4 Powerful Ways Agentic AI Eases Burnout and Boosts Efficiency in Healthcare
Agentic AI reduces clinician burnout by managing scheduling, documentation, and patient care tasks autonomously. It streamlines workflows and improves patient engagement in healthcare settings.
4 Top Use Cases for Agentic AI in Healthcare
Agentic AI is helping reduce burnout among clinicians by managing scheduling, documentation, and patient interactions. These AI systems act autonomously to support decision-making and assist during staffing shortages.
Wes Little, executive vice president of analytics and AI at WellSky, calls AI agents “the biggest untapped opportunity” in healthcare. They operate around the clock, handling tasks that traditionally required human staff, especially in areas like post-discharge and post-acute care. Fertility clinics, facing clinician shortages and rising demand, are already using AI to manage workflows more efficiently, says Irene Alvarado, CEO of Berry Fertility.
Agentic AI integrates with application program interfaces (APIs) to perform actions like querying electronic health records (EHRs). These agents are evolving to read entire web pages, extract useful information, and input data into other systems automatically. This shift suggests a future where internet traffic will largely come from AI agents gathering and sharing data rather than humans.
1) Scheduling and Appointment Reminders
Healthcare providers use voice-activated AI agents to handle appointment scheduling and send reminders via text or phone calls. WellSky’s voice agent, integrated with their scheduling software, calls patients the day before appointments—something that was previously hard to scale due to limited staff.
Missed appointments cost providers both time and money. AI agents now enable natural conversations with patients, going beyond the old “press 1 to confirm” style to address patient responses in real-time. This reduces the need for follow-up calls by staff and improves patient engagement.
Even without direct API access, AI agents can log into EHR calendars, fill open appointment slots, send confirmation emails, and trigger SMS reminders. Other companies offering similar voice AI solutions include Amelia and Innovaccer.
2) Preauthorizations
AI agents are streamlining insurance preauthorization by interacting autonomously with payer portals. They call insurance companies to seek approvals for treatments, saving providers from maintaining large teams dedicated to these tasks.
These agents perform “web crawling” to gather all necessary documentation and data required for authorization. In fertility care, where insurance coverage varies widely, AI helps finance coordinators by validating information and speeding up approvals. This reduces the typical 4-8 month wait patients face before starting treatment.
Preauthorization automation also helps patients and clinics identify covered medications faster. While AI is still early in taking over these calls, it can validate human research and free up time for staff to focus on clinical care.
3) Documenting Patient Encounters and Automating EHR Entries
AI tools assist nurses and physicians by drafting clinical notes or summarizing patient visits. For example, Oracle Health’s Clinical AI Agent uses voice recognition to record conversations and generate draft notes directly within their EHR system.
Healthcare systems like Beacon Health use ambient AI to reduce administrative burdens, allowing clinicians to focus more on patients. Improved documentation accuracy also strengthens patient trust, as notes reflect a fuller picture of the encounter.
4) Patient Engagement
Agentic AI enhances patient engagement by routinely checking in through apps or calls to monitor patient well-being. These interactions collect data points that feed predictive models, helping providers identify risks early.
For patients recovering from procedures like hip or knee replacements, AI agents provide continuous follow-up outside the hospital. This reduces readmissions by catching issues before they escalate and keeps patients connected to their care teams.
As AI agents interact more with patients, they improve in answering questions and providing guidance. Often a “human in the loop” reviews AI recommendations, ensuring safe and accurate responses. Over time, agents learn from feedback to become more effective and responsive.
For healthcare professionals interested in understanding AI’s impact and applications, exploring targeted courses can be valuable. Resources like Complete AI Training’s healthcare-focused courses offer practical insights into integrating AI tools in clinical settings.
