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Newsweek
02-05-2025
- Health
- Newsweek
AI Agents Are Hospitals' Newest 'Employees.' We Called Their References.
Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources. There's a new type of AI bot on the block—and this time, it's completely autonomous. AI agents are steadily making their way into the public consciousness as more companies release them. Last year, generative AI was all the rage, producing ambient scribes that could transcribe a conversation into clinical notes and in-box bots that could draft responses to patients' MyChart messages. This year, however, the spotlight has shifted to agentic AI, which can initiate a task and complete it—start to finish—without human intervention or oversight. It's widely considered that this technology could change the way health care organizations function. Earlier iterations of AI could make humans' work easier, more efficient or more accurate, but AI agents can work independently of us. While generative AI can answer your questions, agentic AI can pose its own and even reason through them. AI agents were a hot topic at the Healthcare Information and Management Systems Society (HIMSS) conference in early March, and the buzz has only grown since then. On April 23, Nvidia launched a new platform to help companies build AI agents, which it calls "AI teammates." The company estimates that the agentic AI market is worth $1 trillion, according to The Wall Street Journal. Other projections anticipate rapid market growth, from $7.8 billion in 2025 to $56.2 billion in 2030. Health systems are deploying agentic AI models across multiple departments, including the revenue cycle and the patient exam room. Health systems are deploying agentic AI models across multiple departments, including the revenue cycle and the patient exam room. Photo-illustration by Newsweek/Getty But health systems have taken a more cautious approach to AI than their counterparts in business and tech. Although many health care organizations are experimenting with AI, only 30 percent of their pilots and proof-of-concept projects make it to the development phase, according to a recent report from Bessemer Venture Partners, Amazon Web Services and Bain & Company. As agentic AI introduces even more capabilities and risks, it can further complicate the gradual rollouts underway at health care organizations: so Newsweek connected with 10 agentic AI developers to learn exactly what leaders can expect from the technology. How are health systems using agentic AI? AI agents have been deployed in various departments across hospitals and health systems, from the revenue cycle to the clinical decision-making process. They're yielding strong results—according to the technology companies that create them and the researchers who are examining them. Cedar, a patient financial platform for health care providers, launched an AI voice agent on April 29 to automate patient billing calls. Two days later, Zocdoc announced an agent to automate scheduling calls. Both companies said that their agents could speak conversationally and answer phones 24/7, freeing up operators to focus on more complex requests. Care providers are also using agentic AI. Google Cloud collaborated with more than 50 health care providers at Seattle Children's to develop Pathway Assistant, an AI agent that can synthesize information from clinical standard pathways. The tool is expected to increase compliance with standard care processes and make it easier for physicians to access the information they need, the companies said. It would take 15 minutes for a physician to conduct this search manually, but the agent can do it in seconds. AI agents are improving system-level efficiency too. Take for example: It is designed to orchestrate the chaotic reality of hospital operations by continuously gathering, reasoning through and acting on real-time data. The platform starts by graphing a comprehensive map of how patients, staff and clinical spaces interrelate, using live feeds from electronic health records, staffing schedules and inventory management systems (supplemented by Bluetooth technology). This allows it to predict problems, like equipment shortages or staffing bottlenecks, and initiate efforts to prevent them. uses a team of AI agents, each assigned a narrow task to focus on constantly. While one agent monitors the availability of clean equipment, another might keep watch over a predictive model that calculates future equipment demands. When the robot squad senses trouble, it will ping another agent to call the biomedical department and relay the message to a human coordinator: for example, "We need to move six pumps to the ICU in the next 45 minutes, and there are five broken pumps in the cardio unit. Maybe you should go take care of the broken pumps, then grab another from room one and take them to the ICU." Since AI agents can converse, the human coordinator can respond with questions about the inventory or tell the agent that they're busy and should call back later. The agentic team is constantly triaging issues to flag the most pertinent problems first, based on both real-time data and the predictive model's concerns. Historically, humans have made these small decisions themselves, but they didn't have the time or bandwidth to coordinate with one another, Rom Eizenberg, chief revenue officer, told Newsweek. Agentic AI can serve as the middleman, eliminating guesswork that causes accidental clogs. "It's a jungle out there," Eizenberg said. "The 1,400 vendors, the unstructured data, the siloed behavior, the millions of phone calls to make everything work: that's the root cause for all the evils in health care." Can AI agents make call centers more efficient? Communication is a major hiccup in the health care industry; as of 2019, 70 percent of health care providers still used fax machines. Patients, providers, payers and pharmacies frequently swap info by phone (to all parties' dismay). About half of patients are satisfied with the service at their health care provider's call center, according to a 2023 survey of 200 senior leaders. The average hold time at these organizations was 4.4 minutes, well above the HFMA's recommendation of 50 seconds. When patients can't reach their health care providers, they may seek instant answers elsewhere: turning to social media and search engines, which are rife with misinformation. "I wish I had thousands of doctors that could do every single phone call to every patient, every outreach, every follow-up," Dr. Jackie Gerhart, a family medicine physician and the chief medical officer and vice president of clinical informatics at Epic, told Newsweek. AI agents can help fill the gap: calling patients to check in after missed appointments, scheduling upcoming labs and even talking through top concerns so a patient's doctor can prepare for their visit before they enter the exam room. AI agents can also handle the back-office phone calls, which present their own pricey challenges. During Medicare Advantage reverification season—from January 1 to March 31—health care organizations staff seasonal workers to handle heightened call volumes as they confirm patients' insurance plans. Enter machines, which have a higher tolerance for hold music than the average human being. Tech company Infinitus deploys AI agents to help alleviate the pressure on health care call centers, especially during busy seasons. Last year, the company's AI agents spent more than 1.4 million minutes waiting on hold, CEO Ankit Jain told Newsweek. This January alone, they spent more than 2 million minutes navigating interactive voice response systems (the more archaic version of a robotic call assistant, known for asking callers to "press one if you are an existing patient, press two if you are a pharmacist, press three if ..."). Agentic AI is far savvier, according to Jain and other solutions developers. While researching for this article, Newsweek's health care editor spoke with two AI agents and did not feel inclined to yell, "I need to speak to a representative!" "The conversational AI voice platform that we have built is extremely natural, extremely conversational, and it's akin to the ones that you would have if a human picked up right away," Jain said. Does agentic AI hallucinate? If agentic AI is going to be carrying conversations and informing doctor's decisions, it needs to meet the same standards as a call center representative or a board-certified physician. Although numerous studies have examined generative AI for hallucination, there isn't extensive data on agentic AI. On April 24, Infinitus launched AI agents that it "guarantees" are hallucination-free. Newsweek asked the company's technology lead, Shyam Rajagopalan, how he could be sure. The company's AI agents are confined to hyper-specific sets of data, according to Rajagopalan. For example, if it's calling to verify a patient's information, it will access that individual patient's information—not information from every patient within the health care system. "Because I've constrained the space to only be relevant for this particular patient, [the agent] will never be able to tell you a different patient's birthday or a different patient's diagnosis," he said. Color Health—a health tech company focused on cancer care solutions—is also working to reduce AI hallucinations by using agentic models. It developed a "large language expert" that merges the strengths of an LLM with the structure of an expert system. Unlike traditional LLMs, which can invent plausible-sounding (but incorrect) outputs when faced with ambiguity, the LLE forces reasoning through structured clinical decision factors (the individual yes/no questions that an AI system parses from clinical guidelines) and Boolean formulas (the strict rules for combining the answers to those yes/no questions into a final recommendation). Since the LLM's role is limited to answering specific questions rather than generating broad narratives, errors are easier for the model to catch and correct, according to a recent study from the company. "Agentic AI goes beyond generative AI with the proactive performance of tasks," Othman Laraki, CEO of Color Health, told Newsweek. "While generative AI creates content by learning from different data sources and patterns, agentic AI is an autonomous, decision-making technology that takes action based upon its learnings." Is agentic AI going to replace generative AI? The future will include both generative and agentic AI, according to Gerhart and her colleague Sean McGunigal, Epic's director of AI. "There are going to be cases where the simpler forms of AI make sense, especially if we look at it from a compute-saving or cost-saving perspective," McGunigal told Newsweek. "If we don't need the heavier firepower of an agent, we won't go that route—but I think you will see more and more automation in the form of agents." We shouldn't think of agentic AI as an evolution of generative AI, per Eizenberg. It's something entirely different—not a system upgrade, but a stand-alone invention, set apart by the agents' ability to connect with one another. "An LLM is a transformer, the enabling tool to talk to people or reason or make decisions," Eizenberg said. "But it isn't software architecture. Agentic AI gives us ways to build that we never had before." Is agentic AI going to replace humans? Yes and no. AI agents may cut down on call center staff, but it's unlikely that they'll ever stand in as your doctor. Three health system and AI researchers—including Dr. Eric Topol of the Scripps Research Translational Institute—explored the question in an April comment for the academic journal Nature Biomedical Engineering. "As AI continues to advance, physician-independent workflows are likely to emerge in certain areas of health care," the authors said. "These workflows may be driven primarily by collaborations between clinical and operational AI agents and may streamline processes, optimize resource utilization and improve patient outcomes." But these physician-independent workflows "will not be suitable" for other areas of health care, such as complex cases and rare diseases, according to the authors. In these instances, AI agents can still support physicians by offering insights and optimizing workflows. Doctors' roles have evolved as the health care industry has grown more complex. Some physicians, like Gerhart, are optimistic that AI agents could assume some of that work to help provide more thorough, comprehensive patient care. "When I think about what it means to be a doctor in the future, it's not only doing individual workflows and only knowing medical knowledge," Gerhart said. "It's knowing how to manage and give the best care. So I'm hopeful that my team of care coordinators and AI agents can work together to make sure that the patient actually gets everything they need done at the appointment, their population health is taken care of, their family dynamics are considered." "It's really this opportunity to reimagine what medicine can be, and the extent of medicine that you can do, with the new tools that you have."
Yahoo
12-02-2025
- Business
- Yahoo
Remote Patient Monitoring Market To Hit USD 88 Billion By 2030 : Wissen Research
The global remote patient monitoring (RPM) market is estimated to be valued at $40 Billion in 2023, and is expected to grow at a CAGR of ~12% during the forecast period (2024 – 2030) Remote patient monitoring market Sheridan, Feb. 12, 2025 (GLOBE NEWSWIRE) -- The remote patient monitoring market is set to experience remarkable growth, fueled by a rising need for innovative healthcare solutions. As technology continues to advance and the focus shifts to patient-centered care, RPM provides a holistic way to manage chronic diseases and enhance patient outcomes. However, there are also challenges that stakeholders need to address to unlock the market's full potential. @ The RPM market is primarily driven by the rising burden of chronic diseases, which account for 71% of global deaths according to WHO. This is exemplified in diabetes care, where Continuous Glucose Monitors enable real-time blood sugar tracking and remote provider monitoring, leading to improved patient outcomes and reduced healthcare costs through fewer data management systems present a major market opportunity in Remote Patient Monitoring (RPM), with 76% of healthcare organizations reporting improved clinical decisions according to Healthcare Information and Management Systems Society (HIMSS). These systems aggregate data from multiple RPM devices to create comprehensive patient health profiles. The opportunity centers on developing platforms that provide AI-driven insights, automated alerts, and EHR integration. For example, Mayo Clinic's centralized RPM platform reduced cardiac patient readmissions by 40% through real-time data analysis, demonstrating how effective data management can improve outcomes while reducing fraud in Remote Patient Monitoring (RPM) presents a significant market challenge, particularly as the adoption of digital health solutions expands. Fraudulent activities include billing for non-existent patient monitoring sessions, falsifying patient data, and submitting claims for services not rendered. Common schemes involve providers billing for RPM services without proper patient consent, using automated systems to generate false readings, or charging for monitoring periods that exceed actual patient engagement times. Request Sample Report @ In 2023, RPM devices emerged as the dominant segment in the medical device market, primarily driven by the widespread adoption of vital sign monitors, blood glucose monitors, and cardiac monitoring devices. This dominance is attributed to the increasing prevalence of chronic diseases and the growing acceptance of wearable technology among patients. For instance, continuous glucose monitoring devices saw particularly strong growth, with market leader Dexcom reporting a 31% increase in global device shipments in diabetes segment led the Remote Patient Monitoring market in 2023, fueled by rising global diabetes cases (537 million adults in 2021 per IDF) and the need for continuous monitoring. This leadership position was strengthened by widespread adoption of advanced CGM systems and connected insulin pumps enabling real-time data sharing with healthcare patient monitoring serves a number of end-users such as hospitals, home care, ambulatory care centers and others. The traditional healthcare facilities, i.e. hospitals remained the significant holder of user market share due to increase in the adoption rates of RPM devices patient monitoring market research included a comprehensive analysis of five key regions: North America Europe Asia Pacific Middle East and Africa Latin America. Regions were assessed on healthcare infrastructure, regulations, tech adoption, and market dynamics. North America dominated the remote patient monitoring market due to advanced healthcare systems, high adoption rates, and the presence of major industry innovators. As per the historical and the base year of the report (2022 and 2023, respectively), key players in remote patient monitoring were Koninklijke Philips N.V. (Netherlands), Medtronic (Ireland), GE Healthcare (US), Cerner Corporation (US), Siemens Healthineers Ag (Germany), Omron Healthcare (Japan), Boston Scientific Corporation (US), Abbott Laboratories (US), Resideo Life Care Solutions (US), among for Customization @ Latest Reports from Wissen Research Dental Implants & Prosthetics Market Point-of-care Diagnostics Market Lyme Disease Treatment Market In Vitro Diagnostics Market About us: Wissen Research is a leading market research firm that serves over 800 clients, with 40% of the top 2,000 companies relying on us for insights into key business questions and the identification of new high-growth and niche revenue opportunities. In a world marked by constant technological innovation and market disruptions, we assist organizations in planning and operationalizing their future revenue strategies by uncovering numerous growth opportunities. Companies choose Wissen Research to stay ahead of the competition and make informed revenue decisions, leveraging actionable insights and recommendations that give them a unique first-mover advantage. Our research methodology delivers quantifiable and actionable insights into interconnected market ecosystems shaped by disruptive technologies and emerging markets. We not only focus on factors that will impact our clients' revenue but also explore what could affect their customers' revenue by revealing latent and adjacent market opportunities. We collaborate across all B2B sectors, engaging with C-level executives in areas such as R&D, intellectual property, strategy, marketing, sales, product development, and M&A. Wissen Research offers exclusive market intelligence from over 120 subject matter experts and analysts, complemented by our high-growth niche market studies and consulting services. Attachment Remote patient monitoring market CONTACT: Mayur Jain Wissen Research LLC Gould St, Ste R Sheridan, WY 82801 Phone: (+91) 7814300364 info@ in to access your portfolio
