The Good Tech Companies - Modernizing AI Agents for Healthcare: From Documentation to Decision Support

Episode Date: September 17, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/modernizing-ai-agents-for-healthcare-from-documentation-to-decision-support. AI agents are shifting healthcare from paperwork to decision support. Isan Sahoo highlights how they cut burnout, improve care, and build resilient systems. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-healthcare-agents, #isan-sahoo, #healthcare-decision-support, #ai-documentation-tools, #ehr-automation, #ai-in-clinical-workflows, #resilient-healthcare-systems, #good-company, and more. This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com. Healthcare AI agents are evolving from transcription tools into digital teammates. By handling documentation, suggesting care plans, and enhancing engagement, they free clinicians to focus on patients. Isan Sahoo emphasizes transparent, explainable AI to earn trust and highlights resilient cloud systems as key to crisis-ready healthcare.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Modernizing AI agents for healthcare, from documentation to decision support. By John Stoyan journalist. For decades, the healthcare industry has turned to technology with the hope ofusing the administrative burden on clinicians. The promise was simple. Let machines handle the paperwork so doctors and nurses could focus on patients. Theirality has been far more complicated. Electronic health records, EHRs, while essential for storing and sharing patient information, often introduce new challenges. Instead of creating efficiency, EHR systems added layers of complexity.

Clinicians found themselves estethered to screens, navigating endless menus and clicking through rigid workflows. The result. Less time with patients, more time with keyboards, and mounting frustration across the profession. Today, a new class of AI agents is emerging, one that doesn't just record information but actively helps shape care decisions. These intelligent systems represent a turning point in the ongoing struggle to balance operational efficiency with patient-centered care. From burden to breathing room, documentation remains one of healthcare's greatest pain points. Studies consistently show that physicians spend nearly twice as much time updating charts as they do in direct patient interaction.

This imbalance contributes to burnout, dissatisfaction, and even declines in the quality of care. AI agents are beginning to change that equation. With ambient listening systems, a doctor's conversation with a patient can be transcribed, structured, and uploaded into the patient's record in real-time. Allergies, medications, and laborers are flagged automatically. No extra typing, no scrambling after the visit, just a clean, accurate record created seamlessly in the background. Documentation has long been a hidden tax on health care, says Issen Sahu, senior IEEE member and distinguished fellow at the Soft Computing Research Society. AI agents can help reclaim time for clinicians, letting them focus on care rather than keyboards. Beyond documentation, toward digital teammates,

the real innovation isn't just an automating paperwork, it's in transforming Iinto digital teammates. Instead of just recording what happened, agents can start suggesting what should happen, explains Sahu. For example, if a patient presents with diabetes and heart disease, the agent could generate a dynamic care plan, schedule follow-ups, and send medication reminders, keeping the entire care team aligned. This vision reframes AI not as a replacement for human expertise but as a collaborative partner. Nurses may receive daily task lists drawn directly from the care plan. Physicians may see risks flagged in real-time. Patients benefit from timely, personalized prompts. In this model, AI is woven into the workflow, augmenting every role in the care

continuum. Real-world use cases emerging. Across hospitals and research pilots, AI agents are already showing value. Early applications include dynamic care plans, adaptive care goals updated in real time as patient conditions evolve. Pre-surgical follow-ups. Automated reminders for labs or prep steps, reducing last-minute cancellations. Billing and coding, translating clinical notes into accurate claims, cutting administrative overhead, patient engagement, personalized nudges to improve medication adherence, lifestyle changes, and checkups. These examples demonstrate how AI agents can both lighten the workload and directly improve patient outcomes. The road ahead. Promise meets complexity. The potential is enormous, but the path forward isn't without obstacles.

Date interoperability across fragmented systems remains a challenge. Regulatory frameworks are still catching up to eye-driven decision support. And perhaps most importantly, clinician trust must be earned. Transparency and explainability are critical, stresses Sahu. Clinicians must understand why an agent made a suggestion. Otherwise, adoption will stall. Trust doesn't come from flashy features. It comes from clear, explainable recommendations and systems that respect the clinician's judgment. A digital teammate for every clinician. The trajectory of AI in healthcare is clear. from note takers to decision support partners. The ultimate destination isn't a monolithic AI, doctor, but rather a network of specialized,

interoperable agents integrated throughout the healthcare delivery system. As Sahu puts it, greater than, the ultimate goal is simple, give clinicians their time back, give patients greater than more personalized care, and make the healthcare system more resilient. Spotlight on ISN Sahu, the promise of AI agents in healthcare is closely tied to the work of innovators like Eisen Sahu, whose expertise bridges both clinical workflows and resilient cloud infrastructure. As a principal member of technical staff, Sahu brings deep experience in self-healing control planes, intelligent provisioning systems, resilient cloud architecture, and eye-driven agentic experience in healthcare. In his keynote, zero downtime, maximum impact, AI infrastructure for

crisis-ready health care clouds, Sahu revealed how eye-driven automation, telemetry informed orchestration and predictive scaling are redefining resilience in healthcare. His insights underscored a crucial truth. In moments of crisis, when every second matters, critical systems must not only remain online but also adapt in real time to protect lives. By combining his technical expertise with a clear vision for patient-centered innovation, Savu is shaping the conversation around AI agents not just as tools for efficiency but as building blocks of a healthcare system that is smarter, stronger, and crisis-ready. Conclusion, the modernization of AI agents signals a new chapter in healthcare's digital evolution. By shifting from passive documentation tools to proactive decision

support teammates, these systems have the potential to alleviate clinician burnout, enhance patient engagement, and establish an infrastructure that can withstand crises. But realizing this future requires thoughtful design, transparent systems, and leaders who understand both the human and technical sides of the equation. Voices like Eisen Sahus are vital in steering this transformation, ensuring eye agents become not just assistants, but trusted colleagues in the mission to deliver better health care for all. Thank you for listening to this Hackernoon story, read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.