Agentic AI for Medicare Annual Wellness Visits: Improving Preventive Care

This paper addresses the role of Annual Wellness Visits (AWVs) among Medicare beneficiaries. According to the study, the AWVs could be an ideal way of providing evidence-based prevention for Medicare beneficiaries. While Medicare AWVs presents a free, one-time event once a year, the implementation rate is under 30%. The top three challenges that have the most impact on the low number of AWVs are Patient-related barriers, Provider-related barriers and System-related barriers. This paper studies various efforts made with the goals of increasing efficiency, improving adoption, and having better patient outcomes with the AWVs workflow. While recognized improvement in AWVs adoption with these efforts, most of the efforts were manual or very little use of digital technologies and required significant amount of time from healthcare providers. This research discusses how the potential of using AI, and specifically Agentic AI workflows, can be harnessed to overcome such barriers and streamline A WV delivery at the same time reducing the administrative burden for healthcare providers. By utilizing LLMs and Agentic AI, automating processes like appointment scheduling, pre-visit data collection, and other AWVs steps, healthcare providers can spend their crucial time for patient care. The article proposes Agentic AI workflow and theoretical study, with the goal of more effective and efficient preventive care. Lastly, this paper will briefly state the possible challenges, opportunities, and obligations of applying Agentic AI workflows in AWVs. These include requirements such as strong data privacy protection, solutions for ethical AI decision-making issues, and ensuring that AI instruments are designed and put into place equitably and in an open manner. The paper will show, how Agentic AI can render AWVs more proactive, tailored, and useful prevention care option for Medicare patients.