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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">Health Tech | Fierce Healthcare</span></td>
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<td><a href="https://www.fiercehealthcare.com/health-tech/health-tech-weekly-rundown-googleorg-johnson-johnson-foundation-partner-ai-training" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Health Tech Weekly Rundown: $10M initiative for AI training</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Apr 27th 2026, 13:46</div>
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<p><div class="col content" morss_own_score="5.870794078061911" morss_score="83.29130689857473">
<p>Stay up-to-date on the latest in health tech, digital health and health AI news with this weekly brief. This is news from the weeks of April 6-24.</p>
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<h3><strong>H1 launches first AI-powered platform to connect sponsors, sites in clinical trials</strong></h3>
<p>Artificial intelligence platform H1 launched the H1 Site Network Suite, in what it says is the “first-of-its-kind” platform connecting sponsors and sites for seamless clinical trial workflow. </p>
<p>Through the platform, sites can claim and manage profiles, validate capabilities and respond to feasibility questionnaires. The company said the platform deploys AI “across the full feasibility workflow, connecting protocol design, site identification, and feasibility execution.”</p>
<p>“For decades, feasibility has been a fragmented, one-off process built on incomplete data and manual workflows,” said Ariel Katz, H1 CEO and co-founder, in a statement. “With H1’s Site Network, we’re bringing sponsors and sites into one single, connected system where feasibility becomes faster and continuously improves over time. At the end of the day, this means sponsors can move quickly when it comes to feasibility and institute smarter clinical trial processes.”</p>
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<h3><strong>Health systems focusing on ROI, AI integration: McKinsey survey</strong></h3>
<p>Half of U.S. healthcare organizations have implemented generative AI solutions into their workflows, and the focus has shifted to integration, agentic AI tools and return on investment (ROI), an April 16 <a href="https://www.mckinsey.com/industries/healthcare/our-insights/generative-ai-in-healthcare-current-trends-and-future-outlook#/">report</a> from McKinsey & Company found.</p>
<p>The report surveyed healthcare leaders online from mid-September to mid-October and included leaders from 50 payers, 50 clinical care organizations and 50 health services and technology (HST) firms. </p>
<p>“At the same time, the challenges that healthcare leaders face are evolving,” the report authors wrote. “Longstanding concerns around trust, safety, and governance now sit alongside the operational realities of integration.” </p>
<p>Most healthcare leaders included in the report expect a positive ROI (82%) on AI investments, with 45% quantifying a positive return. </p>
<p>The biggest barrier for healthcare leaders attempting to scale generative AI solutions is difficulty integrating or adapting tools to existing workflows, with 59% of respondents reporting the issue. Forty-three percent of healthcare leaders also cite the concerns of the risk of scaling generative AI solutions as a barrier to implementation.</p>
<p>The survey also found despite increasing interest in agentic AI platforms, implementation is lagging behind generative AI tools. Only 19% of respondents report their organizations have implemented agentic AI, but, simultaneously, 51% of respondents report their organizations are pursuing agentic AI proofs of concept. Only 1% of respondents said their organizations have no plans to pursue agentic AI solutions.</p>
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<h3><strong>Google and Johnson & Johnson Foundation invest in AI training</strong></h3>
<p>Google.org and the Johnson & Johnson Foundation <a href="https://blog.google/company-news/outreach-and-initiatives/google-org/ai-training-rural-health-clinics/">announced</a> a $10 million philanthropic collaboration to fund AI literacy training for rural healthcare workers across the U.S., aiming to bridge the adoption gap. </p>
<p>Each organization is committing $5 million to the project, according to a press release. There are three main pillars of the partnership:</p>
<ul><li>AI literacy</li><li>Burnout reduction</li><li>Community-driven solutions</li></ul>
<p>The collaboration expands on different initiatives from each organization. Google.org’s AI Opportunity Fund, <a href="https://publicpolicy.google/article/AI-opportunity-fund/">launched</a> in 2024, aims to help Americans develop AI skills. And, Johnson & Johnson’s <a href="https://www.jnj.com/j-j-care-community">CareCommunity</a> aims to advance programs that improve quality care access for communities across the globe.</p>
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<h3><strong>Qualifacts acquires MethodOne to fully integrate medication-assisted treatment</strong></h3>
<p>Behavioral health technology platform Qualifacts <a href="https://www.qualifacts.com/resources/qualifacts-acquires-methodone/">acquired</a> MethodOne by Computalogic, a controlled-medication dispensing software, to create a fully integrated solution. </p>
<p>The acquisition expands Qualifacts electronic health record (EHR) capabilities, “closing a critical gap” for substance use disorder and complex mental health providers that required integrated medication-assisted treatment and medications for opioid use disorder dispensing. </p>
<p>“Joining Qualifacts gives MethodOne the scale and resources to accelerate our roadmap and reach more providers who need a better solution,” said Keith Jones, CEO of MethodOne by Computalogic, in a statement. “Together, we can offer SUD treatment organizations something they haven’t had before: a truly integrated solution that handles the full scope of their clinical and dispensing needs, backed by a partner with deep and exclusive behavioral healthcare expertise</p>
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<td><a href="https://www.fiercehealthcare.com/ai-and-machine-learning/unityai-builds-out-agentic-ai-staffing-operations-keep-pace-patient-demand" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">UnityAI builds out agentic AI for staffing and labor operations</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Apr 27th 2026, 13:46</div>
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<p>Nashville-based health tech startup UnityAI built out an agentic AI platform to streamline day-to-day staff scheduling and match it in real-time with patient demand.</p>
<p>The healthcare staffing and labor management platform, called StaffOps, is already live in about 120 sites of care, supporting workforce scheduling across a growing network of clinical organizations. The startup's AI agent connects workforce scheduling with electronic health record data to reduce cancellations, improve throughput and optimize labor utilization, executives said.</p>
<p>The platform enables healthcare teams to adjust staffing and labor based on live appointment data, cancellations and overall patient flow, according to the company.</p>
<p>UnityAI first developed specialized agents to help staff with patient scheduling, appointment confirmation, intake and follow-up. Its voice AI technology was designed to support healthcare staff in outpatient clinics to answer incoming calls and proactively engage with patients. </p>
<p>The startup, founded in 2023, is strategically focused on healthcare operations, noted Edmund Jackson, co-founder and CEO.</p>
<p>"What we're trying to do is create excellent schedules, that's our North Star. Our belief is that what providers bring to the market is time for a patient in a place with a clinician, and, if you get that right, everything else happens," Jackson said in an interview with Fierce Healthcare, giving a first look at the StaffOps platform. "The first evolution so far has been using agents on the supply side of that, getting patients on the schedule where they should be. But that's only half the problem. The other half is the clinicians. How do you do staffing? So not just clinicians, but clinical techs, other staff members. How do you get them in the right place at the right time to meet the patient demand? How do you match it?"</p>
<p>Jackson asserted that patient access and patient experience need to be matched with staffing operations, not addressed as separate functions.</p>
<p>Currently, most providers staff their healthcare workforce based on a fixed schedule with static shifts that are planned in advance, but that doesn't keep pace with the realities of patient demand, which changes by the day, and even the hour. Providers frequently deal with cancellations and mismatched staffing, with overworked clinicians in some areas, and underutilized capacity in others.</p>
<p>UnityAI's StaffOps integrates directly with the EHR and human resources systems, giving managers a real-time view of patient appointments, including cancellations and reschedules. Organizations can align staffing levels to actual patient demand rather than static schedules. By continuously syncing workforce supply with patient volume, StaffOps enables a more dynamic staffing model that improves patient throughput while reducing unnecessary labor spend, executives said.</p>
<p>"The platform figures out who are the roster of staff, what are their credentials, where can they work? Where can't they work? What are their preferences for language? What's their experience. What patients are coming in, when and where? It'll optimize a schedule and say, this is the mathematical optimal given these constraints," Jackson said. "Clinic providers can manage all the exceptions to that, move patients around, deal with PTOs, call-on, call-off shift trades. What's really important is that it has a broad view as most of our clients are multi-site, so we're not just managing one clinic."</p>
<p>StaffOps provides a unified, self-service platform for both frontline staff and site leaders. For healthcare practitioners, the platform simplifies day-to-day scheduling. Clinicians and staff can request shifts, release shifts they cannot work and submit PTO requests through a single interface, eliminating the back-and-forth that often slows down staffing coordination. For staffing managers and site leaders, the StaffOps platform is designed to improve visibility and responsiveness, executives said, making it faster to identify and fill coverage gaps caused by PTO or last-minute call-offs, helping reduce patient appointment cancellations and maintain continuity of care.</p>
<p>UnityAI's work to apply agentic AI to healthcare workforce operations marks a broader shift where AI isn’t just helping with documentation or analytics, but is also starting to coordinate actual work inside provider organizations, Jackson noted.</p>
<p>The vision, Jackson said, is to expand AI agents beyond scheduling into labor optimization and autonomous workforce operations for all staff in a clinic. The AI agents will be able to handle both sides of the operation--supply and demand.</p>
<p>"That operation consumes so much mental bandwidth and time and energy, so lifting that friction from [site managers] creates time in their day to take care of the patients that are actually in the clinic," he said.</p>
<p>The company is developing AI agents that can manage routine staffing decisions in real time via voice and SMS text, including processing call-offs, coordinating shift swaps, approving PTO requests and adjusting coverage based on patient demand. The aim is to coordinate patient appointment adjustments, helping organizations proactively manage access changes rather than reacting after the fact, according to the company.</p>
<p>UnityAI was formed by three former HCA Healthcare engineers and data scientist executives, including Jackson who served as chief data scientist and chief data officer at the health system. UnityAI initially focused on scaling up its care orchestration technology to improve patient flow in a hospital setting. The startup shifted its focus to multi-site outpatient providers and works with radiology, dental, behavioral, substance abuse, primary care and other providers.</p>
<p>"We decided we needed to move faster, to find clients where we could apply AI for operations at a higher metabolic rate. What we found was that these multi-site outpatient providers are very well organized, they're looking to move faster and they care about operations very, very deeply," Jackson said.</p>
<p>UnityAI raised $8.5 million in a series A round back in March to fuel its work to develop an autonomous AI workforce across all healthcare operations.</p>
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<td><a href="https://www.fiercehealthcare.com/ai-and-machine-learning/ama-urges-lawmakers-implement-stronger-safeguards-ai-chatbots-mental-health" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">AMA urges Congress to create stronger AI chatbot safeguards</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Apr 27th 2026, 13:46</div>
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<p><div class="col content" morss_own_score="5.196029776674939" morss_score="31.26948177366093">
<p>The American Medical Association (AMA) <a href="https://www.ama-assn.org/press-center/ama-press-releases/ama-urges-congress-strengthen-safeguards-ai-chatbots">urged</a> federal lawmakers Thursday to strengthen safeguards towards artificial intelligence chatbots as use increases for mental health. </p>
<p>The organization penned letters to the co-chairs of the Congressional Artificial Intelligence Caucus (<a href="https://searchlf.ama-assn.org/letter/documentDownload?uri=/unstructured/binary/letter/LETTERS/lfi.zip/2026-4-22-Letter-to-McCaul-Obernolte-Matsui-and-Beyer-re-Mental-Health-Chatbots.pdf">PDF</a>), the Congressional Digital Health Caucus (<a href="https://searchlf.ama-assn.org/letter/documentDownload?uri=/unstructured/binary/letter/LETTERS/lfi.zip/2026-4-22-Letter-to-Balderson-and-Kelly-re-Mental-Health-Chatbots.pdf">PDF</a>) and the Senate Artificial Intelligence Caucus (<a href="https://searchlf.ama-assn.org/letter/documentDownload?uri=/unstructured/binary/letter/LETTERS/lfi.zip/2026-4-22-Letter-to-Rounds-and-Heinrich-re-Mental-Health-Chatbots.pdf">PDF</a>). While the organization recognized lawmakers efforts towards “advancing conversations about AI’s role in society and mental health,” it said the rise of mental health chatbots, including reports of encouraging self-harm and privacy breaches, “highlights the urgent need for clear guardrails.”</p>
<p>Safeguards recommended by the AMA include: </p>
<ul><li>Enforce transparency standards and penalize deceptive practices, including systems presenting themselves as licensed clinicians</li><li>Create a modern, risk-based oversight framework and clarify when AI tools qualify as medical devices</li><li>Mandate ongoing safety monitoring and adverse event reporting </li><li>Require strict data protection standards</li></ul>
<p>The AMA uses the term “<a href="https://www.ama-assn.org/practice-management/digital-health/augmented-intelligence-medicine?check_logged_in=1">augmented intelligence</a>” when referring to AI to emphasize the technology's assistive role in medicine. </p>
<p>“AI-enabled tools may help expand access to mental health resources and support innovation in health care delivery, but they lack consistent safeguards against serious risks, including emotional dependency, misinformation, and inadequate crisis response,” said John Whyte, M.D., AMA CEO, in a <a href="https://www.ama-assn.org/press-center/ama-press-releases/ama-urges-congress-strengthen-safeguards-ai-chatbots">statement</a>. “With thoughtful oversight and accountability, policymakers can support innovation and ensure technologies prioritize patient safety, strengthen public trust, and responsibly complement—not replace—clinical care.”</p>
<p>A March Rock Health survey <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/ai-chatbot-use-health-information-16-2024-rock-health-survey">found</a> 32% of respondents use AI chatbots to seek out health information, with 28% of AI users reporting that they turn to chatbots to help manage mental health or stress. Despite the increasing reliance, Mass General Brigham researchers <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/gen-ai-chatbots-continually-struggle-differential-diagnoses-mass-general">found</a> publicly available generative AI models often fail to properly navigate diagnostic situations. </p>
<p>While all 21 large language models (LLMs) analyzed in the study achieved a correct final diagnosis more than 90% of the time, all models failed to produce an appropriate differential diagnosis more than 80% of the time, which researchers say emphasize AI models should “augment—not replace—physician reasoning.” </p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
<p><strong>This information is taken from free public RSS feeds published by each organization for the purpose of public distribution. Readers are linked back to the article content on each organization's website. This email is an unaffiliated unofficial redistribution of this freely provided content from the publishers. </strong></p>
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