The Rise of Agentic AI: Transforming Healthcare Workflows
A Leap Beyond Traditional AI
Recent advancements in artificial intelligence (AI) are pivoting from conventional machine learning models focused solely on data analysis to more autonomous systems that can act upon data with minimal human involvement. A prime example of this shift is agentic AI, also referred to as autonomous agents, which enhances general generative AI capabilities by making independent decisions aimed at specific goals. This development represents a fundamental change in how technology interacts with clinical, administrative, and patient-facing workflows.
The Growing Emphasis on Agentic AI at HIMSS25
The HIMSS25 conference showcased agentic AI as a prominent theme, whether on the exhibition floor or in keynote addresses. One key takeaway was the recognition that while leveraging this technology for operational improvement is crucial, navigating the complexities of integrating autonomous AI into clinical care poses serious challenges. Finding the balance between operational efficiency and patient safety remains a pressing issue.
AI Agents: Supporting Physicians, Not Replacing Them
AI agents serve as valuable tools for healthcare professionals, designed to help meet the increasing demand for care. While they can accelerate and automate routine tasks, they are not intended to replace the critical decision-making role of physicians. As healthcare organizations consider employing agentic AI to manage complex workflows, such as staffing optimization, they must tread carefully in sensitive areas like clinical decision-making.
Navigating Health AI Governance and Policy
In January, Bill H.R. 238 was introduced to the House Committee on Energy and Commerce, proposing amendments to the Federal Food, Drug, and Cosmetic Act. This bill aims to enable AI and machine learning systems authorized by the FDA to be classified as practitioners eligible to prescribe medications. However, concerns exist among EHR (Electronic Health Records) developers about the readiness of autonomous AI for such responsibilities.
Building Trust in Autonomous AI
Experts emphasize that transparency and trust are crucial for the successful adoption of autonomous AI in healthcare systems. At HIMSS25, Dennis Chornenky from UC Davis Health noted that existing healthcare regulations are not designed for autonomous decision-making, posing risks of biased decisions that could potentially compromise patient safety. A lack of established governance mechanisms only amplifies these concerns.
The Role of Agentic AI in Patient Follow-Up
One of the primary goals of implementing agentic AI in healthcare organizations is to reduce the admin burden on clinicians and staff. Companies like Epic are leading the charge by integrating AI into various applications, positioning agents to enhance clinical efficiency. For example, AI agents are expected to facilitate pre-visit preparations by interacting with patients, identifying necessary tasks, and creating concise summaries of needed actions.
Real-World Applications of Agentic AI
During HIMSS25, Garrett Adams from Epic introduced an innovative post-surgical patient assistant agent. This AI system engages with patients through conversation, asking for recovery updates and even requesting images or videos of their surgical site. By leveraging its database, it can suggest whether a follow-up appointment is still necessary based on patient recovery trends—an impressive amalgamation of technology and patient care.
Ensuring Human Oversight in AI Interactions
Despite the autonomy offered by these AI systems, human oversight remains fundamental. The post-surgical assistant can propose appointment cancellations but ultimately routes the request to the care team for confirmation. This system ensures that care is prioritized and human judgment isn’t entirely sidelined.
Automating Clinical Workflows with Caution
Companies like InterSystems are emphasizing caution as they introduce AI components like IntelliCare, which streamlines administrative tasks. While this AI assistant efficiently summarizes patient histories and aids billing processes, there remains a hesitance to use agentic AI in direct clinical decisions. The expectation is to allow AI to handle more mundane tasks while giving healthcare professionals the freedom to focus on critical patient interactions.
The Dialogue on Governance Continues
In conversations after HIMSS25, discussions highlighting the pros and cons of agentic AI surfaced. Stakeholders raised important questions regarding the balance of clinical oversight when AI begins to automate more nuanced tasks, like developing diagnostic lists or managing prescriptions. While future applications seem promising, the industry must prioritize governance to ensure patient safety.
Advantages of Agentic AI in Revenue Cycle Management
The progressive capabilities of healthcare AI now allow it to autonomously navigate complex Revenue Cycle Management (RCM) tasks. As these systems evolve, AI can manage interactions with payers and handle non-linear processes, offering much-needed relief in administrative burdens.
A New Era of Efficiency
Leaders in healthcare technology are witnessing incredible productivity gains through the implementation of agentic AI. Girish Navani of eClinicalWorks cited instances where AI agents could handle work typically assigned to multiple employees. This suggests an exciting future where staff can redirect their focus to more value-driven work, maximizing the efficiency of healthcare systems.
Practical Applications of AI in the Field
eClinicalWorks recently showcased its AI document intelligence tool, which accurately processes incoming patient data across various formats. This tool exemplifies how AI can enhance accuracy while reducing time spent on administrative tasks, alongside the healow Genie—a virtual agent designed to provide 24/7 patient support for common inquiries.
Gradual Integration in Key Workflows
Athenahealth’s gradual implementation of AI features emphasizes the importance of maintaining human oversight within clinical workflows. The company focuses on using AI to relieve providers of repetitive tasks, enabling them to concentrate on applying their medical expertise more effectively.
The Path Forward: Caution and Innovation
As healthcare continues to embrace agentic AI, there remains a strong call for caution. The balance of leveraging autonomous technology while ensuring effective governance is essential to maximizing benefits in clinical care. Conversations surrounding the capabilities of AI agents will remain critical as the sector adapts to these sweeping changes.
Conclusion: Embracing Change with Care
In conclusion, the rise of agentic AI represents a transformative leap in healthcare technology. While the potential for enhancing efficiency and reducing workload is significant, the onus is on healthcare organizations to integrate these technologies thoughtfully. Striking the right balance between innovation and oversight will be paramount in shaping the future of clinical care.
