shows both of those symptoms can be threats to a developing fetus if left untreated. As with any medicine, the benefits of acetaminophen must be balanced by the risks. Unlike its pros, however, the long-term cons are not as well researched. "This medication was… approved decades ago, and may need reevaluation by the FDA," argues pediatrician Sheela Sathyanarayana from UW Medicine. "Acetaminophen was never evaluated for fetal exposures in relation to long-term neurodevelopmental impacts." In recent years, several other epidemiology studies have found associations between acetaminophen use during pregnancy and ADHD outcomes in children, and yet some studies have produced conflicting results. All of these investigations are purely correlational and their findings are not a cause for alarm, some scientists argue, but rather, alertness. Because of the current study's small sample size, the data are probably not robust enough to change the minds of officials at the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), the American College of Obstetricians and Gynecologists (ACOG), the Society of Obstetricians and Gynecologists of Canada, and the Society for Maternal-Fetal Medicine – all of whom maintain that acetaminophen poses minimal risk when using the lowest dose as needed during pregnancy. For instance, the current study does not account for factors "like the mother's reason for taking [paracetamol], such as headaches or fevers or pains or infections, which we know are risk factors for adverse child development," statistical geneticist Viktor Ahlqvist from Sweden's Karolinska Institute, who was not involved in the current research, told Grace Wade at New Scientist. Nevertheless, lead author Brennan Baker, from Seattle Children's Research Institute, thinks it may be time for the FDA to take another look at acetaminophen's safety during pregnancy. The last time the FDA did so was in 2015, when officials declared there was inconclusive evidence to connect acetaminophen use in pregnancy and ADHD in children. "Most of the prior studies asked women to self-report whether they had taken Tylenol or anything that contained acetaminophen," explains Baker. In 2020, two studies (one led by Baker) measured acetaminophen levels in newborns and found that higher levels of the painkiller were linked with ADHD in childhood. One of these also found a link to autism spectrum disorder (ASD). In light of this initial data, an international team of 91 scientists, clinicians, and public health professionals came together to urge 'precautionary action'. "[Acetaminophen] is an important medication and alternatives for treatment of high fever and severe pain are limited," they wrote in a Consensus Statement for Nature Reviews Endocrinology in 2021. "We recommend that pregnant women should be cautioned at the beginning of pregnancy to: forego acetaminophen unless its use is medically indicated; consult with a physician or pharmacist if they are uncertain whether use is indicated and before using on a long-term basis; and minimize exposure by using the lowest effective dose for the shortest possible time." In response to the 2021 commentary, officials at ACOG held firm. "Neurodevelopmental disorders, in particular, are multifactorial and very difficult to associate with a singular cause. The brain does not stop developing until at least 15 months of age, which leaves room for children to be exposed to a number of factors that could potentially lead to these issues," they wrote in 2021. "ACOG's clinical guidance remains the same and physicians should not change clinical practice until definitive prospective research is done." A study on 307 pregnant people that needs to be replicated again is probably not going to cut it. "The conflicting results means that more research is needed," says Baker. The study was published in Nature Mental Health. Female Physicians Are Dying by Suicide at Astonishingly High Rates Study Finds Humans Age Faster at 2 Sharp Peaks – Here's When Extreme Heat Can Accelerate Aging, New Research Finds
