/ en Sun, 15 Jun 2025 00:12:57 -0500 Thu, 12 Jun 25 14:26:15 -0500 /news/headline/2025-06-12-joint-commission-announces-partnership-develop-best-practices-ai-health-care <p>The Joint Commission June 11 <a href="https://www.jointcommission.org/resources/news-and-multimedia/news/2025/06/the-joint-commission-and-coalition-for-health-ai-join-forces/">announced</a> a new partnership with the Coalition for Health AI to help accelerate the development and adoption of best practices and guidance for using artificial intelligence in health care. The organizations will co-develop a series of AI playbooks, tools and a certification program based on The Joint Commission’s platform for evidence-based standards and CHAI’s consensus-based best practices for health AI. The first guidance will be released this fall, followed by AI certification.</p> Thu, 12 Jun 2025 14:26:15 -0500 Artificial Intelligence (AI) /care-delivery-transformation/clinical/technology-enabled-care <div class="cdt-banner-wrap"><div class="clinical-banner-wrap"><div class="clinical-banner-wrap-content"><h1 class="text-align-center">Technology-enabled Care</h1><h2 class="text-align-center">Care Delivery Transformation Framework<br><span>Clinical Settings</span></h2></div></div></div> Wed, 11 Jun 2025 04:44:42 -0500 Artificial Intelligence (AI) /education-events/harnessing-power-partnerships <p><em><strong>AHA Leadership Scan: A Series of Virtual Panel Discussions</strong></em><br><br><strong>Harnessing the Power of Partnerships </strong><br><em>Transformative strategies to cost-containment and technological integration </em> </p><p><strong>Tuesday, July 15, 2025 </strong><br><em>1 - 2 p.m. Eastern; noon - 1 p.m. Central; 10 - 11 a.m. Pacific  </em></p><p>Health care providers are at a tipping point. Mounting financial pressures, a constrained labor market, and the accelerating pace of technological change are exposing the limits of today’s labor-dependent models. In this environment, sustainable reinvention—not incremental optimization—is essential. Join us as we explore bold strategies to free up financial and human capacity by leveraging sourcing partnerships, automation, and AI to fundamentally rethink how work gets done.  </p><p><strong>Implementing innovative cost-containment approaches. </strong>Panelists will explore the implementation of robust utilization management programs and the transformation of care delivery models, such as shifting to home-based care, to achieve more sustainable and cost-effective health care services.</p><p><strong>Embracing the power of partnership in transformation.</strong> Participants will discover the benefits of partnering with sourcing providers that not only addresses financial elements, but also accelerates the transformation process. This partnership mindset not only makes financial sense but also accelerates the transformation process by providing access to specialized talent and skills necessary for successful implementation.</p><p><strong>Enhancing operational efficiency.</strong> Learn how health care organizations are developing tech strategies that can enhance operational efficiency across various areas of the health care value chain and augment human processes with automation. This includes understanding the specific tools and technologies that can be leveraged to streamline processes, identify cost variations and improve patient outcomes.</p><p><strong>Attendees Will Learn:</strong></p><ul><li>To identify nontraditional approaches to advancing efficiency in back-office operations.</li><li>To build greater organizational resiliency in supply chain and other essential operations.</li><li>To explore the value of various partnership operating models.</li><li>To benefit from the collective insights from front-line, tech-savvy leaders who are optimizing the power of automation to drive improved performance.</li></ul><p><strong>Session Panelists:</strong></p><p>Kristin Ficery <br><em>Senior Managing Director </em><br><strong>Accenture</strong></p><div><p lang="EN-US" lang="EN-US" paraid="2146811975" paraeid="{80e1b98a-6687-4f86-896c-1f654d1b0984}{119}">Steve Downey, M.S., Management of Technology <br><em>Vice President, Chief Supply Chain & Support Services Officer </em><br><strong>Cleveland Clinic Foundation </strong></p><p lang="EN-US" lang="EN-US" paraid="2146811975" paraeid="{80e1b98a-6687-4f86-896c-1f654d1b0984}{119}">Amanda Chawla, MBA, MHA, FACHE, CMRP<br><em>Senior Vice President, Chief Supply Chain and Post Acute Care Officer</em><br><strong>Stanford Health Care </strong></p></div><div><p lang="EN-US" lang="EN-US" paraid="1767124233" paraeid="{8314609e-544e-4471-90c8-9b0d143c8e15}{77}">William “Bill” Moir, MBA <br><em>SVP of Care Delivery Support Services Operations </em><br><strong>Henry Ford Health </strong></p></div><p><strong>AHA Moderator:  </strong></p><p>Mike Schiller  <br><em>Executive Director, </em><strong>Association for Health Care Resource & Materials Management (AHRMM)  </strong><br><strong>The ���������� Association </strong></p><p>By attending the AHA Leadership virtual panel discussion "Harnessing the Power of Partnerships" offered by the AHA, participants can earn up to <strong>1 ACHE Qualified Education Hour</strong> toward initial certification or recertification of the Fellow of the American College of Healthcare Executives (FACHE) designation. </p> Tue, 03 Jun 2025 09:00:00 -0500 Artificial Intelligence (AI) /aha-center-health-innovation-market-scan/2025-06-03-3-health-care-takeaways-google-io-2025 <div class="container"><div class="row"><div class="col-md-8"><img src="/sites/default/files/inline-images/3-Health-Care-Takeaways-from-Google-IO-2025.png" data-entity-uuid="b23e93d4-46a0-4e5e-b31c-f6462add9566" data-entity-type="file" alt="3 Health Care Takeaways from Google I/O 2025. The logo for Google I/O 2025 conference." width="1200" height="751"><p>It was no surprise that artificial intelligence (AI) dominated news coming out of last month’s <a href="https://blog.google/technology/ai/google-io-2025-all-our-announcements/" target="_blank" title="Google: 100 things we announced at I/O">Google I/O 2025</a>, the tech giant’s annual developer conference.</p><p>And as in past conferences, excitement abounded about where AI is headed and how fast some of the grandest visions for the technology’s promise could be realized. Here’s a rundown of what grabbed our attention.</p><h2>Could AGI Really Be Here in Five Years?</h2><p>Google's co-founder Sergey Brin and Google DeepMind CEO Demis Hassabis shared slightly different projections about whether artificial general intelligence (AGI) would arrive by 2030 or slightly later.</p><p>AGI generally has been understood to mean AI that matches or surpasses most human capabilities, which could have potentially huge implications for health care and other fields.</p><p>The trouble is, AGI remains somewhat of a unicorn. Plenty of tech gurus and AI developers can describe AGI, but no consensus exists on what it would look like or how it could change lives once it gets here, notes a recent <a href="https://www.axios.com/2025/05/21/google-sergey-brin-demis-hassabis-agi-2030" target="_blank" title="Axios: Google leaders see AGI arriving around 2030">Axios report</a>.</p><p>Hassabis predicts developers likely will need a couple more big breakthroughs to get to AGI. One of those breakthroughs already may have been partially achieved via reasoning approaches that Google, OpenAI and others unveiled recently, he said.</p><h3>Takeaway</h3><p>AGI developments bear watching in health care, regardless at what pace they occur. And make no mistake. Experts believe AGI has a future in all fields — whether that’s two, five or 10 years from now. AGI's self-learning can transform health care, improving diagnoses and personalized treatments. However, its integration presents regulatory, ethical and public perception challenges.</p><h2>MedGemma Could Speed Development of Health AI Apps</h2><p>The launch of <a href="https://deepmind.google/models/gemma/medgemma/" target="_blank" title="DeepMind: MedGemma homepage">MedGemma</a>, an open model for multimodal medical text and image comprehension, has the potential to accelerate development of new health applications.</p><p>It is designed to be a starting point for developers building such applications as analyzing radiology images or summarizing clinical data, and its small size makes it efficient for fine-tuning specific needs. When evaluated on the <a href="https://arxiv.org/pdf/2009.13081" target="_blank" title="What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams">MedQA benchmark</a>, its baseline performance on clinical knowledge and reasoning tasks is similar to that of larger models, Google states.</p><p>MedGemma follows on the heels of Google’s Articulate Medical Intelligence Explorer (AMIE) launch last year. AMIE is a research AI system based on a large language model that is optimized for diagnostic reasoning and conversations. Google says it trained and evaluated AMIE along many dimensions that reflect quality in real-world clinical conversations from the perspective of both clinicians and patients.</p><p>To scale AMIE across a multitude of disease conditions, specialties and scenarios, Google developed a self-play-based simulated diagnostic dialog environment with automated feedback mechanisms to enrich and accelerate its learning process.</p><h3>Takeaway</h3><p>Speeding development of medical AI programs is important, but experts note that users must remain diligent in testing programs for the possibility of errors, privacy breaches, biases in decision-making and potential replacement of human judgment.</p><h2>An AI operating system to enhance efficiency</h2><p>Google outlined how its Search with <a href="https://blog.google/products/search/ai-mode-search/" target="_blank" title="Google: Expanding AI Overviews and introducing AI Mode">AI Mode</a> powered by Gemini 2.5 (an experimental tool at this point) could help health care organizations improve operational efficiency, improve the patient experience and support better clinical outcomes. A <a href="https://medium.com/@rstechcreations2020/gemini-2-5-pro-vs-complex-clinical-notes-you-wont-believe-how-well-it-did-978c21c2e75f" target="_blank" title="Medium: Gemini 2.5 Pro vs Complex Clinical Notes: You Won’t BELIEVE How Well It Did!">new report</a> shows one health care AI expert’s experiments with Gemini 2.5.</p><p>The AI Mode rollout to all U.S. users employs Gemini 2.5’s advanced reasoning, multimodal capabilities and contextual understanding to handle complex, longer queries (two to three times longer than traditional searches) and ask follow-up questions. It provides conversational answers rather than traditional link-based results.</p><p>Google’s Deep Search, meanwhile, breaks down queries, performs web exploration, iteratively browses and synthesizes information into structured responses or reports. AI Mode incorporates Deep Search, which analyzes hundreds of sources in real time to generate comprehensive research reports, enhancing its utility for in-depth queries.</p><h3>Takeaway</h3><p>Potential use cases include image classification, clinical reports, summarization, triage and medical Q&A. The models are for research, not clinical use, requiring developers to validate and adapt them before deployment. Google states that health care users can use Deep Search to assist physicians in summarizing a patient’s medical history across multiple providers, analyzing lab results and other tests, while generating a comprehensive overview to support decision-making.</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; } h2 { color: #9d2235; } h3 { color: #9d2235; } Tue, 03 Jun 2025 06:15:00 -0500 Artificial Intelligence (AI) /news/headline/2025-05-28-agencies-release-guidance-ai-data-security <p>The National Security Agency, Cybersecurity and Infrastructure Security Agency and international partners May 22 released <a href="/system/files/media/file/2025/05/joint-cybersecurity-information-tlp-clear-ai-data-security-may-2025.pdf">guidance</a> on securing data used for artificial intelligence and machine learning systems. The guidance outlines potential risks from data integrity issues in various stages of AI development and usage, and it provides best practices to secure AI-based system data. Additionally, the guidance examines three significant areas of data security risks in AI systems — the data supply chain, maliciously modified or “poisoned” data and data drift.  <br><br>“This crucial reference guide, compiled by the world’s leading government AI experts, is a must-read for health care leaders involved in the governance, development or deployment of AI systems in their organizations,” said John Riggi, AHA national advisor for cybersecurity and risk. “The guide discusses specific methodologies to help ensure data security and integrity throughout the AI system lifecycle. These include starting with sourcing reliable data sets and employing immutability and encryption tools, along with digital signatures, to validate and record any trusted changes to AI systems and data.” <br> <br>For more information on this or other cyber and risk issues, contact Riggi at <a href="mailto: jriggi@aha.org">jriggi@aha.org</a>. For the latest cyber and risk resources and threat intelligence, visit <a href="/cybersecurity">aha.org/cybersecurity</a>.</p> Wed, 28 May 2025 16:02:02 -0500 Artificial Intelligence (AI) /aha-center-health-innovation-market-scan/2025-05-27-digital-health-funding-surges-q1-ai-leading-way <div class="container"><div class="row"><div class="col-md-8"><img src="/sites/default/files/inline-images/Digital-Health-Funding-Surges-in-Q1-with-AI-Leading-the-Way.png" data-entity-uuid="734cd6d5-6942-4131-9c5b-726f64e0d487" data-entity-type="file" alt="Digital Health Funding Surges in Q1, with AI Leading the Way. The hand of a venture capitalist inserts funding into a AI hospitals building." width="1200" height="751"><p>Digital health funding, particularly in artificial intelligence (AI) companies, surged 47% in Q1 over the previous quarter, even as deal volume slipped 9%, according to a recent <a href="https://www.cbinsights.com/research/report/ai-trends-q1-2025/" target="_blank" title="CB Insights: State of AI Q1’25 Report">CB Insights report</a>.</p><p>This underscores a broader venture capital trend: Investors are making fewer bets but writing larger checks.</p><p>Investments reached the highest level since mid-2022 despite contraction in contract deal volume. The divergence can be attributed to a more selective funding environment, with capital concentrating around established companies, particularly those leveraging AI for specialized health care applications, the report explains.</p><h2>3 Takeaways from the Report</h2><h3><span>1</span> <span>|</span> Megarounds are back, and AI is claiming most of them.</h3><p>Funding from megarounds ($100 million-plus deals) rose to $2.5 billion across 11 deals in Q1, capturing 46% of all digital health funding. AI-focused startups secured eight of the 11 megarounds, signaling where investors expect outsized returns.</p><h3><span>2</span> <span>|</span> AI companies are capturing more than half of digital health funding.</h3><p>AI startups raised $3.2 billion in Q1, or 60% of all digital funding, the report states — up from 41% in 2024. Top-funded segments included AI-derived small molecule drug discovery and clinical documentation tools, underscoring the shift toward targeted, high-impact applications.</p><h3><span>3</span> <span>|</span> Unicorn creation rebounds, driven by AI-native platforms.</h3><p>Digital health saw six new unicorns in Q1 (companies with more than $1 billion in value) — more than in all of 2024. With half of these investments focused on AI related to provider workflows, the data suggest that investor conviction is highest where AI directly supports care delivery.</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; } h2 { color: #9d2235; } Tue, 27 May 2025 06:00:00 -0500 Artificial Intelligence (AI) /education-events/ai-enhanced-health-care-operations-strategic-imperative <p><strong>AI-Enhanced Health Care Operations: A Strategic Imperative </strong><br><em>Using AI in the Claims Denial Process to Detect, Correct and Resubmit Denied Claims </em> </p><p><strong>Thursday, July 10, 2025 </strong> <br><em>1 - 2 p.m. Eastern; noon - 1 p.m. Central; 10 - 11 a.m. Pacific  </em></p><p>In this webinar, hospital leaders will discover how AI technology is transforming manual operations through intelligent automation.  </p><p>We’ll explore how health care organizations can use AI to automate denied claims appeals, significantly reducing the manual burden on health care staff. Attendees will learn implementation strategies that free up valuable workforce resources, improve operational efficiency and increase denied claims reimbursement.    </p><p>With staffing shortages impacting hospitals nationwide, health care organizations must find innovative ways to maximize their existing workforce’s productivity while maintaining quality care.    </p><p><strong>Attendees Will Learn:</strong></p><ul><li>How to evaluate AI solutions based on their true integration capabilities and implementation requirements, not their theoretical benefits.  </li><li>The “Invisible Integration” methodology that allows AI to operate within existing workflows without disrupting staff routines or requiring extensive training.  </li><li>Practical strategies for implementing AI automation with manageable IT resource investment and rapid time-to-value (typically 30-45 days).  </li><li>Key technical considerations for seamless system integration, including EHR connectivity, security measures and maintaining data integrity (including on-premises vs. cloud).  </li><li>How to overcome common implementation barriers and address staff skepticism about AI.  </li></ul><p><strong>Speaker(s):</strong></p><p>Glen Pendley <br><em>President </em><br><strong>Ailevate </strong></p> Thu, 22 May 2025 12:07:38 -0500 Artificial Intelligence (AI) /news/headline/2025-05-16-agencies-collaborate-pharmaceutical-manufacturing-projects-using-ai <p>The Administration for Strategic Preparedness and Response May 15 <a href="https://aspr.hhs.gov/newsroom/Pages/NewsRoomHome.aspx" target="_blank">announced</a> it is launching four pharmaceutical manufacturing projects using artificial intelligence and other technologies in collaboration with the Department of Health and Human Services, the Defense Advanced Research Projects Agency and private sector organizations. The program, called “Equip-A-Pharma,” will address U.S.-based manufacturing of eight sterile injectable or oral drugs and the pharmaceutical ingredients for those medicines.   </p><p>Private sector partners conducting the projects are Battelle Memorial Institute and Aprecia, BrightPath Laboratories, Rutgers University and the Mark Cuban Cost Plus Drug Company. Each organization is expected to submit abbreviated new drug applications to the Food and Drug Administration within a year. </p> Fri, 16 May 2025 14:57:07 -0500 Artificial Intelligence (AI) /aha-center-health-innovation-market-scan/2025-05-06-4-critical-steps-scale-generative-ai <div class="container"><div class="row"><div class="col-md-8"><img src="/sites/default/files/inline-images/4-Critical-Steps-to-Scale-Generative-AI.png" data-entity-uuid="7ea69c77-70fc-4898-b953-67ac0db1cbd5" data-entity-type="file" alt="4 Critical Steps to Scale Generative AI. A brain that is half generative AI and have biological brain connecting health care data." width="1200" height="751"><p>As health care organizations grapple with rising operational costs, an aging population and a worsening workforce crisis, the need for transformative solutions has never been greater. A new Accenture report, <a href="https://www.accenture.com/content/dam/accenture/final/accenture-com/document-3/AI-Amplified-Scaling-Productivity-Final.pdf" target="_blank" title="Accenture—Gen AI amplified: Scaling productivity for healthcare providers">“Gen AI Amplified: Scaling productivity for health care providers,”</a> highlights how generative artificial intelligence (AI) can offer a critical path forward — unlocking unprecedented productivity gains, enhancing patient care and reshaping the future of care delivery.</p><h2>Health Care’s Inflection Point</h2><p>Health care providers face a historic staffing shortage: By 2033, the U.S. is projected to lack as many as 139,000 physicians while the global nursing shortfall could reach 13 million. Traditional solutions like increased hiring and training alone cannot meet this demand. Providers must embrace innovative technologies to scale human capacity.</p><p>Generative AI presents a powerful opportunity. According to Accenture’s survey of 300 U.S. health care C-suite executives, 83% view boosting employee efficiency as the biggest opportunity of generative AI, and 77% expect it to drive direct revenue growth productivity gains. Early pilots show promise — automating routine tasks, improving data analysis and enhancing decision-making — but widespread adoption remains limited.</p><img src="/sites/default/files/inline-images/Potential-Benefits-of-Generative-AI-in-Health-Care.png" data-entity-uuid="2fbbdc98-8b8d-4810-8e21-52ee7353de18" data-entity-type="file" alt="Potential Benefits of Generative AI in Health Care. 70% of health care workers’ tasks could be reinvented with AI. 20%: Automation could free up 20% of nurses’ repetitive tasks, unlocking $50 billion annually. 9+: Generative AI could help doctors see 9 additional patients per month. Source: Accenture 2025." width="896" height="197"><p>Despite high awareness, a major execution gap exists. While 83% of health care organizations are piloting generative AI, fewer than 10% have invested in the infrastructure needed for enterprise-wide deployment. Without decisive action, health care risks falling behind industries like automotive and finance, where AI-driven gains are already significant.</p><h2>A Road Map for Action</h2><p>The Accenture report outlines four critical steps to help health care leaders move from fragmented pilots to scaled implementation:</p><ol><li><span><strong>Build a reinvention-ready digital core.</strong></span> A robust digital infrastructure — including cloud integration, seamless data access and scalable AI capabilities — is essential. Organizations with a strong digital foundation are poised to reinvent twice as many functions with generative AI over the next three years compared with those without.</li><li><span><strong>Strengthen data quality and strategy.</strong></span> High-quality, centralized data are a prerequisite for reliable AI outcomes. Health care providers must prioritize data cleansing, standardization and accessibility to empower AI to deliver clinical and operational benefits.</li><li><span><strong>Prioritize responsible and secure AI deployment.</strong></span> As the use of generative AI expands, safeguarding patient privacy and preventing cybersecurity breaches are nonnegotiable. Embedding responsible AI governance is critical to building trust among patients, providers and regulators.</li><li><span><strong>Forge strategic partnerships.</strong></span> Scaling generative AI requires expertise beyond internal capabilities. Collaborations with technology leaders, academic institutions and specialized vendors are key to accessing cutting-edge tools and accelerating innovation.</li></ol><h2>The Productivity Promise</h2><p>Accenture estimates that 70% of health care workers' tasks could be reinvented through technology. In nursing alone, automation could free up 20% of repetitive tasks.</p><p>Examples already abound:</p><ul><li>Generative AI can automate clinical documentation, giving physicians back minutes to hours per day — time that can be redirected to patient care.</li><li>Generative AI-augmented call centers have reduced patient wait times and improved first-call resolution rates without compromising security.</li><li>AI-enabled clinical appeals processes have achieved a 70% reduction in handling time and a 30% decline in misrouted claims.</li></ul><p>However, staying in pilot mode comes at a cost. Piecemeal implementations prevent providers from achieving the full operational efficiencies that scaled deployment can offer and widen the gap between health care and faster-moving industries.</p><h2>Leadership Alignment Is Critical</h2><p>A unified C-suite vision is essential. While CEOs recognize the transformative potential of generative AI, clinical leaders like chief medical officers (CMOs) and chief nursing officers (CNOs) are often underutilized in planning and deployment efforts, even though clinical workflows are among the most impacted.</p><p>The report stresses that everyone from board members to front-line clinicians must be involved in redefining roles, automating tasks where appropriate and reskilling teams to work alongside AI tools.</p><p>Key takeaways for health care leaders</p><ul><li><strong>The time to act is now.</strong> Scaling generative AI can drive productivity, reduce burnout and enhance patient care — all while improving financial sustainability.</li><li><strong>Build the foundation.</strong> Investment in cloud infrastructure, high-quality data and responsible AI frameworks are nonnegotiable prerequisites.</li><li><strong>Don’t go it alone.</strong> Strategic partnerships will be critical to closing skill gaps and accelerating deployment.</li><li><strong>Empower clinical leadership.</strong> CNOs and CMOs must play a central role in redesigning work processes to ensure that AI initiatives improve, not burden, care delivery.</li><li><strong>View generative AI as an ongoing journey.</strong> Scaling technology is not a one-time event, but a continuous reinvention of how health care operates.</li></ul><p>Generative AI is no longer a futuristic concept; it’s a present-day imperative. Health care organizations that act decisively today by scaling generative AI strategically and responsibly will define the next decade of health care delivery. Those that hesitate risk being left behind.</p><h3>Additional Resource</h3><p><em>The AHA recently released a report to guide hospital and health system executives on using AI and AI-powered technologies to transform their organizations’ operations. The report, </em><a href="/center/emerging-issues/market-insights/ai/building-and-implementing-artificial-intelligence-action-plan-health-care"><em>“Building and Implementing an Artificial Intelligence Plan for Health Care,”</em></a><em> features insights from 12 health care AI experts and leaders, published health care articles, presentations, reports, research and surveys on health care AI.</em></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; } h2 { color: #9d2235; } h3 { color: #9d2235; } Tue, 06 May 2025 06:15:00 -0500 Artificial Intelligence (AI) /news/headline/2025-05-05-ai-stroke-treatment-expert-insights-henry-ford-health <p>In this conversation, Aaron Lewandowski, M.D., emergency medicine physician and the emergency medicine stroke representative at Henry Ford West Bloomfield Hospital, and Alex Chebl, M.D., interventional neurologist and director of the Henry Ford Stroke Center and the Division of Vascular Neurology at Henry Ford Health, discuss how artificial intelligence is revolutionizing stroke care.<strong> </strong><a href="/advancing-health-podcast/2025-05-05-ai-stroke-treatment-expert-insights-henry-ford-health" title="stroke AI pod"><strong>LISTEN NOW</strong></a><strong> </strong></p> Mon, 05 May 2025 17:25:38 -0500 Artificial Intelligence (AI)