/ en Fri, 25 Apr 2025 17:29:18 -0500 Tue, 14 May 24 06:00:00 -0500 /aha-center-health-innovation-market-scan/2024-05-14-3-companies-hope-advance-health-research-quantum-leap <div class="container"><div class="row"><div class="col-md-8"><p><img src="/sites/default/files/inline-images/3-Companies-Hope-to-Advance-Health-Research-in-a-Quantum-Leap.png" data-entity-uuid="338d6359-aca5-47b1-9428-91d0142bce9f" data-entity-type="file" alt="3 Companies Hope to Advance Health Research in a Quantum Leap. A quantum computer." width="100%" height="100%"></p><p>Cleveland Clinic and IBM have embarked on a <a href="https://my.clevelandclinic.org/research/computational-life-sciences/discovery-accelerator?_gl=1*1w25toe*_ga*ODcyNzUzNjk1LjE3MTU2MDc0NDk.*_ga_HWJ092SPKP*MTcxNTYwNzQ0OC4xLjAuMTcxNTYwNzQ0OC4wLjAuMA.." target="_blank" title="Cleveland Clinic: Discovery Accelerator">10-year quantum computing initiative</a> that allows the health system’s team to work with the tech giant’s full spectrum of computation, including high-performance computing, artificial intelligence (AI) and machine learning (ML).</p><p>And even though this research and application of quantum computing is a long-term effort to explore its potential for facilitating faster diagnoses, developing customized medicines and optimizing data management, the partners are exposing entrepreneurs to the technology.</p><p>Three startups recently were named to participate in a 24-week <a href="https://www.lerner.ccf.org/news/article/?title=Cleveland+Clinic+announces+Quantum+Innovation+Catalyzer+Program+winners&id=616b0ab4b12ec7ccafa800d27f4f83d3121f1c8a" target="_blank" title="Cleveland Clinic Lerner Research Institute: Cleveland Clinic announces Quantum Innovation Catalyzer Program winners">Quantum Innovation Catalyzer Program</a>. The companies will connect with Cleveland Clinic experts and working groups to learn and share best practices and new applications.</p><p>The startups also will present their findings to an audience of investors, clinical, corporate and ecosystem partners.</p><h2><span>Algorithmiq</span></h2><p>One of the companies chosen, <a href="https://algorithmiq.fi" target="_blank" title="Algorithmiq homepage">Algorithmiq</a>, develops advanced algorithms to solve complex problems in life sciences. The team hopes to develop its proprietary <a href="https://algorithmiq.fi/wp-content/uploads/2022/11/algorithmiq-aurora-launch-press-release-nov-2022.pdf" target="_blank" title="Algorithmiq: Algorithmiq launches new drug discovery platform, Aurora ">Aurora software</a> to improve the field’s understanding of <a href="https://newsroom.clevelandclinic.org/2023/10/24/cleveland-clinic-selected-by-wellcome-leap-for-two-quantum-computing-research-projects" target="_blank" title="Cleveland Clinic: Cleveland Clinic selected by Wellcome Leap for Two Quantum Computing Research Projects">photon-drug interactions</a>. By understanding these interactions, researchers can improve cancer treatments, disease prevention and medical imaging.</p><h2><span>Picture Health</span></h2><p><a href="https://picturehealth.com/" target="_blank" title="Picture Health homepage">Picture Health</a>, meanwhile, specializes in AI diagnostics tailored for oncologists. The team will use quantum parallel processing to enhance medical image processing with a focus on digital pathology and high-resolution histology. This will lay the groundwork for cancer researchers to explore novel biomarkers and gain a better understanding of complex biological structures within medical data.</p><h2><span>Qradle</span></h2><p>The final company chosen, <a href="https://qradleinc.com/" target="_blank" title="Qradle Inc homepage">Qradle Inc.</a>, provides quantum software used to make drug discoveries. The team plans to develop a group of programs that will work together to aid drug-discovery research. This includes a classical computing-to-quantum computing conversion tool that can leverage existing classical AI/ML solutions for drug discoveries.</p></div><div class="col-md-4"><p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" alt="AHA Center for Health Innovation logo" width="721" height="130" data-entity- type="file" class="align-center"></a></p><p><a href="/center/form/innovation-subscription"><img src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png" data-entity-uuid data-entity-type alt width="360" height="300"></a></p></div></div></div>.field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 14 May 2024 06:00:00 -0500 Machine Learning /aha-center-health-innovation-market-scan/2023-01-10-how-personalize-care-across-four-generations-patients <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="How to Personalize Care across Four Generations of Patients. A digitally rendered human face next to health care icons in interconnected hexagons." data-entity-type="file" data-entity-uuid="988ae771-bb65-4801-b7ff-ced8f851e0d8" src="/sites/default/files/inline-images/How-to-Personalize-Care-across-Four-Generations-of-Patients.png" width="620" height="381"></p> <p>Health care organizations have become increasingly more sophisticated in how they collect, analyze and use patient-experience data to personalize and improve care delivery.</p> <p>These capabilities will be even more important in the years ahead as providers respond to growing competition from retail health care disruptors that have built long-term relationships with consumers and have deep insights into their personal preferences.</p> <p>Over the next five years, hospitals and health systems will need to make greater use of artificial intelligence (AI) and patient data to glean valuable insights that can help them differentiate their services, according to AHA’s recently released <a href="https://www.shsmd.org/resources/futurescan-2023" target="_blank" title="SHSMD: Futurescan 2023: Health Care Trends and Implications">Futurescan 2023</a>.</p> <p>Developed by the AHA’s Society for Health Care Strategy & Market Development in collaboration with the American College of Healthcare Executives, Futurescan 2023 provides insights from thought leaders across eight topic areas, including workforce trends, health equity, the competitive environment and more. Each report is supported with data from a 2022 survey of health care leaders.</p> <h2><span>Leverage AI to Personalize Care</span></h2> <p>Delivering more personalized health care depends on being able to segment and understand the differences in experiences among age, racial and ethnic groups, notes Chrissy Daniels, chief experience officer of Press Ganey Associates. Daniels and her colleague Joan Kelly partner in strategic planning at Press Ganey, provide insights on age generations and other important demographic groups such as the LBGTQ+ community and people of color.</p> <p>“Creating personalization in health care is reliant upon being able to segment and understand the differences in experiences, rather than the aggregation of experiences,” Daniels notes.</p> <p><img alt="Health Care Executives Were Asked: By 2028, will your hospital or health system be equipped to use machine learning/AI algorithms to drive care management for all patients that they serve? Already happening: 2%. Very likely: 28%. Somewhat likely: 31%. Neutral: 24%. Somewhat unlikely: 13%. Very unlikely: 3%. Source: "Futurescan 2023: Health Care Trends and Implications," AHA." data-entity-type="file" data-entity-uuid="33dc4c6a-20a6-40ef-bf45-08444f97d68f" src="/sites/default/files/inline-images/Health-Care-Executives-Were-Asked-Machine-Learning-AI.jpg" width="898" height="435"></p> <p>The use of AI will be critical to this effort, the authors state. The latest Futurescan survey data show that most responding organizations are in the middle of this journey. Fifty-nine percent said it was very likely or somewhat likely that their organization would be equipped to use machine learning or AI algorithms to drive care management for all their patients by 2028; only 2% report already using AI.</p> <h2><span>Key Takeaways to Personalize Care by Generation</span></h2> <p>Health care executives will need to know the current experiences among various generational cohorts and how to meet their specific needs, including:</p> <h3>1 <span>|</span> <span>Baby Boomers</span> <em>(born between 1946 and 1964)</em></h3> <p>This unique group wants the best and their demands have transformed areas like senior living, leisure and recreation. Concierge and luxury health care emerged because baby boomers want high-touch services, Daniels says, noting that this creates a growth opportunity for health care organizations.</p> <h4>Takeaway</h4> <p>Baby boomers have a high degree of confidence in brands that convey quality and are willing to pay for name-brand patient experiences. As a result, the market for destination medicine is likely to grow.</p> <h3>2 <span>|</span> <span>Gen X</span> <em>(born between 1965 and 1981)</em></h3> <p>Gen Xers are a silent but emerging demographic for patient acquisition, Kelly says. This cohort, more than any other, is handling multigenerational patient direction for their own children and often their parents. Health care organizations will need to respond by coordinating care in a family-convenient way.</p> <h4>Takeaway</h4> <p>As more care moves into the home setting and family members take on a greater role as caregivers, Gen Xers will need more support from health care organizations.</p> <h3>3 <span>|</span> <span>Millenials</span> <em>(born between 1981 and 1996)</em></h3> <p>Now the largest living adult generation in the U.S., millennials generally have been healthy and less insured than earlier cohorts. They value convenience first and foremost. They look for care close to where they want to receive it, need to know wait times, want to be able to message providers and find hours and reviews online.</p> <h4>Takeaway</h4> <p>Identifying all the locations affiliated with your organization and optimizing your presence on Google Maps has never been more important, Kelly says.</p> <h3>4 <span>|</span> <span>Gen Z</span> <em>(born between 1996 and 2012)</em></h3> <p>This age bracket has the highest percentage of young adults living at home in the post-World War II era, Daniels notes. They are likely to be covered by their parents’ health insurance and often defer care decisions to their mothers. They are comfortable with both virtual care and text-based care and are less likely to engage in face-to-face, in-person care.</p> <h4>Takeaway</h4> <p>This generation is more willing to seek care for behavioral health issues, particularly among transgender individuals, Daniels says. These individuals don’t separate physical and mental health, and access behavioral health at a much younger age than other generations.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 10 Jan 2023 06:15:00 -0600 Machine Learning /aha-center-health-innovation-market-scan/2022-12-13-its-new-genomics-data-services-aws-hopes-facilitate-rapid-advances <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="With Its New Genomics Data Services, AWS Hopes to Facilitate Rapid Advances in Precision Medicine. A DNA helix strand on a binary background made up of zeroes and ones." data-entity-type="file" data-entity-uuid="856756a3-e035-4248-9f9c-f82d13e9874b" src="/sites/default/files/inline-images/AWS-Hopes-to-Facilitate-Rapid-Advances-in-Precision-Medicine.png" width="620" height="381"></p> <p>Developing a deeper understanding of biology and the human genome has the potential to transform how diseases are treated. Standing in the way of this progress are challenges posed by the scale and complexity of data required to accelerate such advances.</p> <p>With the recent launch of <a amazon href="https://aws.amazon.com/about-aws/whats-new/2022/11/amazon-omics-generally-available/" introducing omics target="_blank title=">AWS Omics</a>, Amazon Web Services is using artificial intelligence, machine learning and other AWS and partner products and services to speed the translation of this data into actionable intelligence. Insights generated from the data can then be used to facilitate precision medicine and advance scientific discoveries.</p> <p>The service will help bioinformaticians, researchers and scientists store, analyze and generate more valuable insights from genomic, transcriptomic and other omics data.</p> <p>Clinicians will be able to query thousands of variants across genes at once to understand how genomic variation coupled with corresponding clinical data may affect human health or predict clinical outcomes, according to AWS. The platform also supports large-scale analysis and collaborative research.</p> <p><strong>Amazon Omics has three primary components:</strong></p> <ul> <li><span><strong>Omics-optimized storage</strong></span> that helps customers store and share their data efficiently and at low cost.</li> <li><span><strong>Managed compute-for-bioinformatics workflows</strong></span> that allow customers to run the exact analysis they specify without worrying about provisioning underlying infrastructure.</li> <li><span><strong>Optimized data stores</strong></span> for population-scale variant analysis.</li> </ul> <p>Children’s Hospital of Philadelphia now uses Amazon Omics to power its genomics projects to get a more comprehensive view of patients so that the best possible care can be delivered, Jeff Pennington, associate vice president and chief research informatics officer, told <a href="https://www.fiercehealthcare.com/health-tech/aws-launches-new-genomics-data-service-life-sciences-healthcare-companies" target="_blank" title="Fierce Healthcare: AWS launches new genomics data service for life sciences, healthcare companies">Fierce Healthcare</a>. “Combining multiple clinical modalities is foundational to achieving this. With Amazon Omics, we can expand our understanding of our patients’ health, all the way down to their DNA,” Pennington said.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 13 Dec 2022 06:00:00 -0600 Machine Learning /aha-center-health-innovation-market-scan/2022-08-16-mayo-clinic-mercy-data-collaboration-aims-drive <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="Mayo Clinic-Mercy Data Collaboration Aims to Drive Improved Outcomes. Two business people shake hands with their hands appearing inside a digital cloud icon with medial data analytics overlaid across the rest of the image." data-entity-type="file" data-entity-uuid="42c712c4-2b02-48a6-91d5-4c33ad442a1a" src="/sites/default/files/inline-images/Mayo-Clinic-Mercy-Data-Collaboration-Aims-to-Drive-Improved-Outcomes.jpg" width="620" height="381"></p> <p>Advances in artificial intelligence, machine learning and secure cloud-based environments have helped researchers make better use of aggregated data to enable earlier detection of disease and better treatment options. <a href="https://www.mayoclinic.org/" target="_blank" title="Mayo Clinic homepage">Mayo Clinic</a> and <a href="https://www.mercy.net/" target="_blank" title="Mercy homepage">Mercy</a> will take advantage of these greater capabilities and data science, as well as their immense volumes of de-identified data collected over the years, to partner on finding diseases earlier and determining the best treatment paths.</p> <p>The <a href="https://www.mercy.net/newsroom/2022-07-26/mayo-clinic--mercy-collaborate-to-globally-transform-patient-car/" target="_blank" title="Mercy.net: Mayo Clinic, Mercy Collaborate to Globally Transform Patient Care">10-year collaboration agreement</a> between the health systems will eliminate barriers to health care innovation by bringing together data and human expertise in a new way of working together, notes John Halamka, M.D., an emergency medicine physician and president of <a href="https://www.mayoclinicplatform.org/" target="_blank" title="Mayo Clinic Platform homepage">Mayo Clinic Platform</a>.</p> <p>The collaboration’s success rests on having each organization share its strengths.</p> <p>Mayo’s expertise in highly complex care and extensive investment in data science platforms together with Mercy’s two centuries of innovative care delivery in diverse communities and vast clinical information, including more than 500 million de-identified patient encounters, will provide the opportunity to develop high-value solutions and algorithms leading to more optimal care for patients. Additionally, Mercy’s and Mayo’s different populations and geographic locations will improve accuracy, reduce model bias and create more diverse, and therefore stronger, treatment recommendations.</p> <h2>Two Initial Patient Outcome Focuses for the Alliance</h2> <h3>1 <span>|</span> <span>Information Collaboration</span></h3> <p>The organizations will use a distributed data network that enables Mayo and Mercy to work with de-identified data assets without extracting or transferring any data between them. Instead, each organization will retain control over its data and enable more effective interventions. The goal is to help data scientists analyze patterns of effective disease treatment and prevention based on longitudinal data review over prolonged periods.</p> <h3>2 <span>|</span> <span>Algorithm Development and validation</span></h3> <p>Algorithms and machine learning models that come from the research will help indicate proven treatment paths based on years of patient outcomes. The evidence eventually could be made available to other providers to help them deliver more proactive and predictive care.</p> <p>The alliance is similar to that of <a href="https://www.truveta.com/" target="_blank" title="Truveta homepage">Truveta</a>, the clinical data analysis startup launched in 2021 by health systems including Tenet, Providence and CommonSpirit. Truveta currently has more than <a href="https://www.truveta.com/members/" target="_blank" title="Truveta: Our Innovative Health System Members">20 health systems</a> partnering in its venture.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 16 Aug 2022 06:00:00 -0500 Machine Learning /aha-center-health-innovation-market-scan/2022-05-17-weigh-social-factors-along-clinical-conditions <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="Weigh In Social Factors Along with Clinical Conditions When Predicting Sepsis Risks. A scan of a patient's chest showing inflamed lungs with a close up image of a bacterial infection." data-entity-type="file" data-entity-uuid="74fd74d3-0cf3-4ebb-adfb-ebc10e70453c" src="/sites/default/files/inline-images/Weigh-In-Social-Factors-Along-with-Clinical-Conditions.jpg" width="620" height="381"></p> <p>It’s no secret that social factors influencing health can lead to higher readmission rates and poorer outcomes. But a <a href="https://academic.oup.com/jamia/advance-article-abstract/doi/10.1093/jamia/ocac060/6576837" target="_blank" title="JAMIA: Inclusion of social determinants of health improves sepsis readmission prediction models">new study</a> indicates that these social factors when built into sepsis readmission models can help predict which patients are at risk of an unplanned readmission within 30 days.</p> <p>The study, conducted by <a href="https://www.nematilab.info/" target="_blank" title="The Nemati Lab @UC San Diego homepage">researchers at the University of California San Diego</a>, highlights the importance of identifying which patients may benefit from additional resources around the time of discharge or post-discharge, to prevent readmissions within 30 days.</p> <p>The report also underscores the importance of considering social factors of health alongside clinical conditions when developing predictive analytics for patients most likely to be readmitted for sepsis.</p> <p>The research team used a data set and patient-level survey information from the <a href="https://allofus.nih.gov/" target="_blank" title="National Institutes of Health All of Us Research Program homepage">National Institutes of Health All of Us program</a> for the study. These data included information from more than 265,000 individuals from 35 hospitals.</p> <p>Identifying which patients are most at risk is no simple task. Many hospitals use risk models and scores not specifically designed for sepsis patients to identify those most likely to be readmitted, the researchers explain.</p> <p>In this study, however, <a href="https://www.nematilab.info/projects.html#ML_CC" target="_blank" title="The Nemati Lab: Machine Learning in Critical Care">researchers identified potentially actionable factors</a> such as poor transportation to access care, lack of insurance or money to pay for care that are associated with 30-day readmissions. The study also identified other factors that may contribute to higher 30-day sepsis readmissions, including:</p> <ul> <li>Being male.</li> <li>Identifying as Black or Asian.</li> <li>Experiencing housing instability.</li> <li>Having a high school diploma, GED or less.</li> </ul> <p>Future studies will be needed to prospectively validate the research findings and further explore the relationship among social factors influencing health, readmissions and patient-centered outcomes, the researchers said.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 17 May 2022 06:00:00 -0500 Machine Learning /aha-center-health-innovation-market-scan/2022-02-08-walmart-leverage-ai-software-guide-employees <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="Walmart to Leverage AI Software to Guide Employees to Clinicians. The Walmart logo on a screen surrounded by medical icons with a physician tapping on it." data-entity-type="file" data-entity-uuid="00ed140c-2a80-4c9a-9bc7-22c0d36c8878" src="/sites/default/files/inline-images/AHA-MS-Walmart-to-leverage-AI-software-to-guide-employees-to-clinicians.jpg" width="620" height="381"></p> <p>For several years now, Walmart has guided its employees with major surgical or other complex medical needs to centers of excellence. The move was prompted by a desire to ensure better outcomes and to more effectively manage employee health costs. Now the megaretailer is going a step further.</p> <p>Walmart recently partnered with <a href="https://www.prnewswire.com/news-releases/walmart-and-health-at-scale-launch-customized-provider-recommendations-for-plan-participants-301471149.html?mkt_tok=NzEwLVpMTC02NTEAAAGCZGHmD2AJa7VhHfxDtV7aVPufriGba7UttETKKFNe5CIHla78ZhxjTvu6AQ-lMcEFmP76ZevDpQPtGIEGsEs" target="_blank" title="Cision PR Newswire: Walmart and Health at Scale Launch Customized Provider Recommendations for Plan Participants">Health at Scale</a>, a company that uses predictive artificial intelligence to direct patients to providers who match their specific health needs. Walmart will use new software from <a href="https://healthatscale.com/" target="_blank" title="HEALTH[at]SCALE homepage.">Health at Scale</a> to make personalized clinician recommendations to employees and their families who are enrolled in the company’s health plan and who work in locations where Health at Scale is offered.</p> <p>The platform uses machine intelligence to identify providers who have successfully treated patients with similar characteristics and care needs. It also uses patient health data to determine which patients could be at greater risk of adverse outcomes.</p> <p>Health at Scale was founded by clinical and machine learning faculty from Massachusetts Institute of Technology, Stanford, Harvard and the University of Michigan whose goal is to achieve better outcomes for patients.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 08 Feb 2022 06:00:00 -0600 Machine Learning /aha-center-health-innovation-market-scan/2021-08-24-primary-care-medicare-rates-one-startups-recipe <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="Primary Care at Medicare Rates: One Startup’s Recipe for Expansion. Carbon Health logo on a building." data-entity-type="file" data-entity-uuid="fec3e111-6894-4c6d-b1a4-a11f10765d72" src="/sites/default/files/inline-images/ms_082421_item2_CarbonHealth_190_1993210.jpg" width="190" height="127" class="align-left">Carbon Health, a San Francisco-based startup founded in 2015, has a simple but audacious goal: to become the largest provider of primary care services in the U.S. Whether it ever approaches that goal, there’s no question that the omnichannel provider is attracting investors’ attention with its unusual model.</p> <p>With a valuation of more than $3.3 billion, Carbon Health recently closed a <a href="https://www.mobihealthnews.com/news/multimodal-primary-care-provider-carbon-health-scores-350m-become-largest-us-and-more-digital" target="_blank">$350 million investment round</a> led by Blackstone’s Horizon platform. The company says it will use the money to buy new technology to differentiate and expand its services.</p> <p>Deploying an iPad-based, streamlined electronic health record (EHR) and offering in-person care through 80 clinics in 12 states and virtual care in 23 states, Carbon Health charges Medicare rates to all payers. Part of its approach is an intuitive EHR built in concert with physicians and patients that the company says requires minimal training. Its platform also uses machine learning to identify most likely diagnoses, provides in-app messaging to get second opinions and integrates with electronic prescribing and labs.</p> <p>In the past year, Carbon Health has treated more than 1 million patients, a 129% increase (excluding patients seen for COVID-19 testing or vaccinations). During the pandemic, the company’s staff doubled from 800 to 1,600 full-time employees. Its future plans call for operating 1,500 clinics by 2025.</p> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 24 Aug 2021 06:00:00 -0500 Machine Learning /aha-transformation-talks/ep11-patient-care-ai <div></div> <div> /* Banner_Title_Overlay_Bar */ .Banner_Title_Overlay_Bar { position: relative; 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bottom:0px } @media (max-width:567px){ .Banner_Title_Overlay_Bar.TT_Banner h1{ display: inline-block; position: relative; max-width:calc(100% - 200px); } } @media (max-width:567px){ .Banner_Title_Overlay_Bar.TT_Banner h1{ display: inline-block; position: relative; max-width:100%; background-color: #f6f6f6 } .Banner_Title_Overlay_Bar.TT_Banner img{ float: none !important; margin: auto; display:block ; position: relative ; } } <header class="Banner_Title_Overlay_Bar TT_Banner"><img alt="Banner Image" src="/sites/default/files/2020-12/AHA_TT_thumbnail_300x173.jpg" /> <div> <h1 class="tth1">Improving Hospital Performance Using AI and Patient Data</h1> </div> </header> </div> /* CntMenuSub */ .CntMenuSub{ margin:20px 0px; padding-bottom: 5px; color: #afb1b1; letter-spacing: 1.5px; font-weight: 400; font-size: 11.2px; } .CntMenuSub .CntMenuBar{ border-bottom: 1px solid lightblue; } /* if includes a logo */ @media (min-width:361px){ .CntMenuSub.CntMenuSubLogo .CntMenuBar{ margin-top: 10px; float: left; width: calc(100% - 425px); } } @media (max-width:767px) and (min-width:361px){ .CntMenuSub.CntMenuSubLogo .CntMenuBar{ float: left; width: calc(100% - 0px); } .CntMenuSub.CntMenuSubLogo img{ width: auto; } } /* // */ .CntMenuSub .CntMenuBar a:after{ content: "|"; padding: 0 3px 0 6px; color: #555; } .CntMenuSub .CntMenuBar a:last-child:after{ content: ""; } .CntMenuSub .CntMenuSubHome, .CntMenuSub .CntMenuSubParent{ text-transform: uppercase; color: #555; opacity: .9; } .CntMenuSub .CntMenuSubParent{ } .CntMenuSub .CntMenuSubChild{ } .CntMenuSub .CntMenuSubCurrent{ opacity: .7; } .CntMenuSub .CntMenuSubHome:hover, .CntMenuSub .CntMenuSubParent:hover{ text-transform: uppercase; color: #d50032; } /* CntMenuSub // */ <div class="row CntMenuSub"> <div class="CntMenuBar"><a class="CntMenuSubParent" href="./" id="CntMenuSubParentOnly"></a> <span class="CntMenuSubChild" id="CntMenuSubChildz"></span></div> <div> </div> </div> var url = window.location.pathname; var path = url.split('/').slice(1, 2).join('/'); var pathreplace2 = path.replace(/-/g, " "); document.getElementById("CntMenuSubParentOnly").innerHTML =(pathreplace2); var y = document.getElementsByTagName("h1"); document.getElementById("CntMenuSubChildz").innerHTML = y[0].innerHTML; <div class="row"> <div class="col-md-6"> <div class="embed-responsive embed-responsive-16by9">View</div> <p>Sponsored by: <a href="https://www.wolterskluwer.com/en" target="_blank"><img alt="Wolters Kluwer Logo" src="/sites/default/files/2021-07/Logo_WoltersKluwer_834x313.jpg" /></a></p> </div> <div class="col-md-6 center_body"></p> <p class="center_Lead"></p>--> <p><strong>Hospitals and health systems continue to face challenges in rapidly identifying and standardizing care of patients at risk for adverse events.</strong></p> <p>These events include sepsis as well as those related to medication use, health care-associated infections like Clostridium difficile and other causes of patient deterioration such as respiratory insufficiency and acute myocardial infarction. The opportunity for improvement in these areas is significant, as data have shown.</p> <ul> <li>On average, the Centers for Disease Control and Prevention reports, one in 31 patients has at least one health care-associated infection.</li> <li>1 in five hospital deaths in the U.S. are caused by sepsis according to a January 2020 report in The Lancet.</li> </ul> .TTreadmore{ font-weight: 700; margin-top:50px; } <p class="TTreadmore">Download the <a href="/system/files/media/file/2021/07/TT_ep11-patient-care-ai.pdf" target="_blank">Episode Abstract</a> >></p> </div> </div> <div class="container-fluid row"> <div class="row"> <div class="col-md-12"> /* CalloutBorderWrapper - aka SponsorMarketoForm */ .CalloutBorderWrapper { background-color: ; padding: 5px 25px 20px 25px; border: solid 2px #307FE2; margin: 25px 100px 25px; } @media (max-width:640px){ .CalloutBorderWrapper { margin: 25px 0px 25px; } } .CalloutBorderWrapper h3 { margin: 10x 0 0 0; color: #555; font-size: .7em; text-transform: uppercase; font-weight: 400; letter-spacing: 3px; max-width: 200px; /* Custom for the copy length */ background-color: #fff; padding: 5px 15px; position: relative; top: -35px } .CalloutBorderWrapper h2 { color: #002855; } .CalloutBorderWrapper .CalloutBorderWrapperHolder { background-color: ; padding: 15px; display: inline-block; margin-bottom: 25px; } .CalloutBorderWrapperHolder form { margin: auto; } /* CalloutBorderWrapper - aka SponsorMarketoForm // */ <div class="cta--image-container CalloutBorderWrapper center_body"> <h3>Key Take Aways</h3> <p>Here is what our experts had to say:</p> .sp_CTA5_holder { margin-top:50px; border-bottom: solid 1px #555; padding-bottom: 50px; } .sp_CTA5_holder_last { border-bottom: solid 0px #555; } .sp_CTA5_holder >div{ overflow: auto; } .sp_CTA5_holder ul { list-style: none; /* Remove default bullets */ padding-left: 0px; margin-bottom: 25px; } .sp_CTA5_holder ul li { margin-bottom: 7px; line-height: 1.5em; } .sp_CTA5_holder ul li::before { content: " "; font-size: 1em; margin-right: 10px; display: inline-block; height: 12px; background-color: #d50032; width: 12px; position: relative; top: 0px; } .sp_CTA5_holder ul li { padding-left: 23px; text-indent: -23px; } .sp_CTA5_holder h2 { color: #002855; /*! 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Perlin" src="/sites/default/files/2021-07/Jonathan_Perlin_300x300.jpg" /> <p class="ci_profile_name">Jonathan B. Perlin, M.D., Ph.D., MSHA, MACP, FACMI</p> <p class="ci_profile_title">President, Clinical Operations & Chief Medical Officer</p> <p class="ci_profile_company">HCA Healthcare</p> <p class="ci_profile_award"> </p> <div class="ci_profile_social"> </div> </div> <div class="col-md-4 col-sm-4 ci_profile"><img alt="Itay Klaz" src="/sites/default/files/2021-07/Itay_Klaz_300x300_0.jpg" /> <p class="ci_profile_name">Itay Klaz, M.D., MCHI</p> <p class="ci_profile_title">Medical Director</p> <p class="ci_profile_company">Wolters Kluwer</p> <p class="ci_profile_award"> </p> <div class="ci_profile_social"> </div> </div> <div class="col-md-4 col-sm-4 ci_profile"><img alt="Chad E. Beebe" src="/sites/default/files/2018-08/Cleary-Fishman_Marie.jpg" /> <p class="ci_profile_name">Marie Cleary-Fishman, BSN, MS, MBA, CPHQ</p> <p class="ci_profile_title">Vice President, Clinical Quality, AHA Center for Health Innovation</p> <p class="ci_profile_company">���������� Association</p> <p class="ci_profile_award"> </p> <div class="ci_profile_social"> </div> </div> </div> </div> </div> <div class="col-md-1"> </div> </div> <div class="container-fluid CenterCallout_a"> <div class="row"> <div class="col-md-1"> </div> <div class="col-md-10 CenterCallout_a-Center"> <h4>Fuel Your Transformation</h4> <p>Health care leaders are more in need of innovative solutions than ever before. The <a href="/aha-transformation-talks">AHA Transformation Talks series</a> of video discussions among health care thought leaders offers insights to help hospital and health systems navigate health care’s new, disruptive environment and prepare for what’s next. Each 10-minute video in this series focuses on a transformational topic explored by the <a href="/environmentalscan" target="_blank">2021 AHA Environmental Scan</a> and SHSMD's <a href="https://www.shsmd.org/futurescan" target="_blank">Futurescan 2021-2026: Health Care Trends and Implications</a>. Explore the videos on this page for fresh ideas and best practices to guide you through this time of tremendous upheaval.</p> </div> <div class="col-md-1"> </div> </div> <div class="row"> <div class="col-md-1"> </div> <div class="col-md-10"> <div class="row rowEqual_768"> <div class="col-sm-4 CenterCallout_a_Holder CenterCallout_a-Center"> <div class="CenterCallout_a_Wrapper"><a href="/system/files/media/file/2021/07/TT_ep11-patient-care-ai.pdf" target="_blank"><img alt="icon" class="EffectiveEducation" src="/sites/default/files/2020-11/Speech_Bubble_icon.png" /></a> <h2 class="CenterCallout_a_SectionTitle"><a href="/system/files/media/file/2021/07/TT_ep11-patient-care-ai.pdf" target="_blank">Abstract Overview</a></h2> <p>Read this abstract to learn about how current demands are impacting the health care workforce.</p> </div> </div> <div class="col-sm-4 CenterCallout_a_Holder CenterCallout_a-Center"> <div class="CenterCallout_a_Wrapper"><a href="/system/files/media/file/2021/07/Whitepaper-AI-Driven-Clinical-Surveillance_TTalks.pdf"><img alt="icon" class="EffectiveEducation" src="/sites/default/files/2020-12/Tools_icon.png" /></a> <h2 class="CenterCallout_a_SectionTitle"><a href="/system/files/media/file/2021/07/Whitepaper-AI-Driven-Clinical-Surveillance_TTalks.pdf" target="_blank">Sponsor Toolkit</a></h2> <p>AI-Driven Clinical Surveillance Accurately Identifies Patient Risk and Informs Objective Care Decisions</p> </div> </div> <div class="col-sm-4 CenterCallout_a_Holder CenterCallout_a-Center"> <div class="CenterCallout_a_Wrapper"><a href="/center/emerging-issues/market-insights/ai/ai-care-delivery"><img alt="icon" class="CenterCallout_a_Icon" src="/sites/default/files/2020-12/Documents3_icon.png" /></a> <h2 class="CenterCallout_a_SectionTitle"><a href="/center/emerging-issues/market-insights/ai/ai-care-delivery">AHA Resource</a></h2> <p>AI and Care Delivery: Emerging opportunities for artificial intelligence to transform how care is delivered.</p> </div> </div> <div class="CenterCallout_a_Wrapper"> <img alt="icon" class="CenterCallout_a_Icon" src="/sites/default/files/2020-12/Documents3_icon.png"> <h2 class="CenterCallout_a_SectionTitle">AHA Resources</h2> <ul> <li><a href="/">xxxx</a></li> <li><a href="/">xxxx</a></li> </ul> </div> </div>--></div> </div> <div class="col-md-1"> </div> </div> </div> <h3>Video Series Developed in Collaboration with:</h3> <a href="https://iprotean.com/"><img src="/sites/default/files/2020-11/Logo_iProtean_VirtualEd_834x313.jpg" /></a> Wed, 21 Jul 2021 07:47:54 -0500 Machine Learning /aha-center-health-innovation-market-scan/2021-04-20-study-finds-new-commercial-ai-devices-often <div class="container"> <div class="row"> <div class="col-md-8"> <p><img alt="Study Finds New Commercial AI Devices Often Lack Key Performance Data" data-entity-type="file" data-entity-uuid="88d736cb-61f4-4e9f-9c7a-9016f2636f63" src="/sites/default/files/inline-images/ms_042021_item1_AI_620_1885315.jpg" width="620" height="381"></p> <p>Enthusiasm for and adoption of commercial artificial intelligence (AI) tools to aid clinical decision-making and patient care have been accelerating at a rapid pace. A new study, though, cautions that critical information often is missing from the Food and Drug Administration (FDA) clearance process that could measure how these devices actually work in patient care.</p> <p>The study, published in the research journal <a href="https://www.nature.com/articles/s41591-021-01312-x.epdf?sharing_token=8BNOnt1UUOf0iPsJ9yU0J9RgN0jAjWel9jnR3ZoTv0M6PlZXWQqbgCrdZtSbNOnPDQlhZJ-fPz8LJ4JqCoxGYshqBh62049hIhMSEfJaE7pKaceG00AD1FUBHLZ5YShokEBQWoF6kBbZitEELPDqWu-9esaFE8DcbdQ1QAgRChw%3D&utm_source=STAT+Newsletters&utm_campaign=fdec4d0d0d-health_tech_4-6-21_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-fdec4d0d0d-152708089" target="_blank">Nature Medicine</a>, notes that while the academic community has started to develop reporting guidelines for AI clinical trials, there are no established best practices for evaluating commercially available algorithms to ensure their reliability and safety.</p> <p>And while the FDA is working on regulations for how commercial AI devices should be evaluated, provider organizations will have to analyze these tools based on limited data. What concerns authors of the Nature Medicine article is whether the information submitted by manufacturers is sufficient to evaluate device reliability.</p> <p>Most of the cleared AI tools are designed to work as triage devices or to support clinician decision-making. In their review of 130 FDA-cleared AI devices, the researchers found that 126 were based on retrospective data, i.e., data collected from clinical sites before evaluation. And none of the 54 high-risk devices were evaluated by prospective studies. This is significant because prospective studies are needed to show how devices actually work with physicians’ and hospitals’ data systems.</p> <p><img alt="In reviewing 130 FDA-cleared AI devices, researchers found that 126 were based on retrospective data. Source: Nature Medicine, Vol. 27: 576-584, April 2021." data-entity-type="file" data-entity-uuid="06d05679-47ed-47a4-ab63-91c797db6ef9" src="/sites/default/files/inline-images/ms_042021_item1_AI_quote_390_1885317.jpg" width="309" height="436" class="align-right">“A prospective randomized study may reveal that clinicians are misusing this tool for primary diagnosis and that outcomes are different from what would be expected if the tool were used for decision support,” the study notes.</p> <h2>Lack of Data on Effectiveness by Demographics, Sites</h2> <p>Most disclosures did not include the number of sites used to evaluate the AI devices nor whether the tools had been tested to see how they perform in patients of different races, genders or locations. This shortcoming in the current review system can make a significant difference in how AI tools perform, the study notes. Also, it wasn’t clear how many patients were involved in the testing of an algorithm. Of the 71 devices in which this information was shared, companies had evaluated the AI tools in a median of 300 patients. Having more thorough public disclosures would be beneficial to provider organizations who need to identify potential vulnerabilities in how a model performs across different patient populations.</p> <h2>How the FDA Is Responding</h2> <p>In January, the FDA released its first <a href="https://www.fda.gov/media/145022/download" target="_blank">AI and machine learning (ML) action plan</a>, a multistep approach to further the agency’s management of advanced medical software. The plan outlines the FDA’s next steps toward advance oversight for AI-ML-based software as a medical device and will further develop the proposed regulatory framework.</p> <p>The agency acknowledges that AI-ML-based devices have unique considerations that require a proactive, patient-centered approach to their development and utilization that takes into account such issues as usability, equity, trust and accountability. The FDA is addressing these issues by promoting the transparency of the devices to users, and to patients more broadly. Comments from the health care field identified the need for manufacturers to clearly describe the data that were used to train the algorithm, the relevance of its inputs, the logic it employs (when possible), the role intended to be served by its output, and the evidence of the device’s performance.</p> <h2>3 Tools to Navigate AI Decision-Making</h2> <p>These AHA Market Insights reports can help leaders navigate the AI landscape:</p> <ul> <li><a href="/center/emerging-issues/market-insights/ai/tips-and-tricks-selecting-right-ai-vendor-partner">“Selecting the Right AI Vendor Partner,”</a> an AHA member-only resource, provides key questions to ask vendors, whether organizations are working on a homegrown AI project or outsourcing AI projects.</li> <li><a href="/system/files/media/file/2019/11/Market_Insights_AI_Care_Delivery.pdf">“AI and Care Delivery”</a> helps leaders successfully integrate AI-powered technologies to improve outcomes and lower costs at each stage of care.</li> <li><a href="/center/emerging-issues/market-insights/ai/17-questions-leadership-teams">“17 Questions for Leadership Teams,”</a> another AHA member-only tool, provides strategic questions leaders should consider when integrating AI technologies into care delivery.</li> </ul> </div> <div class="col-md-4"> <p><a href="/center" title="Visit the AHA Center for Health Innovation landing page."><img alt="AHA Center for Health Innovation logo" data-entity- data-entity-uuid="7ade6b12-de98-4d0b-965f-a7c99d9463c5" src="/sites/default/files/inline-images/logo-aha-innovation-center-color-sm.jpg" type="file" class="align-center"></a></p> <a href="/center/form/innovation-subscription"><img alt data-entity-type data-entity-uuid src="/sites/default/files/2019-04/Market_Scan_Call_Out_360x300.png"></a></div> </div> </div> .field_featured_image { position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } .featured-image{ position: absolute; overflow: hidden; clip: rect(0 0 0 0); height: 1px; width: 1px; margin: -1px; padding: 0; border: 0; } Tue, 20 Apr 2021 06:30:00 -0500 Machine Learning /sponsored-executive-dialogues/2020-01-31-power-harnessing-patient-safety-data-artificial <div class="container"> <div class="row"> <div class="col-md-8"> <h4 class="sponsortype">Executive Dialogue</h4> <div class="col-md-4"><a href="/system/files/media/file/2020/01/The-Power-of-Harnessing-Patient-Safety-Data-with-Artificial-Intelligence.pdf"><img alt="RL Executive Dialogue" src="/sites/default/files/2020-01/The-Power-of-Harnessing-Patient-Safety-Data-with-Artificial-Intelligence-cover.jpg" /> </a></div> <p> </p> <p>As artificial intelligence (AI) and machine learning (ML) continue expanding into health care, its full potential remains unknown. Health care organizations are beginning to use AI and ML to improve clinical decision-making, enhance patient engagement and make health care providers more efficient and productive. The development of an AI system, however, is only as good as the data used to create it. This executive dialogue will discuss the intersection of AI and patient safety, exploring ways big data can be harnessed to prevent patient harm. It not only will examine key metrics that organizations can use to identify the potential for harm, but it also will explore ways to achieve clinician support and buy-in.</p> </div> <div class="col-md-4"> <div class="sponsorlogo_rr"> <h4>Sponsored by:</h4> <a href="https://www.rldatix.com/en-nam/" target="_blank"><img alt=" logo" src="/sites/default/files/2020-01/RLDatix_logo.jpg" /></a></div> </div> </div> </div> body p, body li { font-size: 16px; } .sponsortype { color: #9d2235; font-size: 1.5em; margin: 0px; } .sponsorlogo_rr{ border: solid 1px #b1b3b3; padding: 15px; margin-bottom:25px; } .sponsorlogo_rr img{ max-height: 150px; margin: auto; display: block; } Fri, 31 Jan 2020 10:16:22 -0600 Machine Learning