Explore the transformative power of GenAI

Q1. What is the single most transformative impact you believe Gen AI will have on Providers, physicians, and patients in the next five years?

John: Five years is a long-time horizon. However, one significant impact will be the embedding of GenAI into general processes like answering emails, refilling prescription orders, and basic workflows such as prior authorization. This integration will prompt both clinicians and administrators to ask, “Why can’t we just do this?” This will drive data transformation and modernization projects, giving them more reason to invest. However, there’s a risk of over-reliance on technology, which could increase vulnerability to resiliency issues and cyberattacks. People will need to know how to revert to analog methods if necessary.

Q2. How are Providers, CXOs, and leaders leveraging GenAI today? What are their biggest challenges at scale, and how can they overcome them?

John: A perfect example is the replacement and augmentation of call center staff. Traditionally, intake involved someone collating information and routing it to experts. Now, with GenAI, the focus is on first-call resolution, whether it’s resolving technical issues, intake, scheduling, or directing to an informed person. By harnessing existing data and creating synthetic advisors, we can provide faster and more accurate responses.

Q3. In what ways can GenAI transform revenue cycle management for healthcare Providers?

John: Documentation has become a significant burden since the prevalence of HMOs and managed care in the early '90s. GenAI can shift the role of humans from documentation creators to validators, reducing workforce redundancy and after-hours work for clinicians. This will allow more face-to-face time with patients instead of being occupied at the keyboard.

Q4. How is GenAI being leveraged in digital engineering tasks for Providers, such as ETL processes, stored procedures, and script generation?

John: In healthcare IT, CIOs often joke that their role is more about interfacing systems. GenAI can memorize well-known patterns and create integrations on the fly, reducing the labor intensity of data engineering tasks. This will shift the focus from creating and re-engineering to defect resolution, improving efficiency and product quality.

Quote:
"GenAI is not a flash in the pan. It’s already being used profoundly in healthcare, particularly for high-volume challenges with well-defined knowledge bases. As we tackle smaller problems, we’ll unlock investment for bigger ones, leading to higher efficiencies over the next two years."

Q5. What role can GenAI play in enhancing the productivity of call center agents, specifically for IT help desk and appointment scheduling in healthcare?

John: GenAI excels at remembering everything that has ever happened. It can interrogate various databases, knowledge bases, resolved trouble tickets, and email correspondences to provide real-time answers to call agents. This capability will also boost scheduling efficiency by surfacing relevant information and identifying available doctors for quicker patient intervention.

Q6. How can GenAI automate patient care navigation and improve care transitions between different stages of patient care? What are some real-world outcomes you’ve seen so far?

John: Every patient discharge or care transition seems unique, but there are distinguishable patterns. GenAI can harvest these patterns to create discharge plans and coordinate complex sequences of care, such as timing durable medical equipment deliveries with interventionalist visits. This automation can significantly improve care transitions and outcomes.

Q7. What should be the top investment priorities for provider leaders and CXOs wanting to scale Gen AI and create significant value for their organizations?

John: The key is to set up centers of excellence, even small ones, with representatives from key functions or service lines. Start with easy use cases like call agents and scheduling intake, where there are already good solutions. Follow with areas that have adopted other types of AI, like RPA, as they are more open to investing in and adopting GenAI. This approach will unlock investment for tackling bigger problems and drive efficiencies across the healthcare model.