Transcripts For CSPAN Health 20240705

Witnesses and representatives also discuss the issue of data privacy and the need for federal regulation. The subcommittee will come to order in the chair will recognize itself for an Opening Statement for five minutes. I will spend my first little bit to say we have news on our Ranking Member and we Exchange Messages over thanksgiving weekend. What a wonderful lady, what a wonderful person and someone who really puts this committee, the subcommittee and the institution of congress. We have another year to Work Together. You will be sorely missed. Thank you. [applause] oh my goodness. [applause] thank you. We still have a year to get things done and we will get things done. I would just like to thank our witnesses for being here today. Ive got to get my statement in and four minutes. That was important. I should not use all my time. Thank you to our witnesses for being here today. Issues regarding Artificial Intelligence. It is important that we shine a light on a roll ai can play in solving some of our most significant healthcare problems. They are already changing the way in which clinicians pay for their patients and how they conduct Clinical Trials. As ai continues to drive innovation in healthcare it is essential that they examine the meaningful benefits at any potential unintended consequences that these technologies could have. The potential benefits are seemingly without limit. Technology could help our Healthcare System save lives by better predicting potential diagnosis and help us reduce redundancies in our system. We have already seen this play out in real time and i watch unimaginable advances in healthcare. As a result of generative ai. Numerous Success Stories and using Critical Research and development to give research to the market sooner. This was a case by mit scientists to be used as an effective antibiotic. They use ai to help detect earlystage cancers. It is being used to augment existing. This is not to say we should let the use of these technologies go without guardrails. Over the next several months, some fundamental questions regarding the role they will play in our Healthcare System. Trained with supervised ai to drive outcomes. Are these technologies trained with unsupervised ai . Based off Human Behavior for healthcare consumers. Are these technologies trained with reinforced ai which they are really rewarding the systems for which that is generated. They are very complex and difficult things we need to explore as we move forward. These cases are important to remember that every decision comes with a cost. Both human and financial. There constantly monitoring someones heart rate caloric intake and outtake in sleep patterns can help. Extreme cardiac event. Using user data to predict better lifestyle habits. How are we ensuring this data is secure and ensuring they have full control over this information and it is not being used or sold without their consent. A major health event. Are there protocols to ensure individuals are taking unnecessary trips to the emergency room and incurring debt as a result. In closing i support the real possibilities they can bring to our Healthcare System and most importantly to patients. We should get the technology the license to coexist alongside clinicians, patients and innovators as well as regulators while also remaining vigilant of how this technology is being used. I look forward to the discussion today and i will yield back and continue my praise for the Ranking Member. We have a year to Work Together. You treated me with most respect in the areas where we did not agree, you challenge my thinking sometimes. Sometimes we had to move forward it was always with the utmost respect. With that, i will recognize the Ranking Member for five minutes for her Opening Statement. Thank you very much, mr. Chairman. Your words mean a great deal to me. I am deeply moved and touched by the expression of the members of the subcommittee. You know how much i love this committee. We have gotten so many important things done, gotten them over the finish line. Lets optimize our time so we can continue that tradition. Thank you to each one of you. You are all my friends. My fellow americans, my fellow colleagues. There is so much that i want to say. Really, there are not words to express how deeply deeply grateful i am. And the messages board and, i kept them all and i reread them before i go to sleep at night. They are really beautiful. Its like falling asleep on this magnificent cloud of goodwill. Thank you from the bottom of my heart. Here we are to discuss ai and healthcare. The nexus between the two is really very, very important one. It represents an Incredible Opportunity for our country. It has the potential to make our Healthcare System more efficient improve on physicians. New ways to use ai in the Healthcare System are consistently in the news. I think all of you see this in your national clip as you read them at the end of every day. New york times in the october of this year. New diagnosis, brain tumors on the operating table. Forbes in august of this year. Ai is a game changer for toughest areas of Drug Discovery wall street journal in november of last year. While straightbacked researchers use ai to probe for weaknesses. Despite this incredible permit, ai we know and some of the fathers and mothers of ai have instructed us on the potential that ai has, its the other part of the spectrum to worsen Patient Outcome and exacerbate inequities that we have in our Healthcare System if it is not deployed with adequate guardrails. Earlier this month reports found that a lawsuit now alleges that United Health group, one of the largest insurers in our country used in ai algorithm to wrongfully deny medicare to beneficiaries. Yay i algorithm made decisions about patient care that went against the recommendations of the patients own physicians. Another example is our nations children are being left behind as ai and medical imaging rapidly expand. There are no computer aided detections, computerassisted triage or computer aided diagnosis radiology progress authorized for pediatric use is. These pediatric radiologists are working with children. You cannot experiment on children. In many areas, the red lights are blinking and we need to Pay Attention to that. Children are not little adults. I am working on a proposal to address this gap for pediatric patients. In my view and the view both republican and democratic members of both the house and the senate have created legislation that would democratize a i. Today the resources, massive resources are really in the hands of very large hightechnology companies. So we can get that over the finish line in this congress. So then please the witnesses are here. Im happy to beat with each one of you and my colleagues. I think this commit it can lead the effort on ai as it applies to health care. I dont think this is you know easy stuff. We have two rise to this challenge and i think we have the capacity to do so so thank you mr. Chairman and i yield back. Thank you. The gentlelady is back in the chair will recognize the Charitable Committee chair rodgers for five minutes. Mr. Chairman. My heartfelt warm wishes to the ranking democrat eshoo. Shes been a trailblazer for so many including me and im grateful for her outstanding leadership and your friendship these years. This is not a Court Hearing that the energy and Commerce Committee is held across our subcommittees on the subject of Artificial Intelligence. Artificial intelligence has the potential to transform every aspect of our lives for better or for worse. Its critical that america, not china is the one addressing the ai challenges in meeting in the technologys development. The best way to start is by laying the groundwork to protect peoples information with a National Data privacy standards. This is a foundational First Step Towards a safe and prosperous ai future in health care and beyond. I look forward to continuing to discuss how we can improve protections for americans as we incorporate ai tools. Im proud of each of our subcommittee chairs for leading on this important issue. Ai has a unique role to play in the future of health care. Ai can help find the next break through here or improve their ability to catch deadly diseases earlier. Weirsdale Artificial Intelligence can aid in the assessment of medical Indemnity Medical and then in anonymity and ease burdens on Health Care Providers for the recall heard from providers in her district about the burdens of necessary. Cumbersome paperwork and how often this leads to burnout for doctors and nurses and how it eats up time we could be spending providing patient care. For my entire tenure in congress one of the top issues that we have struggled with has been finding ways to cut paperwork redundantly in our Health Care System so we can let doctors do what doctors do best, treat their patients are at 4 years we have nibbled around the edges of this issue but the future of ai could be transformative and hopefully let doctors be doctors instead of administrative staff. We will hear more from doctors schlosser on hca how its being tested out of hospital stay to be clear a i will not solve all the problems with americas Health Care System. One concern we have frequently heard is the potential of human biases to be implicitly based into Ai Technology. The first piece of Health Care Legislation this committee advanced is my bill to ban the usage of quality adjusted life years or quality which are discriminatory measures that are used by federal payers to deny Health Care Services to people with disabilities and chronic illness. If the ai is reliant on quality or other similar measures in clinical decisionmaking are most vulnerable will be left behind. No one here wants to advocate for discrimination and we need to be conscious about federal programs and Ai Technology incorporates these types of biases and what we should be thinking about in this area. I will close by saying that im optimistic about this technology. Think these technologies can make a difference in the lives of patients in this committee needs to lead the way in this innovation. For america to lead we must strike the right balance with ai. He gives businesses the flexibility remain agile as they developed these cuttingedge technologies while assuring responsible use. A National Standard for the selection and handling of data will help Health Care Providers and every american was with clear understandable protections wherever they are. Todays hearing hopefully sheds more light on the current landscape of ai in health care and hopefully provide us with further insight on the next steps that we should take. I yield back. The gentlelady yields back. The chair will now recognize the gentleman from new jersey Ranking Member for an Opening Statement. Thank you mr. Chairman i want to start out by thinking or two democratic members of the subcommittee for their retirement at the end of next year. I told them both they should change their minds that they dont want to. Let me start with Ranking Member eshoo who served as the top democrat on the subcommittee for the last five years including four years as chair and she let the subcommittee. The cobra 19 pandemic played a Critical Role in our success for efforts to user fees but thats just in the last session. And shes been on the Health Care Committee for a long time. A lot of you dont know that i have worked with and not even before energy and Commerce Committee which he played a Critical Role outside of the committee in many ways particularly with the armenian corridor. If it was not for anna lee would not have recognized the Armenian Genocide which is so important in our history when that happened and we did that. So thank you anna and tony to say tony is a long time leader on the subcommittee. Hes also served as the vice chair for Consumer Protection and commerce subcommittee for years. Hes led several other key efforts to put consumers first including a new law that protects babies from dangerous sleeping products. Again i want to emphasize tonys role outside of the Commerce Committee. With the caucus, he has played a tremendous role in promoting not only latino members but also the issues that are important to them. In both cases ended in this case as well as tonys case what they have accomplished here is important for committee that goes beyond the committee so thank you both. I had to say we still have another year left of their contributions and they are still more to be done. Let me go if i can to the issue that we are dealing with today. We are exploring how Artificial Intelligence is changing health care now and potentially in the future. This is an important hearing because the integration that ai present opportunities in patient care and streamline product to bring more efficiency to the Health Sector and at the same Time Congress must recognize the complex ethical and economic and social concerns raised by this sector of the greater deployment of ai in the Health Care System but as we will hear data is central to the use of ai in the delivery of health care as the patients medical data protecting individual information of privacy. I remain concerned the use of ai and health care is generated a significant risk and critical safeguards in place to protect the privacy and security of the patients data and ive said that each of our ai hearing this era strongly believe is the bedrock of any ai regulation we must have a strong protections for all consumers. Ai cannot function without large quantities of data and we must ensure that this increase data demand does not come at the expense of consumers right to privacy. Im going to continue to push for a comprehensive National Privacy standard. Under the chair is just as concerned but i believe its the only way we can limit the unscrupulous Data Collection until practice. Its only way we can ensure all of her personal medical information is protected on line and protected against algorithmic bias in security breaches. Ais role in rich education of medical claim statistically poses a grave concern to me. Its my potential to revolutionize the Health Care Landscape a i answered mrs. Could result in the denial of medical care potentially worsening Health Equity. Right now the classaction lawsuit against a major use of ai to deny medical claims made ai systems played a role in the survival of over 300,000 payment requests in a twomonth period. The average time supposedly revealed its claim is 1. 2 seconds. Ai tools can aid in Health Care Providers but the recommendation should not serve as a substitute for the nuanced judgment of her Health Care Professionals. Ai has the potential to supplement medical decisions however when Health Care Companies driven by efficiencies implement ai suggestions without critical scrutiny i worry that patients could be put at risk. So theres a lot of work to be done here and i want to thank the chairman of the subcommittee and the chair of the full committee for prioritizing this. Thank you and i yield back. At the gentleman would deal for a couple seconds. I didnt see the tony come into the room when i talked about annie. Several issues and one i remember when we had issues to help Small Businesses that were affected and we are focused on working together. It was a great experience so congratulations to you and we have another year to Work Together. The gentleman yields back. Thanks and we well have more time to move forward this year. We will see what happens, right . Now that concludes member statements and we will move to our witnesses Opening Statements but i will introduce each one of you and calling you. If i introduce you as a group and call a new to give your Opening Statement and those of you who have not testified some of you may have not you have a green light. The green light is for five minutes quick sale five minutes to testify and in four minutes of a green light then you get a yellow light and once you have a yellow light you have one minute and when the red light hits its time to wrap up and move forward. Today i will first introduce dr. Michael schlosser Senior Vice President of transformation and innovation of nca health care. Dr. Benjamin nguyen and i hope that with the proper pronunciation of your name. Mr. Peter shen dr. Christopher longhurst chief officer in Association Data u. S. San diego health and also dr. David newmantaker director of the division of neural visual vestibular Disorders Department of neurology professor of neurology at Johns Hopkins university. Appreciate you all for being here taken the time to be here today. This hearing is important and i will begin by recognizing dr. Schlosser for five minutes free Opening Statement. Make sure your microphone is on. And you have it up to your face fuel lifted up towards you. Thank you subcommittee and make member and chairman and Ranking Member toll on and members of this committee for inviting me to testify here today. Im dr. Michael schlosser Senior Vice President for transformation innovation in health care. The background in neurosurgery and operations and involvement in health care with Ai Technology. I want to share my perspective on ai in health care. Our commitment to integrating Ai Health Care is driven by a vision to enhance patient care and Operational Efficiency and effectiveness. Our cases are focused largely and removing administrative work from provisions and providers so we can align the focus on patients critical decisionmaking and other highrisk activity. A lot of my colleagues function at the top of their licensing. Expanded Health Care Workforce at the time of and the tools to deliver a superior standard of care. To achieve these goals are first up was to develop a responsible ai Program Involving a robust government structure to ensure ai applications are fair robust accountable and continuously evaluated for safety. The program is governed and enables the use of ai across organizations. Ensuring that technology is used responsibly but also ensuring to take full advantage of these innovations and the benefits they provide to our care team impatience but i comes to privacy and security we have several decades of experience in protecting patient data to meet the challenges of deploying ai in a secure and private manner prevailing on our experience under the hepa standards we ensure that all are ai applications appeared to be strict. Data and output of any ai model could include protecting Health Information about our patients as well as the models themselves protected in the same way. Private and secure is a key feature of our responsible ai program. We are deploying a new Data Architecture to support ai in our ai agenda which focuses on identifying datasets. The primary source of Training Data. This allows for the use of large data to develop models based analytics without another safeguard we have implemented is a human centric approach to ai. In all of our ai locations we provide a human in the loop approach for this interest we leverage a upper efficiency and accuracy we dont compromise on safety and responsibility. The human model allows for ongoing Model Development and direct feedback providing inside the workflow. The more the models are used therefore the better they become. When it comes to ai driven Decision Support tools these are the models where they are directly advising on the treatment and diagnosis of patients they believe its an exciting opportunity for ai but an area that require significant can be deployed safety safely. Youre my final time let me add three examples of how we can bring ai into health care for the first is enhancing clinical documentation. We have a system in a partnership where ai can listen to a provider and the patient of emergencyroom in the er and then transcribe the event and using natural language processing turned into structured clinical documentations. Moving documentation to ai assistants mode rather than the doctor as a data analyst. The second is streamlining nurse and as handoff occurs for in a thousand times every week across their 183 hospitals but its a risky time during a transition of care. We have a large language model to read data in there for up to be able to interpret that data and create a handoff tool to the nurses after they review it themselves. This will bring standardization and safety to a highly variable time during care delivery. Finally we are using ai for staffing and scheduling. We taught an ai algorithm to understand the data surrounding power care teams are deployed in our hospital to care teams are most valuable resource in ensuring what we have the team at the right place at the right time with the assistance of ai algorithm to create more balance, fair and equitable schedules. In conclusion we are at dedicated to exploring and leveraging ai to enhance and improve Operational Efficiency and unfold the highest standards of privacy and security. We are committed to ongoing dialogue with congress and the subcommittee to help ensure the pathway forward to provide all the opportunities. Thank you for your Opening Statement. The chair now recognizes dr. Nguyen for five minutes for your Opening Statement. How is that . Can you hear me now . Thank you. Chairman guthrie Ranking Member eshoo chairwoman Morris Rodgers and Ranking Member pallone and members of the committee is my pleasure to appear before you today to discuss the ai is changing health care. My name is dr. Benjamin nguyen. I worked at the intersection of technology and care delivery throughout my career with a special focus on Artificial Intelligence. They make it easy for people to access highquality Affordable Health care and controls for Health Care Consumers in employersponsored health plans. Its not a Standard Health plan with their service to and meet the Health Care Journey for 4 million members an easy one. We help make their existing medical plan easier to understand and use. A platform is personalized for each member guiding them to care. We offer access to ondemand care teams and connect an ecosystem with the virtual care solutions. Or affiliated Virtual Clinic provides chat of videobased telemedicine visits for wide spectrum of primary care needs. In significant dan demand we use ai controls to improve the experience for members for reducing the administered a burden on clinicians. When a patient comes the Virtual Clinic in ai system begins to gather information from them about the reason for their visit so by the time the clinician sees the patient they have a detailed summary of the patients history but they can spend their time discussing the treatment decisions and followup care with the patient. Ai is helping these clinicians reduce the administered a burden and it frees them up to spend more time on the patients who need the most without replacing clinical but it want to paint a picture verheim nextgen ai can transform the way patients experienced health care. Imagine a single mother who uses english as a second language. It may be a 10 to 15 minute doctor vista but she may need 60 minutes to answer all they questions about her sons care. It makes this engagement challenging in a modern medical practice. Their patients in the waiting room and there arent enough partition or is. The thoughtfully built a system using extend technology can build partnership with physicians and supply information to her level of comfort or transferred to any nation she prefers. She can spend as much time she wants and needs too. A welldesigned system like this can help us move to onesizefitsall approach to many sizes approach. Years ago would have been immensely difficult and expensive to tailor a chat box to this womans need. This Technology Generative ai is it different nature than you may be familiar with but it can be applied to any domain but the most common application is in Large Language Models of power in the chat box for the chat box powered by this technology can converse with users grasps nuance topics and engage with the user. To use an analogy the technological leaps in ai that happen in five years to enable this are so great that they go from locomotives to powered flight and powered flights brings with it many opportunities. Because generative ai is not perfect and it has shortcomings even among ai companies and experts theres disagreement of best practices for capability safety risks of these new generative technologies much less how to mitigate them. Health cares has unique challenges and opportunities. We need to develop her own expertise and generative ai for this comes from the outside thes brings me to my last point which there is a significant growing gap in the health care. We need more doctors and nurses who are comfortable in speaking with ai and i know we are rightfully focused on teaching bedside medicine. Ensuring ai products are all americans equitably demands active participation from all levels of the Health Care System. We need the incentive frameworks and collective effort to create the opportunities to ensure that ai achieves the potential and changing the Health Care System for the better. Thank you for the opportunity to testify and id be happy to answer any questions you have. Thank you for your testimony. And mr. Shen you are recognized for five minutes free Opening Statement. Members of the subcommittee on the health of a nearly 17,000 employees in the United States and approximately 71,000 employees totally thank you for the opportunity to testify today, topic of Artificial Intelligence health care. My name is peter shen. My career focuses on the introduction of technologies in the Health Care Market including Artificial Intelligence. Its a leading Technology Company with more than 120s of history and break your innovation to market that enables Health Care Professionals to deliver the best care for their patient. Our corporate role includes imaging diagnostics and therapies augmented by Digital Technologies and Artificial Intelligence. We partner with more than 90 of the leading providers of health care address issues around population growth and disease management Health Care Workforce shortages and lack of access to care in underserved areas. But we have the distinction of being the only medical Technology Company capable of end and can secure from diagnosis to screening and survivorship or this is a responsibility we take very seriously as we keep patients at the center of everything we do. Human health has been working on applying technology for more than 20 years. Enter at all this in new jersey we new jersey we built one of most powerful supercomputing infrastructure dedicated to developing ai and health care but does allow the two collector. Organize correct and secure medical data and deliver accurate ai. We create and maintain a transparent Quality Assurance process which involves clinical validation guaranteeing the data being used between the ai is accurate for diagnosis and treating disease. This Training Data is based on a balance cohort of people of different ages and genders and ethnicities. The century we develop reliable accurate and unbiased a algorithms reflective of the Patient Population they will be applied towards. The patient journey is at the heart of human health ai work in ai helps improve outcomes for the patient at a ai helps patients undergoing a ct scan. Optimizing generating images while minimizing the time the patient is in the scanner. Radiologists can utilize their ai software as a companion to identify small nodules and other at rallies that they previously werent able to visualize without the assistance of ai. Suspicious lung nodules diagnosed to be ken chesebro declension could potentially be treated by Radiation Therapy which includes the task of manually drawing a unique contour to target radiation while observing healthy tissue. Our ai enabled software can automatically detect the contours of the cancerous area speeding up the patients time to treatment and eliminate unwarranted radiation. As siemens help commercial ai goes through approval process. They follow all ai enabled medical device regulatory requirements for freemarket review and close market surveillance to ensure safety and efficacy of our devices. We believe the rapid acceleration and innovation of ai medical devices the need for Regulatory Environment should be balance in innovation and adoption. While we believe the current rate of troy framework is sufficient to support innovation in ai we support the continuation of flexibility in the approval process as was the metric to facilitate global harmonization in the development of appropriate International Consensus standards. While cms is recognizing the value of the complex nature of ai the agencys reimbursement decisions have not uniformly and consistently ensured appropriate levels of payment for these ai products. To view and approach and limits access to patients benefiting from Ai Technology across their Health Care System especially in in underserved areas. We support a solution that ensures a predictable consistent approach to cms and approach that recognizes the cost of ai and reimbursement, ai analysis with separate Payment Systems so more data can be evaluated. See nisquallys ai has a Great Potential to include access to care diagnosed disease faster and make more precise treatment decisions. Rick said to see what the future holds for ai and health care. Again thank you for their pretended to testify before you today and i look forward to your questions. They think you for your test the money. Dr. Longhurst you are recognized for five minutes. Thank you members of the subcommittee for their pretended to speak with you today better experience in using ai models to improve health care delivery. Im a practicing pediatrician at the privilege of serving as the chief medical officer chief associate dean at uc health. We have been carefully evaluating and implementing models to enhance quality and safety for over five years and we believe our experience can be helpful in health care ai. As a leader at the intersection of care and Delivery Technology its disappointing to see so little progress of the past two decades. A recent study from boston suggest one of her patients admitted to the hospital continues to experience an adverse event many of which Health Care Organizations are complex systems using new ai tools will bend the Patient Safety curve in a better direction. One instructive example of her use of this technology is early in the pandemic. Serving as one of the first two sites for evacuation of wuhan expatriates we monopolize some of the first in the country in february 2020. This early experience led us to deploy an imaging which helped identify covid and chest xrays. This was months before wide strip widespread testing became available. Our evaluation showed clinical decisionmaking for one of five patients in Emergency Department over the course of the summer of 2020. After processing 60,000 returned it off at the end of 2020 because it was no longer useful to our clinicians when testing which demonstrates the importance of ongoing monitoring to ensure that ai tools continue to be safe and effective. The study was recently sided with her review of research about cove cold in ai which found their publication was one of just four of over 9000 which demonstrated impact on Clinical Health outcomes for this demonstrates another key point which is a huge gap between the christian algorithm and implementation at measuring patients. What we refer to as the ai cycle. The second example comes from her use of ai to support earlier identification and treatment of sepsis. Uc san diego has chosen to develop a local model using local data. We trained users as i dont know when confidence was low. The results have been associated with a decreased risk of death among patients with sepsis in our Emergency Department. The case study highlights importance of not only creating algorithms. Ensuring their transparent to generate trust and doing the hard work of integrating the workload where they can impact air quality. A final sample his recent use of generative ai to help the mission answer patient messages which is breached unprecedented levels in virtual care busy san diego authored a study showing generative ai is highquality quality. On these results it became one of of the person at the nation to implement generative ai to help our clinicians respond to patient messages. Importantly with full transparency with their patients by ensuring every message has a message automatically generated by the doctor for these messages cannot be without a clinician review and the results of cms has been well received by clinicians and patients and may save a cognitive burden. The study illustrates the importance of transparency in keeping humans in the loop at all times. The privacy and security perspective i want to know no information as leapt r. Hipaa protect the environment. We found cybersecurity with a focus on improving her digital protections and resiliency. This summarizes the Health System engages in the use of largescale Machine Learning models to perform a while at wide for a test. These benefits mitigate brummel five years or helped ai committee has been evaluating all Machine Learning models from an ethical and Health Equity framework to ensure safety and security and trust will find that the model proposed by the National Quarter for health i. T. To ensure safe use of ai. Awesome advocate for Testing Process our experiences local audits to be more effective for ensuring alignment with these principals in these models must be evaluated within the context of care. Finally with the generous support of the center for Health Innovations we see an opportunity to move this industry together with you and the frustration of responsible ai use metaphor to answer any questions you have. Thank you. We appreciate your Opening Statement in the chair recognizes dr. Newmantaker. Thank you could epshteyn to address congress on this critically important subject. Im a physician scientist with training Public Health and the Research Focus including the development and deployment of diagnostic technologies such as ai. Im currently a professor of virology and director of the center for diagnostic and a past president of the society for diagnostic medicine. My testimony will focus on challenges with a health care from a Public Health perspective with an emphasis on ai to medical diagnosis. Id like to say for the record the pin is express my written testimony are my own and do not necessarily the university. A is a branch of Computer Science concerned with and on computers with a billet to simulate Human Behavior. Most complex Cognitive Task and medicine would be diagnostic to cause a patients symptoms. Diagnosis accounts for an 800,000 deaths or permanent disability disability each and the west more than 80 with her clinical reasoning failures. This creates an opportunity for ai patients to save american lives. Potential benefits include better Health Outcomes and lower costs greater access to and efficiency of care delivery especially those underserved and disadvantage and decrease Health Care Costs workforce for now. Under these benefits would be realized without tackling data challenges facing ai. Implementing ai systems is no longer the technology. The sources of data which technologies are trained. They are three Critical Data problems. First using data that are wrong the garbage in out problem relying on the wrong kinds of data and third not having the right kinds of data at all especially Health Outcomes or inaccurate diagnoses unexpected adverse events for data Quality Health care is not uniform even for diagnosis. Most reliable complete dataset in radiology and Laboratory System diagnostic systems are being built. The least reliable or from routine clinical encounters. Patients at thems or terminations finding the Electronic Health record are often missing or inaccurate. There must be a radical shift in the way we capture diagnostic information. Faulty data will make the same mistakes that simply its available Electronic Health care data to train ai systems in the best we can help force a systems replicated with out vices. If systems are to play without e will drop. The biggest Public Health gains for welldesigned ai can present expect parts of the Health Care System for their large quality apps that will be closed for many individuals. Diagnostic errors lack of access to care in underserved areas and health disparities. For any and health care to that effect and help all americans the following are essential. First ai systems must be trained on Gold Standard datasets that are unbiased including complete information on clinical and carry outlets. It must integrate clinical workloads leveraging the strength of computers and humans together to reach better result being achieved. Wherever ai is used systems to monitor maintain and enhance Skills Including diagnostic once should continue to fact check each other. Ai systems must be held to a high rated her standard and demonstrate scientifically to improve hair kit care quality. New payment incense will be made to ensure ai systems are unbiased and health come outcomes or monitor. Targeted Research Funding to address these areas essential for special consideration should be given to funding programs to support the development of large Gold Standard datasets for its highquality ai systems are trained but in summary and ai has Great Potential to transform health care for the better. Absent carefully crafted legislation and target resources risk will dominate. The guiding principle for policy changes should be Public Health impacts including emphasis on the aqua distribution of and risks across the population. Thank you for this opportunity and id be pleased to answer any questions you may have. Thank you protest to me. That includes Opening Statements were witnesses. I think dr. Nguyen you guys have a lot of information we have a lot of curiosity so each of you will get five minutes. I know what would be hard to answer some of the questions briefly. If one of the say im sorry im moving to the next questioner we are being. We just want to make the best of our five minutes. And some of my colleagues on more than others will ask a detail questioned for five seconds left in their time. Ill let you answer as much as we can but im not being its getting things done so i can appreciate your time as well. I will say that and i will begin to the five minutes by recognizing myself for five minutes. You mentioned the various types of ai and how it genitive ai is the focus. Can you walk us through how you might deployed to various forms of ai supervised, unsupervised reinforced into these are the main drivers of how you deploy ai then please give us your approach. Absolutely. I think its helpful to think about ai is a highlevel into different categories. One is a will call it narrow ai narrow specialized ai tools and they typically are built to do specialized in specific things. They trained him well. Tools like this such as predictor tool to predict the risk of a cardiac event. That is a narrow type. You want to apply those types of narrow ai systems when you have highrisk, tasks that you must get right. Things such as supporting diagnoses and the patients deterioration. Those are what use the systems four. The other half is the systems are genitive ai systems. These systems are much more flexible. They are built for specific specialized tasks. We see them most often in technologies like chat box and chat cpt. They are built to be flexible and to do things like take language and output of language response. They are good at flexible task like assisting with an Administrative Burden of generating educational context. You need flexibility rather than a specialized nature. You may thank you. Mr. Shen for health care especially ensuring that patients their guardrails in place ai. We want to make sure we protect safety while promoting Better Outcomes for the taxpayer dollar. How can we strike a proper rated tory balance on the front into ensure their safeguards in place without stifling innovation and growth . Thank you for that question. Our algorithms got a rated tory process with the fda and we follow the Machine Learning enabled device regulatory requirements in premarket and review to make sure the solutions are safe for patients and effective for them as well. We also have regular dialogue with the fda regarding ai Machine Learning and provide feedback on the ways we can ensure safe and effective also we work closely with the ftm and temptation of the predetermined change control plans for ai and i think this committee for their support in this effort. Those helpless and sure we continue to innovate in this area will having the right regulatory components in place. At the same time one of the challenges right now is around the adoption of Artificial Intelligence and for providers and physicians to take advantage of the great benefits that we havent talked about here. Right now seem needs to create a consistent and predictable approach for the payment of ai solutions that are fda approved rather than the current ad hock approach we have seen to date for certain technologies based on cost. Other ones dont receive that payment. The uncertainty for providers is to make investment to Artificial Intelligence and enforcement because of that uncertainty patients get lost in terms of their ability to take advantage of the technology. Thank you and i want to move to dr. Newmantaker. Some of my concerns is the data that goes into ai and what we need to be aware for what could, but the rated tory policy challenge that we need to consider. Example would be to make sure we talked about quality adjusted life years and we want to make sure a data system factors that in to see if people are qualified for care. What are they on pristine challenges that you think we need to be aware of as an example . And their significant data challenges for ai systems particularly when we look at Clinical Data. For example laboratory and imaging datasets whether they are digitized and Clinical Data in electronic notes. They have lots of errors and problems and i do think to some extent thats a key focal point where we should be making sure that they earned over relying on faulty data sources as the try to move forward. I didnt leave you much time to answer so thank you for that and hopefully we will toward that more through this hearing. So i back i recognize the Ranking Member for five minutes for her questions. Thank you mr. Chairman of thank you do each one of you for being here today. As i was listening, i was listening hard to absorb what you were saying and i had to admit that there were different parts of your testimony where were really didnt understand what you are talking about. Now thats not to be interpreted as you being less than perfect. Thats a condition for the entirety of humanity. I think that we are very hungry to hear and pedestrian terms if youll excuse that terminology exactly how this is going to work and how you think its working now. I recall a book written by john torit and i think you all know who he is. Google him because hes one of the greats of our country but the title of the book was measure what matters and thats what im trying to extract from your testimony. I dont know if some of this is forward ministers and when you talk about Administrative Burdens, what does that mean . What is ai going to do about that and what does it mean in terms of patients at their bedside . I mean in real life not only is Important Information that medical specialists can have access to, to enlarge their understanding and as you said doctors dr. Longhurst is so wonderful you took all of your experience to the Childrens Hospital tuc. They are first cousins, stanford and university of california. So my questions are really more about the practical, the real practical advantages of ai. I would ask the entire panel if you get into this. Without any congressional statutes yet, how do you guarantee all the positives that you have presented to us today . Answer briefly. You are all saying this and i believe in the potential of this. I think we need to think long and hard about it. You are doing it right now with your systems. Let me see if i can briefly give you an impact winter. We said minister. We are anywhere between 25 and 50 of time during the day that a clinician doctor underspend some activities that dont directly relate to patient care. They are entering data into the system and searching for data in multiple different systems. They are putting the information together and riding it down and organizing it. They are communicating with other physicians with the pharmacy and the other parts of the hospital but all of that just so they can have the right information to be able to make good decisions for their patients. Thats what our language model is for. So are you using it today . Yes. Have you measured what matters and whats the outcome . What are your doctors saying . Does it reduce their burdens by 50 , 20 , 5 . What do they think . Our er doctors that are using this to help documentation they are seeing upwards of 20 to 30 of their time return to them so they can focus on patients and spend more time with the patient in communicating with the patient and not having to do the documentation. Anyone else theres an important distinction to be made between direct ai and indirect ai. We have discussed in direct and having additional time and rest time for clinicians and more time on the task at hand with the patient. The future of ai and the one to look for is one where ai is helping improve health for patients directly through for example the prevention of medical errors by improving the accuracy and diagnosis in improving the accuracy of the allocation of the correct treatment an adverse events from mistakes made in health care. Those are the kinds of things would you talk about measures that matter. Is it happening now quick. I would say its not happening at that level but its a place where we need to focus our attention. I had other specific questions that i plan to ask but i ran off script so thank you for your testimony and the expertise you are bringing to this which is needed and i hope you would all way and in some way shape or form about the create act and the like to know where you are on that. Its important for us to pass it. Thank you. The generally eight the gentlelady is back in the chair recognizes ms. Rodgers. This committee has worked on the National Data standard and i believe thats the first step congress should take is the link to the guardrails that are needed with regard Artificial Intelligence. Your testimony states important of using and developing ai in health care. Would you share any comments on this issue and importance of privacy in Artificial Intelligence . Privacy is critical to everything we do with patient data. And prior to Artificial Intelligence, is a Health Care Provider weve been under the hipaa standards for decades and thats given us a great roadmap to understand how to do a really good job of protecting our patients data. Ai strategy is the data strategy. The two are intrinsically linked so we need good quality data, diverse data sources large datasets to train and finetuned models. We had to think about both sides of this is how we keep the data private and secure which i won hundred agree we need to put also do it in a way that enables us to use the data to train these models to get smarter and to get better. Went to achieve the outcomes my colleagues mentioned. The data is fuel for that so we completely agree that data has today kept private and secure. We would be happy to work with the committee and yourself on the approach of data privacy you mentioned. I would add is a provider we have a lot of deep experience in a lot of insight as well. Theres another Software Application we had to put under the umbrella with hipaa to make sure that we continue to protect their patients data the way we have. Thank you. Mr. Shen recognizing the growing interest in medical products is critical that the fda must ensure patients and providers have timely access to safe and effective products while facilitating the patient by providing industry with predictable regulatory pathways and rules of the road. Can you discuss how the current rate a true process works for ai enabled medical technology and are there any improvements needed . As a relates to the fda to provide several pathways for ai solutions for regulatory approval. They include different rigors available there and organizations to improve the ethical safe and secure in terms of how they are treating patient data and how that application applies to other Patient Populations going forward. The way the construct the fda has they provide good ways for how software can be updated and ai algorithms can be updated going forward. Where we see some the challenges related to regulation not in terms of the approval of the solutions that is mentioned earlier the adoptions of these in leveraging things like tms to provide ways to encourage adoption of ai solutions to the providers mentioned here. Thank you. In the time remaining a lot to ask each of you to speak to this question because ai is being used in different fields to improve health care for patients and we hear examples of improved diagnostics. As we move forward and contained to incorporate and help ai and health care through it to make sure providers and patients are aware of the decisions that involve ai. Starting with doctors schlosser would you speak to a congress should be thinking about in this regard and to make sure it isnt lost his Ai Technology continues to evolve. I would comment that transparency is incredibly important to ai in general. Patients and providers deserve to understand exactly when ai is being used, what datasets were used to train it and what decisions is able to make. Thank you. Is of paramount importance for patients have the right information and transparency around the use of the tools. Providers must understand the limitations of those tools. I would add to that transparency topic not only transparency and how ai is created but also transparency in terms of understanding how ai has derived a clinical decision to educate the users of the ai to understand how the ai makes a clinical decision or recommendation. Think youre going. Unfortunately my time has expired so ill had to look for another opportunity to get input. The chair yields back in the chair recognizes the Ranking Member for five minutes for any questions. Thank you mr. Chairman. My questions im concerned the Rapid Deployment of ai tools means theres an enormous incentive to share best quantities of patient and consumer Health Information to train ai models and invades Data Security concerns particularly as it relates to Data Transfer outside of the hipaa related regulated environment. Do you share my concerns in this respect and particularly for the sale of data through a third party including mobile applications. And is there any privacy law including hipaa . They think you Ranking Member pallone for that great question. We absolutely share your concern. As dr. Schlosser described commitment to transparency is key to transparency requires privacy. Health systems and pears for two decades now understand what that means. The Third Party Apps collecting Health Information directly from consumers are not subject to hipaa and thats deeply concerning to us as an industry that they are growing databases and in many cases by patients themselves that will be unwittingly and inadvertently using it for these purposes. In your testimony mentioned several examples of the ai tools used at the university of california san diego. Do you know what data was used to train those tools and was a protected by hipaa . Thank you. Its a great question. The first examples i gave about imaging of sepsis were tools created with their own datasets on the patients we serve. They created a hipaa protected environment and protected Health Information. A third example is shared with degenerative ai using these tools to respond in a general tool that is not accessing our patients protected Health Information train trained in our patients data and it does exist in our environment. In all three cases they are subject to hipaa regulations. As you point out these thirdparty patients are building databases and creating algorithms without that level of transparency or data protection. Thank you. Let me go to doctors shen. You testified about the vast amounts of medical data need to train the ai tools. How is that regulated under hipaa . A good question. We are deeply committed to safeguarding patient data and data privacy and the pulling the protection standards set forth by hipaa. I think its central to recognize the data thats utilized in training costa rica or his process of identification but we use that to remove all personal identifiable information and any protected Health Information as well. Thats done prior to doing any sort of ai algorithm training. That ensures all that Data Security and privacy is respected for that patient. You mentioned the importance of a strong Data Security so elaborate a important particular concept of consumers Health Care Data. Absolutely. A great followup question Ranking Member pallone. Whats critical is making sure that we want to make sure that we have a healthy dataset thats utilized to train these algorithms for the same time with the rekha guys in respect data privacy and the patient between the patient provider themselves. We work with our clinical partners to utilize offer them training we respect the legal constructs with different providers that are there but on top of that what we do is we also make sure we doublecheck the data that we have received to be identified we doublecheck its truly identify. We goes through the reader to make sure that data has been removed up an api irp h. I. Thank you. Just quickly i only have 30 seconds, what do you recommend on how Ai Ai Developers can correctly identify and mitigate potential biases to prevent unintentional perpetuation of Racial Disparities in the Health Care Algorithms claps 15 seconds. Out to save and if they are reasonable questions about how best to address physiology that may correspond to macroscopic we should not be converting human racial biases to ai determined roles and thats a critical feature and will require we adopt larger datasets that are representative, representative of all the populations. Thank you and thank you mr. Chairman. The gemini of and i know we had a markup. Dr. Burgess is running for election and not our side of the aisle are entire congress is nobody that has more encyclopedic knowledge of Health Care Policy but more important his ability to absorb the facts and his passion for making sure the Health Care System works. And his compassion working for people that have the least ability to do it themselves and someone who has become a deer friend of mine and i have a tremendous amount of respect for. We have another year. We are absolutely going to have an empty seat at the table next year for someone who is so good at what he does so dr. Burgess you are recognized for five minutes. Thank you are to chairman. Thank you for their marks and it was more than i deserve. When you look at ai in the context of the existing ecosystem if i can use that word in health care its not new. Its not unique. We have all had some experience with it and like anything in health care theres rarely a day that goes by or never a day that occurs when someone comes to me and says you know i dont think we dont think we are regulated enough in health care. I want to balance those two things. We do need to be sensitive in finding a balance while we discuss improving the records are processed to make sure the innovation is not clobbered in the process. Let me ask mr. Schlosser and mr. Shen this question. He discussed the importance of clarifying the role of ai as a support tool rather than a primary decisionmaking and extrapolate on the distinction and what makes it so significant in practice. Thank you for the question. Thats an incredibly important distinction for the concept of human and a loop which i mentioned my testimony is the critical safeguard we can use to allow us to accelerate the use of ai and learn more about the capabilities of these tools in particular the new versions of ai the large language model. And do it in such a way that we have a trusted physician or clinician between the ai model and the patient is ultimately impacted. The tool becomes consistent and provides support and advice around data and brings insights but we rely on that position or clinician to be the ultimate decisionmaker for that patient that gives us a level of safety that will allow us to continue to experiment and after stand how to use ai going into the future. Thank you congressmen. To echo what dr. Schlosser said we believe its a companion for the clinician. We fully understand the value of the patient clinician or the patient doctor relationship there. What we want ai to do for that clinician is to derive more information or context for that clinician to make that more informed diagnostic decision or that more personalized decision for the patient. We are not looking for ai to replace with that clinician is trying to do from diagnosis or therapeutic standpoint but to help them form that clinician to make that more informed diagnostic decision. We dont have time to get into it in his hearing but i also hope and i may ask you to respond in riding where the technology will lead to longterm debt and deficit and the health care is one of the primary drivers there. Mr. Shen staying with the windsor experience . I know chairman guthrie asked to this a little bit. You work with center for medicaid and Medicare Services and may make reimbursement determination so how is up and working out for you . We have been working closely with cms to determine what is the appropriate reimbursement as it relates to Artificial Intelligence. Where we see the biggest concern again is around the adoption of these ai solutions and while we are hearing from providers and physicians they have a strong desire to want to adopt these ai solutions and the benefits we talked about this morning for the challenges the uncertainty on whether if they make an investment ai and uncertainty and whether they will receive reimbursement for that investment. Just the inconsistencies coming from that. This is a save space but you can talk about cms all you want. We wont tell a soul. Dr. Schlosser went into detail about the large language model and you talked about a generative model for Large Language Models and i just wonder if its possible to thats what you referenced in your written testimony. Just to clarify using these models quick this i was just intrigued by your language using the language of shakespeare. Lets focus on direct development and is there place where this can play a role in Drug Development . Absolutely. Its a complex process involving many moving parts. There are many ways. Those some of those are predictable at the level of the fda so collecting the data that you will be submitting the timeliness. It seems like ai would be a place where it could be organized. And if it fails it fails earlier during a time of trouble. Exactly. They are clearly things that ai reduces the burden on. Thank you all for being here today. Very informative panel and we are done with this discussion. The gemini of in the chair recognizes the gentlemen from california for five minutes. Thank you chair guthrie and Ranking Member eshoo are holding this important hearing and are witnesses for sharing your expertise and your opinions. Emerging a technology sosin a credible promise to plug the gaps in our Health Care System. Many of you have mentioned these novel technologies have the potential to expand health care access, address outstanding disparities and support the Health Care Workforce. I have been clear in my support for dancing technologies that increase access and quality of care for all americans but theres also the potential for harm. If we are not intentional about how to proceed forward. Ai should make the Health Care Systems more equitable and not less equitable and because ai is only as good as the data it trains on, i worry about the possibility that these technologies may perpetuate the existing health disparities. We have a responsibility to ensure Ai Innovation in health care to build carefully and reliably if we truly want to harness its full potential. Ive question for dr. Newmantaker. You mentioned in your testimony goes in rural or underserved communities or those with social determinative Health Associated with generally worse Health Outcomes may be most susceptible to suffering diverse consequences of inadequately regulated ai pig. Can you expand on the kinds of consequences you have already seeing . Yes. Obviously we have populations that are at risk. These are individuals who do not miss surely have good access to health care the first place and on the Positive Side we hope ai will offer the opportunity to deliver higherquality care, greater access to expertise in on the downside obviously they are concerned about whether ai systems will be accessible to those individuals at all. For example there may be Broadband Access poems or other issues that constrain their ability to access technology. We have further issues about Health Literacy the ability to use such tools and beyond that the issue of whether, when ai systems do potentially fail or make errors they may be less equipped to deal with those problems. Thank you. What should Congress Keep in mind as we look to ai to improve Health Equity and protect against worsening disparities . I appreciate your question. We talked on this panel about the importance of transparency and some of her colleagues talk about submitting the results of internal testing but its important for this subcommittee to recognize those are selfreported tests. The coalition for health ai has proposed a series of National Labs as testing for vendors supplied ai all and the company they should be room viewed in detail. Having external testing is the way we are going to mitigate these Health Equity issues that come up with algorithms developed by datasets. And cupid were the things things im concerned about a we have seen the past are the incredible innovations that make it easier for people to make a conclusion. For example back in the day when the term credit score didnt even exist, i was told at the time i said wait a minute you were going to use it is not the backdrop that use this as the primary driver of whos going to get access to capitol across america and now cross the world. They said no, no, no its just a side tool. Its now the main tool. The old days of having a big file and having the whole review before they make a decision is gone. My point is this, the our proprietary algorithms for the governor deny these w have a clue what those algorithms are. Nobody does but the actual proprietor. I respect that protection because they have done a lot and invested much into that. It is in fact her pride. But the problem is nobody knows whats happening. Thats one of my concerns of the ai especially when it comes to not only quality of life but who lives or dies based on an algorithm decision as to whats going to be the outcome or the cure or if someone is even going to get access to health care because they say no, yours is not an emergency situation so therefore you wont get cared for. 100 agree with you and we see the end creasing rated deniable payor claims and thats driven in part by ai processing these claims and very rapidly denied them in an inequitable way so i share your concerns. We are to have examples in the hope that congress does the job and tries to move as fast as ai has two make a Better Future for us. Zarah it went over my times determined. The gem was back in the chair recognizes the gentleman from ohio for five minutes. Ai is something i applaud and powerful committee for all of our subcommittees. We have been having hearings on ai and how important this issue is as we go forward. Especially when worth talking about the health care sector. This is especially technology that we have that guardrails and place making sure we protect the privacy of americans and prevent other countries especially countries like china from using it. Also the subcommittee its been brought up in your discussion today. We are trying to help the providers out there to do what they are supposed to do but we have a shortage of Health Care Providers. One panel especially about as many as the table today and i said how much are you spending senior patients quick i dont think one of them said more than 50 . When you have a shortage of doctors and its important that they are doing that job is essential to get it done. Dr. Newmantaker in 2020 when were the 100 biologic applications including ai Machine Learning components. Would explain to the subcommittee if we continue with ai how this could lead to a Breakthrough Development . Thank you congressmen for the question. What i would say is as we look to the space of Drug Development the same way as in general of health care their opportunities for ai to help both in the process itself, that is the mechanics of working your way through the rated tory processes flows through the identification process of the actual treatment. For example we have large datasets to identify drug therapies available to us and i think that will give us an opportunity to break through ground using the existing data. Thank you bear much. Dr. Schlosser when i was reading your testimony that it was interesting the Technology Uses the ambient speech models to transcribe the doctorpatient interaction in emergency room. We all have the opportunity to visit our hospitals and especially being on the subcommittee, i go through a lot of different emergency rooms. Im curious how does the technology eliminate that stress to make sure we are getting 100 which it youve got to have, to be transcribed for that patient. Thank you for the question. Ill go back to a common the human in the loop. We always have a physician in their opportunities to review the notes is less the last step before it becomes part of the Electronic Health record so they can ensure its 100 accurate. A eyes done at a point yet where we even do that complete on its own. We are using the data through datasharing agreement to continue to improve the quality of ai and it continues to get better and better. It takes more and more time to do less editing if the entity that. Right now we are using physicians. As you identified the emergency room is a chaotic and challenging environment and thats why with the technology than the first place. We feel like it has the most to offer in that space where precious time given back to the positions so they can tune in to whats going on with that patient will enable quality results. You said something your testimony said we had to have a review of ai and it built into the ethical review of ai. The health ai committee which has been around for years we going to Health Equity researchers and bioethicists. The reason for that is to look at things like what are the ethics of being transparent in this case. Is that an ethically or appropriate thing to do or are there ethically challenged questions. That helps to raise only implemented generative ai to help clinicians respond to patient messages per that question was raised by her ethicist, should we be transparent with their patients and not generate the conversation that results in full transparency to our patients about the fact that we are using generative ai to help the responses even though theres a human and in the loop of those messages are edited by clinicians at the end of the day. My time has expired and i you back. The jahleels back and i recognized dr. Ruiz for five minutes. We have widespread shortage of burnout and barriers to care for patients and as members of cannes who must Work Together to create a Health Care System that is sustainable there and vice versa patient first. Its important to not only supported vans. Improved patient quality of care and strengthen the workforce but also ensured we are addressing barriers to care that affect underserved communities. They are the ones that need to care the most due to disparities of health and the burden of those disparities on those communities. As a witness here today underscored innovation in ai has the potential to address these concerns and improve patient care however these technologies pose a potential risk that we must carefully consider and mitigate as the technology continues to develop. As an emergency medicine physician im all too familiar with the Administrative Burden that physicians face and the negative impact it can have on patient care. Doctors schlosser how is ai currently helping physicians cut down on Administrative Burdens so they can focus their efforts on patient care and how does it affect the quality of patient care . Thank you for the question mr. Ruiz and i agree completely with your comments about the Administrative Burden that are clinicians are seeing. As i just mentioned and mentioned that my testimony we focus on two areas. One is documentation. Documentation takes up an inordinate amount of our questions time and if we can return that time to them they can focus on their Patient Population. We believe we can create an expanded Health Care Workforce using the clinicians we are to help simply automating and removing the past. We are looking at ai. Our nurses are under the same kind of pressure or clinicians are from burnout. Giving them the tools that helps them do their job like handoff tool we talk about the testament of the automated piece of their workflow to make it easier for them to spend time at the bedside with patients. We believe those will lead to improved experiences for caring for patients. Doctors have dr. Nguyen he talked about generative ai in your Virtual Clinics. Is there a place to protect Patient Safety when using generative ai . Absolutely yes. To clarify generative ai is transparent. Safety mechanisms are considered when you are building an ai. Applications of all safety on every layer. You are building these systems and you the need to think about the data layer first to make sure you dont have a in, out problem. We also need redundant i mentioned the use of narrow versus you want to build mechanisms that can detect patients asking questions and getting the other medical emergencies. You want those in place ensuring that you have a high degree of likelihood that youll catch issues like that. You want those layers to ensure the highest level of patient success. Doctors schlosser what would be the ramifications of biases and health care if it addresses the Ai Development and what strategy should we be should be implemented to protect and mitigate biases in ai models used for health care . The mac is a great question, thank you congressmen. But i would say obviously we dont want to compromise the racial biases we see and other biographic Human Behavior in the form of mathematical algorithms. To prevent that we need to do work both on the side of developing the tools using appropriate datasets and we often need to deal with at the backend monitoring for these kinds of problems both using sophisticated tools to identify bias and thats been done in a number of recent studies and furthermore to monitor outcomes of Health Care Associated with ai so that we can monitor measures that matter for patients who are underserved. Thank you. I appreciate that. Thank you all for your insight into the benefits and potential risks of using Ai Health Care. This insight is especially important ensuring this Innovative Technology is used to improve patient care, improve access to care, reduce health care disparities, reduce the barriers that improve equity by giving resources in health care attention to locations that need them the most while mitigating biases and potential risk to patients and i yield back my time. The gentleman yields back and i recognized mr. Griffith for five minutes. Thank you very much mr. Chairman. Im going to pick on you first because i loved this book the perfect written by one of her colleagues so my question is and for those of you who dont know the saving of her husbands life Thomas Patterson who also is a uc san diego individual by finding the right virus to attack the antibiotic resistant bacteria that attacked his body. Its a great story. The question is are you all using ai to find more of those therapy type viruses and if not do you see any potential in that. A great question thank you for referring to the book. Its an amazing story of a life saved by therapy. Something that was explored prior to the advent of antibiotics. We have gone back with antibiotic resistance looking for solutions outside of that domain. It started a whole Movement Across the world and we are the center at uc san diego on therapy for treatment of infections. Im not aware we are currently using ai to help at that center but as previously mentioned in general throughout it will be augmented by the use of ai. Im very optimistic that we will see a large language modeled of generative hypotheses of new ways of treating patients that they may not have previously examined hypothetically so thank you. That was a bit off script and ill go back to script but im going to flip the going to the other side but according to reporting the use of Artificial Intelligence has potential large language modeled like chat gpt and other chat box of old deadly pathogens. They can be used to revive deadly pathogens and create deadly ones. One example students were able to get the large language modeled to suggest pandemic pathogens within one hour per asking a series of questions to a generative large language model. Further research in cambridge massachusetts used open source large language model asking how to revive the 1918 spanish flu. Several participants found the 1815th would be feasible and one got very close quote unquote close to learning all thats needed to obtain the virus but is encouraged to see the white house put out an executive order to attempt to provide more oversight and security on this type of ai. But the still causes great concern. Do you know if any Ai Technologies have security limits on what can be asked and what cannot be asked . Congressmen that thats a very good question. These Ai Technologies have extremely broad implied capabilities. We dont fully understand it yet. While this is outside of the realm of what ai uses ai in general especially in generative ai in that field there is research. The research refers to the science of studying the malicious capabilities of these models and studying the ways in which we can prevent it. In that world its very important work thats being done to find what you are describing which is vectors of malicious use. There is still a lot of work to be done. I think it is very important for us in the Health Care World to acknowledge it at this point. So looking on the Positive Side one article indicated a proponent said maybe we need some kind of a Test Ban Treaty like we have with Nuclear Weapons and you think we should be looking to some kind of a limitation on the test . We want the positives but the negatives could have grave consequences. I think its difficult to truly limit the progress and teg them safe and using them right. I think it requires a measured approach. The other risk of test banning its countries of the United States will also use the process. Also which pierced back to you dr. Longhurst you you mention your testimony today i system is helping with virtual care visits in tube allow doctors to provide more kate care for patients but do the patients trust the system and find benefits from automated responses. I will say briefly anecdotally we have gotten is a feedback from patients and we are submitting more quantitative data for publication. Thank you very much and i yield back. The generally of in iraq and at the gentlelady from michigan miss dingell for five minutes. We are living in an increasingly technological world and technologics like ai addresses Public Health and improve Patient Outcomes. As we keep talking about not that many concerns like others have expressed on the other hand ai does pose serious risk that left unchecked can harm patients and quite frankly or National Security. If this subcommittee has discussed the cove in 19 pandemic and talked about the fragility of her Health Care Supply chain. Its really a National Security issue. How can we keep our nation safe if we cant access the medicines the devices in the protective equipment we need to protect the community from public threats . I think ai has a role to play in all this. How does it affect healthcare . Thank you for the question congresswoman. For Artificial Intelligence here, Artificial Intelligence is the ability to be able to drive efficiencies as it relates to the supply chain. Being able to leverage Computing Power to simplify the processes that are dependent on other components. Names and outside of the u. S. Being able to collect Artificial Intelligence to be able to accelerate the ability to drive delivery and efficiency of supplies that are needed. We see this directly in the solutions you make here. We tried to leverage Computing Power with all the success of that during the pandemic itself by being able to deliver diagnostic equipment and therapeutic equipment during that time. Thank you for that. Our persisting challenge for Patients Health and wellbeing. This summer we saw very real shortages i dont know i say this summer. We continue to shortages of critical cancer drugs during grassroots flu parents across the countrys have difficulty finding common overthecounter just tylenol and advil for their kids as well as antibiotics and amoxicillin which is used to treat common infections. How our suppliers are using ai adjust these shortages . Correct thank you for the question again. At the exciting part about articles intelligence and the ability here to drive efficiencies within the processes that are established. Artificial intelligence provided use that to improve the processes internally within our organizations. For diagnostic therapeutic imaging for providers, and a timely fashion. Make sure patients receive the latest Technology Available medical Technology Available with a diagnosis. Thank you we got to keep working on this. During the pandemic we saw tremendous to ensure limited resources were strategically going to communities and pages aided them the most. How can ai help approved terminal resources . Think for the question congressman. We heard a little bit about the architecture of ai when the issues in this space having the right Data Architecture. To get to the point where ai in those ways. We do not have the right kinds of how it exists for the mismatch is between supply and demand. But to create data sets that digestible by ai for realtime use. If im out of time so i have more questions for the record. I think that witnesses are being here. Quickly gentle it yields back five minutes. Ive seen you tells about the role of generative ai what it is what its potential can be within the healthcare sector i noticed a general question and i know others asked this question but it is so very important please. Pick. High pressure. Congressman. My colleagues have also talked about generative ai. Perhaps i will talk about as it relates to medical imaging and impact of patients. Sounds good too. With a generative ai will receive the greatest potential is the ability for ai to consume more information about the patient themselves. When a patient goes to get an exam done they get a diagnosis for example. Leveraging generative ai is in the ability but precise diagnosis should we be looking for. Not as for the sake of doing a test on that patient seeking a particular diagnosis there. If you think about it helps the patient avoid going through multiple exams trying to look for the issue is here. That is potentially one area of the other air generative ai has benefit from medical imaging standpoint action the interpretation of the images themselves. The ability to take this a complicated medical language and convey the diagnosis through laymans terms for the patient themselves so they get a better understanding of what is going on and the test results that have not exam. That is great stuff we appreciate it, very exciting. I appreciate your testimony of using predetermined change control plan. I was proud to lead the effort in the house last congress to authorize the use here my filth that enacted into law last year. Can you describe pathways nine to us how this can allow for a more efficient Regulatory Framework and why it is so important to ensure the fda implement this with bill effectively . Thank you congressman and again thank you very much for the effort. Enactment of the predetermined change control plan allows organizations with our initial fda product application a description of how the software will be updated rapidly based on new data as it comes about. Felt the need to resubmit back to the fda any sort of application or supplement every time an update happens. This helps accelerate in conjunction with the Rapid Development of Technology Like Artificial Intelligence. Itself include a description of the modifications in the methodology we are using. We provide the transparency that is needed that we talked about here today as it relates to the technology. We are very pleased with your help we are able to move forward and make sure it is part of the fda process going forward. Thank you, excellent. One question, can you elaborate on the potential Large Language Models have a reducing burden with in hospital settings please . Absolutely. Thank you for the question congressman. As i mentioned in my testimony there are numerous opportunities where our current Healthcare System is created what we referred to as Administrative Burden adding tracks to physicians, nurses, pharmacists, other Healthcare Providers that cannot directly add value to the patients related acting with data entry analyst information between different providers or different symptoms. Large language models are really good list types of cash we train them to understand the data which is part of the challenge, they can search for information. Read complex medical charts to find from multiple sources synthesize and understand and serve it up to Healthcare Providers in their workflow. Because the language models you can interact with them in a natural language away. You can ask questions and get feedback. Its a really powerful tool to make universal healthcare around a patient simple and easy to access. Very good, good stuff. Youll back the rest of my time to determine if it was stolen yields back. Now recognize the gentle way from illinois for five minutes. Thank you chair and Ranking Member for holding todays critically important hearing integration aim Healthcare System office of of transformative solution to address longterm disparities in access issues. Many of the healthcare and Technology Fields have promoted ai as a means to create a more accessible and equitable healthcare landscape. Particularly in the minority minorityunderserved and rural communities. Doctor newman i am hopeful about the potential synergy is ai ability to improve Clinical Trial diversity. By scanning from multiple databases for clinical site placed in Patient Population with the hope diverse Patient Population commitment to Clinical Trials left resulting in a more efficient diverse recruitment process. What infant regulations need to be considered regarding pay ideas to improve Clinical Trial diversity . Click excellent question congresswoman. Clearly diversity in Clinical Trial is an essential component of the many health disparities. We have seen a large number of treatments we have studied of the course of time and women centered and white men for a very restricted populations with minorities. I do think the potential of ai to identify locations in places where patients can be recruited is a strong one. In terms of the Regulatory Framework from an existing architecture at rome clinical ie requirements for diversity are important. I think were going have to make sure we further bolster that as we get deeper into the ai space in order to make sure we are having over represented groups of minorities we can do proper subgroup analysis. Thank you. Additionally in bipartisan manner for prior authorization. The free medicare population mom supported on the use of ai or the timeliness of organization and concern about multiple recent articles with use of ai with prior authorization with claim denials. So again the reliance on crucial medical decisions. Rigorous testing and validation are imperative to ensure the safety and efficacy of these technologies preventing errors or misinterpretations that has severe consequences patient wellbeing. In your review of the ai systems vetted and prior authorizations can you explain why we are currently seeing such disappointing outcomes and what can we do to help mitigate these troublesome findings . Thank you for the excellent question congresswoman. I think part of the problem is a preexisting arms race in the space around claims insurers generally trying to find ways to reduce their expenditures and deny more claims than providers trying to increase their claims and the remnant thats a generate associated with this. With that escalate into the ai space. Think more broadly about the regulation here even talk a little bit about ai used in the context of healthcare with patients. I think what you are alluding to us all the ai that may exist in the periphery around the problem is a totally unregulated space that is a potentially dangerous area. We have no idea what systems are being used for controlling the process of healthcare or access to healthcare or even direct to patients in the form of symptom injectors and otherwise great outside the regular toy framework i do think when you start bringing some of us into e regular toy framework. Thank you. I have to give you a chance to comment. Your questions are incredibly pertinent. Not only do we need to think think aboutdiversity of clinical participants and ensuring equity and how this is impacting the system. We think about our workforce. Previous comment suggested we need to train in these new technologies. Ohmic technologies only available to those who can afford them. One to have my strong support for the bipartisan proposed legislation create ai create resources for every established Artificial Intelligence resource both and in university of california strongly endorses ai proposal. Its not just for academics it is for Small Businesses and other organizations. So thank you for the proposed legislation. Thank you yelled back. Thank you, mr. Chairman. Thanks your panels for being here. Artificial intelligence or ai is crating quite a bose run capitol even across the country. It has been met with his excitement and concern with the American People realize it or not ai is sorta prevalent in many sectors particular in the healthcare space. Ive always been an advocate i work with ai little it was a buzzword back in the early 80s when i was in graduate School Georgia tech. Im very familiar with the technology would simply put ai is a tool the medical professionals and scientists and be selling for that the development of care and therapeutics resulting in better outcome for patients. But hopefully at lower costs of families and the taxpayer. Unlike the vast majority of congress, as i mentioned i have a tech background. When in my time in the military as well as my time spent in the private sector i worked in information technology. It has been around for decades. Take Electronic Health records for example. And rightfully so we are settling Healthcare Systems and immense amount of data from patient notes to imaging, doctors, nurses are expected to utilize all this information to best treat their patients. That is a lot easier said than done. So a lot of information for this the perfect example of how ai can be utilized in a reading and deciphering all this data. They can make Health Records more digestible and ultimately increase outcomes for everyone. Not to mention lessening the Administrative Burden for positions nurses and Healthcare Systems nationwide. Generative ai has gotten a lot of attention check gpt and claude and other public facing technology sediment widely used over the past year. However generative ai has been using healthcare for years through Patient Engagement technology and clinical decisions support models. So my first question doctor, to have that right missing that right . Some the other promising ways to use the generative ai integrating into the Healthcare System . Thank you for the question mr. Thompson. Theres numerous opportunities. I think the one you highlighted around making the vast universe of data the clinicians and physicians more easy to access was one we are incredibly excited about. There is one will work out one of our partners with an ai assistant in your pocket. He could interact with the Electronic Health record as well as the Information Health Exchange View and natural language interface allowing you to search for and look for information that otherwise would take a long time and is very burdensome. Using a ccd but the output of hie giant lift of data though the information is provided is incredibly difficult to use. These models are capable of doing more than read information. As an entire hospital better bounce friday night . We can deploy our labor workforce and much more efficient and effective way by harvesting the intelligence contained within these large deep learning models to consult complex problems that were previously nursing leaders or others that struggle to have the information delivered outcomes we are looking for. Lets make a choice second question. What about rural and underserved populations like eastern ohio and appalachia where i live . What can congress do to facilitate more adoption of these technologies are smaller and rural practices to make our Healthcare System or personalize and ensure every patient provider has access to a high Quality Healthcare technology . What is another great question. We linger in the pandemic is basely one one relationship a intent between having of Healthcare Providers and the patient you need to take care of. Ultimately providers take care. Knowing cai helping solve this problem is by it literally clean them up from paths that are not focused on caring for this population so we can increase the size of her Healthcare Workforce without actually needing more bodies but just through ai. One final question before my time expires here. And you can answer this for the record if you would get back to me because my time has expired. How can we facilitate, how can congress facilitate more private investment into these technologies to make them more useful to the Healthcare System . Thank you. If you get back to me id i appreciated i yield back frequently government yields math i reckon is a gentleman from washington for five minutes. Click thank you, mr. Chairman. Thank you to all of our Witnesses Today its been an interesting conversation. Artificial intelligence and Machine Learning are already transforming how we study and practice medicine. We continue to grow these capabilities and to make further breakthroughs its really important that Congress Keeps up and i thank you for this education. Last spring, i loved visiting the Ultrasound Research and Development Center headquarters located in my hometown in washington. And during my visit i learned about and got to see a pretty incredible innovations being done. One of them was the ability to diagnose nonalcoholic Liver Disease and an ultrasound scan that took less than a minute. The implications for morbidity, mortality are incredible. Every time we have a new advance there is a question of cost. We integrate Artificial Intelligence and the more advanced algorithms and new technology, there are impacts on costs. There is development impact. Theres also potential cost savings on the line if they are boarding liver transplant. I have two questions if you could partition your time. I met a little bit on Ai Development and cost . Thank you for the question congresswoman. Of course were very happy to host you in our facility. As it relates Artificial Intelligence as you correctly noted we are trying to integrate ai tools directly into the types of exams or devices that are touching patients here. You are in this case for ultrasound integrate the ai and not have it be a separate type of solution there. Doing that in itself reduces on the costs rather than trying to have a separate solution that has to be procured or whatnot it integrates the solution directly into the medical devices treating the patient. That is one aspect of it. We look at ai we do want to look at not just the cost for procuring but what is the cost . Not just the patient in terms of fewer days that the spent at the hospital or maybe shorter time to diagnose the treatment also cost savings that could be realized by the providers themselves as well so by deploying this type of technology is able to be more efficient and able to make that diagnosis faster. Able to see more patients they have more time to be able to take care of one patient move quickly to the next patient these are all things as we develop ai. I think you and i appreciate that. My next question that convicts. This is really about the impact of ai on the physicianPatient Experience proximately Patient Experience i like to talk about a little bit about the doctor experience and i can understand how nice it would be to have the latest research pop up and suggested pathway for giving patients who i am seen this to be arty filled out their whole history for me. Doctors are already burnt out. We are and have been compared in an oped to cogs in the wheel, two line workers after almost a decade. We are being asked to see more patients faster, do my things and a visit people are burning out. Im to talk to the physicianpatient relationship how physicians feel when perhaps they are just becoming a check on a system where ai makes patient management decisions for them after that kind of training. He speak about that . Thank you and is a real privilege to speak with the fellow pediatric graduate from stanford. When i was at the Childrens Hospital were in the process of Electronic Health record. I have been a primary symptom for burnout. The hours that pediatrician document Health Records is contributing to a national epidemic. We have every day spent in clinic the average physician spends about two hours documenting Electronic Health records to ensure regular tory compliance and other things. For the electric Health Record with the Digital Infrastructure for collecting data, quality and population purposes introduces unintended consequences and incredibly optimistic about ai particularly the ai describes Doctor Foster described as being a solution to help decrease the burden introduced by Electronic Health records. We are seeing positive results forging the technologies are still quite expensive. But they come monetize continued dumpsite outcomes and privacy i think this is going to help us remediate some of the burnout that has happened over the last decade big bucks thank you i appreciate that a guild looked into late yields back i recognize myself in five minutes. Im only just beginning to learn about how ai can contribute to healthcare i recognize it has Great Potential. I was a surgeon before is in congress. Helps reduce costs i believe that example top parties and legislation on a realtime decisions but Medicare Advantage plans and ultimately all plans. I recognize ai would make realtime decisionmaking far more feasible and expect it will be used for this purpose. At the same time having allegations health plans are making coverage determinations using ai high power tools that are openly showed up high rates of errors as was mentioned by the Ranking Member in her Opening Statement. Resulting in patients been more in healthcare going necessary medical interventions. Basically these are improperly denied claims. Recent media articles about one situation which is unacceptable. I would argue this should be investigated by congress. I say all of this term and my colleagues that approach needs to be balanced and to remind the Companies Using ai to do so responsibly. The statement as long as the ai can properly populate the record to obtain appropriate reimbursement for the providers involved in the case, you will see wide acceptance of it, even if the record is there. But it is not properly reimburse the provider for their care than it would be a struggle. I assume it would probably do that. That is a major issue for providers for the documentation required by the federal government for reimbursement. Honestly in my view has been a problem for a long time. Another issue in Healthcare System we will need to think about trying to educate medical professionals use it appropriately. Your testimony mentioned using ai to train and educate medical professionals. There may be a risk that our future providers will become overly dependent on technology resulting will train providers in decisionmaking. Its not direct i have Adult Children in their 20s they cannot navigate anywhere. They literally dont know what direction theyre going. Im too go around the block we map it prevented overreliance on technology. Is not a direct correlation but kind of. How do we begin to drain these professionals on the use of ai and increase awareness of the pros and cons . On something medical schools are begin to think about and if not, should we be . Thats a very good question example. I too have a lot of trouble navigating. I think our institutions focus on the art and science of medicine and think its very, very important leverage new Ai Technologies to create learning experiences first to enhance learning experiences and make them more efficient. The most important concepts we need to know in an efficient amount of time but second its important these institution train and educate their students on these technologies. It will be unavoidable that doctors in the future tense of the most important way to prevent drone or alliance is educate them on limitations of the technology. I would agree with that. Dont get me wrong on big Supportive Technology in the innovative space. Maybe realtime or we sink medical professionals realtime over relying on ai as it relates to ct scans, mris, xrays . Are the people coming up being properly trained i would say on the positives and negatives of the situation . Me and thats going to be really important, right . Thats a great question. To echo what was talked about whats critical here is transparency run Artificial Intelligence. Its not how you actually use the ai but again how the ai is making the clinical determination and educating upcoming physicians on how ai is making the clinical determination. Think it both for the answer to that question. It is really important. I now i recognize New Hampshire five minutes. Thank you so much mr. Chairman thank you to all of you for sticking with us. We appreciate it. Todays hearing is an opportunity to understand how Artificial Intelligence can help patients, providers, and researchers to fully realize the potential we need to ensure ai tools are safe and equitable. You describe one potential benefit to a. I. Is that it can improve Patient Outcomes through more accurate diagnoses. Could you give us some examples how a. I. Tools could benefit Public Health . Yes. So as thank you very much, congresswoman, for the excellent question. As i noted in my testimony, weve recently estimated that about 800,000 americans die or are permanently disabled each year from diagnostic error with serious medical illnesses like stroke, pneumonia, sepsis, etc. Theres an enormous potential Public Health impact of being able to close that gap, that quality gap with a. I. Based detection using Laboratory Data and vital a signs for things like sepsis, using videobased interpretation of eye movements for stroke diagnosis, some of the work that weve been doing. So i think theres tremendous potential in that space, and at the same time to deal with some of the concerns raised earlier about costs, because when you realign when you actually improve diagnosis, you cut down on both false positives and false negatives at the same time. And by doing that, you save lives by catching the cases you had missed, and you cut costs by not overinvestigating the patients that didnt need that investigation. So i think its a tremendous Public Health opportunity. Good, thank you. Two concerns. Im worried about bias in the data. Con continuing with dr. Newmantoker, you staid for tools to be maximum beneficial, or they must utilize Gold Standard data steps. What data sets. What steps can companies and insurers use to insure the training is accurate and without bias . Thank you for the wonderful question. I do believe that this is a foundational challenge that faces this whole area of a. I. In health care. The issue of creating Gold Standard data sets is not, theres no simple solution to that problem. We actually have to do things in health care that we dont normally do such as, for example, determine what actually happens to our patients downstream after an encounter. So we say, for example, that a patient leaves our care and they have x diagnosis, but we dont actually know if thats true. We often dont get that follow up. They may end up in a different Health System. So we have to start coordinating Data Architectures, and we have to start developing and curating good data sets that can be used at a large scale to train these a. I. Models. So i do think thats going to take a big effort and one that would be best coordinated federally. Thats helpful, thank you. And final concern is about protecting patient data when we are developing a. I. Tools. Dr. Shen, i appreciate the help and commitment to protecting patient data. Unfortunately, weve seen an increase in Health Care Cyber or attacks which has more than doubled from 2016 to 2021. What steps does your team take to insure patient data being with used to train a. I. Tools is protected from cyber criminals and just plain bad actors . Yeah, very timely question and really appreciate that, congresswoman. We take data pryce and patient data privacy as a core component to how we approach the development of artificial as well as. And to that respect Artificial Intelligence. And as a it relates to securing the data, one of the important aspects we do is any of the data that we utilize to train our a. I. Algorithms is fully protected in our big data office thats there in princeton, new jersey. So there are physical limitations that are set already in place, physical barriers that dont allow individuals or bad actors to gain access to that data center there. And from a cyber standpoint, what our big data office does is they actually control who has access to the data itself. And in terms of controlling internally the audit thats needed in terms of who are the users that can the access that Clinical Data to do the training. So they have the ability to audit the userrer access and restrict the user access to only the individuals that need to be accessing that data. Great. Thank you. Im all set. I yield back. The gentlelady yields back, and the chair recognizes dr. Dunn for five minutes for questions. Thank you very much, mr. Chairman. I appreciate all the insights from our witnesses regarding the role of a. I. In the clinical setting. I believe theres an important debate to be had about the value adverse us the risks or a. I. In the Doctors Office and the hospital, and i agree with our witnesses about the promises of this technology in medicine. I also echo g. Nguyens dr. Nguyens caution when a. A i. Is used for clinical Decision Making without close physician oversight. Its clear from the advances in a. I. , from narrow a. I. To generative and Large Language Models, that theres sweeping implications for the delivery of health care and presents clear opportunities and challenges. Im encouraged by of a. I. In interpreting radiology and pathology, and although think the Current Evidence demonstrates that this is not quite ready for prime time, im certain that that will become more sophisticated over time. I am especially optimistic about the ability of a. I. Platforms to reduce add a morive burdens Administrative Burdens, simplify clerical tasks. I appreciate the questions dr. Slyerer slier asked on that, and thats a real problem as we address burnout. Physicians are spending a quarter of their time or more on administrative tasks, so thats a huge i would have loved to have had that when i was practicing, quite honestly. [laughter] i do have some concern that private practices may struggle with the upfront costs of adopting a. I. Technology, and i urge the industry to think creatively about ways to provide access to that technology to the full spectrum of provide settings. Provider settings. And to echo mr. Johnsons concerns with our rural communities, rural providers who will be further disadvantaged if they dont have access to that. If those technologies are only accessible to those with the resources, we may have an even worse shortage in rural medicine. So can you briefly comment on on any specific challenges that rural or private practices may face when trying to adopt Something Like transcarent . So, yes, doctor. To address your question, there are always going to be challenges at the rural and private practices which are simply smaller in size, smaller in staff, staller many smaller in budget, right . The challenges come in forms for any technology adoption, a. I. Included, and that is the capacity to assess the right tools and the budget to adopt them. I think its very, very important to continue to support the development of a. I. Tools amongst the private industry in a safe and nonbiased way because that is actually, in my opinion, the fastest way that, ultimately, a lot of these practices will experience and be able to use these generative a. I. Tools, is when the vendors and the tools that they use begin to incorporate those, right . When we began adopting most of these private practices had access to dhr ares once vendors began to build it for those practices specific create. Id like to have offline out of this hearing have somebody from your company whats your pricing mechanism, you know, for different practices and how they can adopt that in their office. Thatd be something we could do separately. Doctor, what are some of the ways youve seep a. I. Improve efficiencies for patients and improve their experience . Well, one thing that automatically in additions and probably everyone in the room will acknowledge is we ask patients the same questions over and over again. Were constantly blending them with their entire Health History and each interaction along the Health Care Journey and if you change systems or go to a different position, you start that entire process over, so i think the ability of a. I. To help us wrangle this entire universe that exist across multiple, disparate ahrs into a longitudinal record of the patient that clinicians and patients can easily access i spent more time as a patient than a doctor the last few years, i have to say, ive filled out my history probably a thousand times. [laughter] yep. Its just an amazing experience. Dr. Longhurst, you made reference to a study, i believe you were the coauthor, i believe, in which thal brit algorithm was rapidly algorithm was rapidly deployed. Every clinician i know has been reading what specific advantages did you confer to these physicians . Great question, thank you. I can tell you the day we rolled this algorithms out that i walked through the emergency and asked if our attending physicians had used it, and one of them said, yeah, last night we got a chest xray on this woman who was in for cardiac symptoms. We didnt see signs of pneumonia, but the a. I. Showed some color, and because of that, we ordered a test. I said, what did the test show . The answer was, well, it takes 24 hours to come back. That test was positive. That patient was diagnosed with covid early, proactively hospitalized, did the not need critical care, went home safely. And that is a great example of a. I. Finding a signal that we would not have found otherwise as a human, and thats the kind of promise i think the technology holds. Thank you, dr. Longhurst. Thank you, mr. Chairman, for your forbearance. I yield back. The chair now recognizes the gentlelady from for five minutes for questions. Thank you, mr. Chair, for holding this hearing and to all the witnesses here today. A. I. In health care has the potential to transform various aspects of the industry by offering new solutions, improving efficiency and enhancing Patient Outcomes. However, congress does have the responsibility to make sure that we establish appropriate guard with rails around a. I. In health care in a way that works best for consumers and maintains patient and provider trust. According to a new survey of more than 28,000 consumers across the globe, consumers are more hesitant about using a. I. To get advice about medical problems than they are for other uses like billing and customer service. The use of a. I. In medicine becomes more common place, patients have raised logical comments around a privacy, transparency, ethical considerations, human oversight, errors and misdiagnoses and access issues. With this in mind, i welcome the opportunity to discuss some of those issues today. Many of my colleagues have already brought up valid ethical considerations around a. I. Including algorithms, potential discriminationif a. I. s impact on vulnerable populations. As a. I. Advances into health care and gips to play a role in making medical decisions, im curious if there are differences among various patient demographics in their willingness to consent to a. I. , decisions making and whether those preferences may unintentionally skew algorithms. So im wondering how important is it to understand if there are pattern earns of patients who would or would not consent to use of a. I. In health care based on race, education level, geographic area, etc. Thank you, congresswoman, thats a fabulous question. I think i dont have any specific data about the demographic variability in trust with respect to a. E. Specifically, but a. I. Specifically, but we have seen over and other again that trust issues are inequitably distributed. For example, in baltimore theres a strong strain of lack of trust of the Health Care System in the black community. This is a major problem for getting equitably distributed data from if patients. So i do believe that its critical concern that trust gaps are a major issue, and they may not be evenly distributed. Thank you. The rapid im going to switch gears, but well definitely probe that further as we e progress. The rapid evolution of a. I. In health care has exposed the need for federal coverage and payment policies that promote innovation and protect patients interests. While the fda has moved forward to regulate software as a medical device, cms has yet to establish consistent methods for the coverage and payment of these technologies. Mr. Shen, what are all federal agencies like the fda and cms well positioned to cope up with the rapid increase in Innovative Technologies such as softwaral a grit. S and a. I. . And if not, what additional capability or or resources do those agencies need . Yeah, thank you for the question, congresswoman. I think as a you correctly pointed out, you know, we work very closely with the f if da and cms to try to bring forth these new and emerging technologies and make sure they get into the hands of providers or and the patients themselves. Where were seeing the challenge here is, unfortunately, specifically around cms and the reimbursement associated with Artificial Intelligence. Today, unfortunately, theres inconsistency in terms of how this technologys being reimbursed, and that inconsistency e and uncertainty translates to providers being unsure whether they should make the investment in Artificial Intelligence. Not e knowing whether they will get reimbursed or not for this. So we see this as actually inhibiting and creating a bit of an adoption problem and preventing the patients from ultimately benefiting from this technology. So we would love to see opportunities where working with this committee here trying to figure out a better way to work with cms to maybe establish some sort of a payment that allows, allows the different providers to move if forward with investing in Artificial Intelligence and helping everybody understand what the true value of this technology is. Thank you. I couldnt agree more. And while there is the warranted skepticism around the use of a. I. In health care, you know, were all excited for increased applications of a. I. And how they will positively impact Patient Outcomes. Dr. Longhurst, how are we already seeing a. I. Used to enhance progress to treat diseases with no known cure like alzheimers and ms . Oh [laughter] [inaudible] can anyone else dr. Longhurst had to step away. As the neurologist on the panel, ill take ill fill in on that wunsch i think that one. I think theres tremendous potential for a. I. To do Early Detection of disease, chronic disease in particular such as a alzheimers disease. You can imagine if we can make diagnoses ten years in advance through information coming out of wearables or eye movement analysis, we will be able to apply early preventative therapy. So i think theres a lot of potential there. Well, thank you, dr. Newmantoker. Appreciate mr. Chair, i yield back. The chair recognizes mr. Carter for five minutes. Thank you, mr. Chairman. And thank all of you for being here. This is, obviously, a very hot assumption on capitol hill, Artificial Intelligence. And particularly in the Health Care World were very concerned about it, and, look, im a big believer in telehealth. I represent a rural area, and ive seen how it has benefited us in the rural areas. As you know, all of you know that weve got a doctor shortage here in america particularly in our rural areas. Telehealth has been a great safe your for us savior for us. Ive always said theres a big difference between knowing something and realizing something. And during the can pandemic i think we realized just how porn telehealth can be important telehealth can be. I think there was an article in the paperer in the New York Times that said telehealth advanced more in one day than it had in the last ten years. So can you talk about using a. I. In your telehealth solution and how thats allowing doctors to be more efficient with their time so they can see more patients . Thank you for the question. I think its been repeated on this panel, a refrain youll hear, a very important benefit of a. I. Is enabling the doctors and nurses to do the thering and the nursing. The doctoring and the nursing. What transcarent does, right, is we really believe in freeing up the time of the doctor to spend with patients and reducing the time required for Administrative Burden. So the way we use a. I. Is in our clinic when a patience patient comes patient comes to the clinic, an a. I. Assistant gathers information from them and synthesizes that information for the doctors. That. Ables the doctors to come in enables the doctors to come in to the visit and spend time on that diagnosis and treatment and really creating the plan with the patient, right . That frees up time and that frees up capacity to see more patients including patients in rural areas since we serve 4. 4 million americans across the entire United States. Right. Good. Mr. Shen, let me ask you, ive heard sometimes theres bias in a. I. And that that can actually be good. Thats somewhat baffling to me, but nevertheless, can you explain to me how that might be and how bias can sometimes help improve the utility of a. I. In health care . Yeah, its an interesting question, congressman. I think whats very important here to make sure that we all emphasize is that as we train these a. I. Algorithms, these algorithms have to be trained with data thats respective of the Patient Population that theyre going to be serving. So its important that we work with our different clinical collaborators to find the right type of patient data to train these a. I. Algorithms, again, that are going to be applied toward that Patient Population and making sure that that Patient Population is reflected in the data thats actually training thosal a grit. S themselves. Okay. Ive got one last question, and its kind of for all of you or to any of you, if you will, and that is we have a Doctors Office here in congress, and im a pharmacist by profession. And ive served in the state legislature on health care, and one of the things that i notice is that a lot of our Health Care Costs have increased because of defensive medicine, doctors running up necessary lab tests just really to protect themselves from litigious patients or our situations. But how is that going to impact the practice of medicine if a physician doesnt use a. I. And then something happens and then, you know, all of a sudden theyre sued because you didnt use something that was available that you should have used . It seems to me like this could potentially increase Health Care Costs as well. I see the savings, yes, but ive also seen and tried to deal with it on a state, local and now on a federal level. And ill open it up. Whoever wants to comment, go ahead. Ill take a stand stab. So a stab. So i think that we we need to remind ourselves that Health Care Decisions are made by physicians and practitioners, right . They should be the ultimate decider when it comes to coverage, when it comes to do you need to be admitted to the hospital, what treatment do you need. These need to be made by Trained Health care finish. Youre a health care professional. Youre not a lawyer. I am. And im, you know, ive got a feel like from the lawyers perspective, theyre going to take a different approach. But thats why i think its important that we understand that as a community, as an industry that that were not turning over Decision Making. These are tools. These are tools in their tool belt, and we need to view them as such not as an authoritative decision, you know, that someone should be held accountable to. Anyone else . Quickly . Ill just say that if we can prove that a. I. Systems save lives, then people should be using them. And if we cant, then we should be relying on clinicians judgment. I dont know that well ever get away from relying on clinician judgment. I agree with you. I think that its unlikely certainly in my lifetime. Good. Okay, thank you. And i yield back, mr. Chairman. Gentleman yields back. The chair recognizes the gentleman from indiana, mr. Pence, for five minutes. Thank you, chair guthrie and Ranking Member eshoo, and thank you, panel, for being here today. Incorporating a. I. Technologies into Health Care Systems may improve and streamline diagnosis and Treatment Options in addition to easing the Administration Burden at health care facilities. Patients personal medical data and background information, however, is typically the foundation of a. I. Delivery in health care. The trust in safeguarding of personal information between patients and their providers or is critical for people receiving the highest quality of care. In the ecosystem of electronic apps and wearabilities wearables, there are areas where Health Care Data is not clearly protected. I had a hospital in my district in Hancock County that was on 60 minutes a number of years ago. Thats why this committee needs to consider a federal data policy law to set the foundation of protections on how such data thes collected, used and shared. We should do that before we can look at regulating a. I. And health care and find the balance in simultaneously encouraging private innovation. Our increasingly Digital World leaves hughes hoosiers and all americans in the dark about who has access to their information. Its alarming to me how little consumers and patients know about how personal details of their lives are collected, shared with third parties and monetized without their informed con sent, monetized with no recompense to the provide iser of the information. Patient trust and those responsible for safeguarding personal data is paraa mount in the use of emerging technologies in health care. As we introduce new a. I. Technologies in health care, patients deserve to have control over when their informations collected, who has access to their data, the right to remove their data and where their data might be shared. Heres the question. Finish should Health Care Organizations that collect protected medical information be transparent with patients on how their data is stored who has access to their data and for todays hearing identifying that a. I. Is part of the process . Yes. [laughter] i would agree with everything that a you just said is. I think that we fully support the idea that we should be transparent with our patients, and we current current are through a rigorous consent process as to how the datas being used, how its being protected and how its maybe stored and shared. And i think as the use of a. I. Expands, that will become increasingly important so patients can know where that datas going and how it might be used. Ill just add that a. I. Is entirely dependent on the data. So if we want the benefits of a. I. , we also have to do this in a way that enables us to use that data in a way to train and find al grit. S. We need to ensure were private and we dont create too many barriers to using that day to achieve all data to achieve all these outcomes weve been talking about. Yeah. It comes to mind back from a believes slide, its garbage in and garbage out. The wrong algorithms or the wrong collection point of thety that of the data can skew the outcome in a big way. And in finance we say you can pay off the National Debt with the wrong numbers. Would anyone if else like to answer that . Yes, sir. Yeah, i appreciate your question very much. I think that as the doctor said, your a. I. Strategy is your data strategy. I would point out that when the ecosystem of treatment, payment and operations, all of us Health Systems, providers, Insurance Companies are covered by hipaa laws around data privacy. And where i think the greater risk lies is with these Consumer Health apps and others that are accessing data either directly from patients, from Health Systems with patient cop sent via the 2 21st century cares act and other mechanismings. And i think youre absolutely right, theres a lot of Health Care Data floating around that is not subject to hipaa today because of these mechanisms. And so i think it is a risk and something that people should and your concern is that that would go into a. I. Comp payings . Is that what youre referring to . I think theres a number of risks, those data sets being used either to generate algorithms without transparency or to target for advertising other types of uses to patients without their awareness. I go to the doctor and i googled all the answers, right . So, yeah. Okay. Thank you very much. Mr. Chair, i yield back. Yes gentleman yields back, dr. Joyce is recognized for five minutes for questions. Thank you, chairman guthrie and Ranking Member issue, for member issue for being here today. We appreciate your time and testimony. Art Firm Intelligence has made a Significant Impact on our daytoday layoff, and the benefit lives and the benefits deryed through it use are very numerous. As this technology continues the explode onto the scene, it has become especially prevalent in health care. But like Many Industries where a. I. Is seeing a dramatic increase in usage, there are and there will be certain risks associated with it. So we must contend with it as policymakers. That should not demean the potential efficacy of its daytoday uses, applications and functions, a. I. Remains a tool, a tool that utilizes vast amounts of data and with its integration for health care space, we must be vim atlanta to insure that vigilant to insure that patient information is safe, secure and protected. As we move forward, Congress Must have that unique task of analyzing and further understanding a. I. s evolution and applicability when it comes to health care. While president bidens executive the order on Artificial Intelligence might lay out the administrations policy initiatives, it is still the responsibility of congress to legislate. It is paraa mount that congress has a firm grasp and a clear come premention on how a. I comprehension on how a. I. Interacts with existing regulations so we can insure that a. I. , first, does no harm. But instead, positively reshapes the health care industry. Dr. Nguyen, patients that live in rural areas like the district that i represent in pennsylvania often face barriers that impede their access to health care. Do you believe that a. I. Has the potential to quash those impediments . And if so, how can we incentivize further adoption of a. I. Technologies . Thank you for the question, congressman. Absolutely. You know, the distribution of care to rural areas and the various access are well known and great. A. I. Can quash those barriers and really close those gaps in a few different ways. First, you know, there is always a supply and demand problemyou think about distribution of resources across rural areas. Making clinicians more efficient, making clinicians more available means that there are more clinicians available to see those patients in rural areas. Two, many of the barriers come also from a lack of Health Literacy, a lack of access, right, to the Health Care System. A. I. Also can help patients in rural areas level the playing field, right, by assisting them in better understanding their care, better navigating the care system and better understanding how to find the best care for themselves. The incentives, right, that congress can end courage, right encourage, right, include development in education of a. I. Skill sets across the Health Care System but specifically in the clinicians who are going to practice in rural areas and the Health Care Leaders who are going to lead systems in rural areas. The rate at which ai is changing healthcare is likely going to require us to think a bit differently about how we regulate medical devices. The current approach based on laws from 1974 nerve pathology really anticipated the kind of technology were talking about so dealing with a model that can learn over time and its something well have to Work Together to learn what that pathway is. Theres incredible potential and movement and progress of ai is outpacing the current regulatory approach. Thank you, chairman guthrie, before i yield, i ask to enter a letter of college of resurgence. Obstructing cerumen jesse peasants so ordered. Thank you and thank you to the witnesses for being here and i yield. Gentleman yields back and the chair recognizes the chair lady for five minutes of questions. Thank you, chairman, and thank you all for being here. Talk about the pharmaceutical supply of the chain and its very difficult and complex to place and as a pharmacist im responsible for knowing every step in the supply chain from the manufacturer to the patient Health Outcomes and providing patient care and how do we use that and be reimbursed for that thank you, congresswoman for the questions. I think theres tremendous opportunity and look for opportunities that conserve up to the pharmacist and dug versus frequency accounting standards boards or substitutions and places to be more efficient and provide more effective treatment and those models are only going to improve and get better with the advent of these more advanced artificial intelligent algorithms and understanding the needs and demand for the patient in hospitals and unit basis to go upstream ken polcari sure theres the adequate supply to meet the demands and make preemptive steps to maintain adequate supplies and its another what do you have for creating payment models for ai healthcare and add ons . Some of my panelist had a chance to weigh in on this today. I think as this technologied a vans and becomes more meaningful and central part of Healthcare Delivery that cms finds an approach and reimburse for the ongoing work that in this case algorithm would do to help prevent complications, help reduce cost. The last comment i want to make is we have a great opportunity with ai to take a businesscase might bed minded approach and not just be another technology we deploy and adds more cost and add more reimbursement and therefore drive up the cost of the Healthcare System and instead be really thoughtful about how can these technologies make us more efficient and more effective and decrease the overall cost of Healthcare System as we deploy them. How do you think medical ai ultimately the liability of the treatment and patients with the position and weave had perhaps not ai tools for a long time but weve certainly had critical decisions to support tools for a long time that suggest interactions and dose range tools and the liability rests with the clinician to see the alerts, manage them, but make the best decisions of the patient. I think that if theres a step taken and begs all sorts of questions of licensing these tools. Exactly. Do you see a scenario where litigation might increase that doctors dont utilize ai . Thats a fantastic question and survey of patients six clicks to put in no charge and takes me ten seconds to write nc and took two minutes to six clicks to no charge. And it leads to burnout and something dr. Long hurst said and fda has not kept up with one of the first medical advices approved by the fda and an article on effectiveness of Artificial Intelligence screening and preventing vision loss from diabetes of policy mod and he will that would lead to reimbursement and whats great about this is that it increases access by having a device that can be put into any Persons Office whether its an eye care provider or family practitioner and the second letter is letter support from Johnson Johnson that does talk about privacy, equity, bias and transparency in the system since those have been brought up. Thank you, were going to accept a documents list at the end and make sure those are included and give my friend here a chance to review. Thanks. I know i did it first because im older and forget things. So wave herd a lot about ai in the potential residenting of unregulated ai integration and fda regulating the product since the 1970s and ai integration into healthcare raised the status quo of healthcare and seen in digital pathology and drug optimaization and integration in Patient Engagement and personalized risk prediction. Can you give examples where gaps exist in current regulation that congress can address to ensure continued innovation and better more Personalized Care for regulation. Were seeing the fda and working with the fda to try and make sure they stay current with the rapidly changing technologies and the challenge was acknowledged on the panel today and its how Artificial Intelligence continues to change and what these are all important aspects that the fda kneads to consider and actually not getting watered down in terms of its ability and more to inhibit us from being able to continue to develop and innovate in this particular area. Thank you. Many hospitals and Hospital Systems are facing significant Staff Shortages and seeing ai as a meaningful tool to alleviate some of the Administrative Burdens driving them out of the profession and the goldman and sachs could expose 300 million fulltime automation and what steps can Congress Take to facilitate better ai integration to help streamline profits that will allow healthcare parole professionals to focus on patients and billing and coding. Thats a great question and streamline the work force problem and only going to get bigger and the gap for supply and demand and nurses alone continues to increase over the next decade and id say the easy answer is lets not be told for the burden some regulation to deploy ai to support the Healthcare Work force and talking about ai directly influencing patients or providing diagnoses and thats Administrative Burden and move quickly to adopt the technologies and free up the work force to handle the increase in demand. With that, i yield back my time. Recognizes here from california. Five minutes. Thank you, mr. Chairman and to the witnesses and interesting hearing and Early Intervention programmed to ask you about some interaccounting standards boards with the fda and were really at a cross roads when it comes to devising a regulatory frame work and unique discipline and separate brewer rock seizure disorders and separate use of ai and follow the lead of countries like the uk who has pointed out because of risk of ai so con tect textual and the contextual and best equipped to regulate within the space withs a bunch of technical help and resources. We work as direct dialogue on the topic with a weekly basis. The other thing thats important to remindoros here and cant not just be considered a separate type of technology and this technology is also being embedded into the medical devices themselves as well. Ct scanners and built into the system better image quality and faster exams for the patient so a lot of benefits to the patient are happening already with the Ai Technology and built into the medical device themselves and thats a good point and also am heartened by the comment and feel the regulatory with the catalyzing innovation and thats a pretty powerful argument for maintaining that relationship and empowering the fda to regulate in that space. Machine learning all about bias and training to generalize and we call it bias talking about kind of maintaining our social stapedius muscle cards when we say for example it would be wrong to consider his race when make ago hiring decision and that means scrubbing the data to train ai and makes recommendations for things that can be used as proxies for race and thats the difficulty and youre talking about how important it is in the medical context of maintaining high quality data sets to avoid those kinds of biases. How do we ethically navigate this space of patient consent . If theres a chest xray and i think it was the doctor talking about detecting covid pneumonia for a chest xray and if you were a patient and come in and get a chest xray. Youve not consented for that xray and learning algorithm and is there a tight saying no, i dont want my data used and if you do, thats introducing bias into the algorithm and from a statistical sense, youre biasing the outcome of the algorithm and who knows what else the group of people would hold consent have in common. A statistician having biasing these algorithms. Thank you, congressman. Thats a great question. I come from the world of Clinical Research where theres always the opportunity to the issue of the replicating the sort of impact on hearing human biases that i mentioned in my testimony, i believe we have the circumstance and appropriateness and approach and thats the bias i dont want to replicate in my 20 minutes and well curated Gold Standard set is critical. Im an ai optimist and i would argue against your statement that the best we could expect is the replication of existing biases and thats a golden opportunity to remove the biases. Well get started and the next men is a gentleman from texas and mr. Crenshaw for five minutes. Thank you for doing this hearing. Theres a lot more on ai and multiple subjects and healthcare utilization of ai and healthcare might be the least of our worries. Thats where it gets scary and facebook and instagram and listen and watch my actions and then we make analysis based on them and heard them and today. Ai meant to have a person and be amazing for healthcare and going for everything and chatgpt and what kind of person is that and talking about healthcare seeming obvious to limit the data inputs. Does that need to be a law . Is that one of the regulations yall are talking about and im gonna stop there and ask you a couple of these saying that we need to regulate it and theres certain gaps with respect in particular to diagnosis in the ai space and i believe that for example if we think about direct to patient symptom checkers for diagnosis where theres a legal disclaimer at the bottom and medical advice and its really incumbent upon us to pay more attention to that Consumer Healthcare. Not just that but when people are making decisions about how and when to access the Healthcare System and its based upon some kind of alga rhythmic and theres no accountability to everything he says outside the proper confines of say the hospital setting or clinic theres a lot going on. Can you give me an example of that. Somebody types into the symptom checker theyre disy and the checker says dont worry, its nothing. Its little rock crystals in your ear. This is hypothetical. Or is it not . Its not hypothetical. Theres a lot of symptom checkers out there and studied significantly and looked at and accuracy often quite low. Theyre not fda regulated and what happens is that at the bottom theres a legal disclaimer and its a toy. If you want real medical advice and ask real medical professional and thats not how theyre dealing with that. Wed never want them to operate independently and in star track mode and definitely for foreseeable future. Wed have doctors blessing and even if theres Amazing Things to happen and seeing technology coming out of china and unfornatalie gets to the competition problem too if we overregulate things and apparently its diagnosing cancer and doctors look at that after the fact and its pancreatic cancer and its Amazing Things we can do with this technology and theres also amazing risks that can happen. The gentleman yields back and includes all members present for questions and we thank our witnesses for being here and included on the staff hearing and thatll be in order and members say theyre going to submit questions to you and they have ten business stakes in the question for the record and we ask that the witnesses respond to the questions promptly and members submit their question by the close of business on december 13th. Again, we appreciate everyone for being here and your time and this is something were still getting very curious and a lot very engaged members and want to understand it. Thats what were focused on and appreciate it and again, the subcommittee is adjourned