By now, everyone in healthcare is well aware of the problem of clinician burnout – and its consequences, which exacerbate the staffing shortage crisis.
Health IT leaders at hospitals and health systems have begun experimenting with artificial intelligence — which is seeing a huge boom in healthcare — to try to mitigate the problem of clinician burnout.
Can AI replace doctors? Some experts say yes — albeit only in small, limited ways. For example, Dr. Bruce Darrow, interim chief digital and information officer and chief medical information officer at Mount Sinai Health System in New York, said that in some cases, where the clinical accuracy of doctors and AI are nearly identical, Some future clinical care may actually turn to AI.
The point is: AI can help reduce doctors’ workloads and, in turn, reduce clinician burnout. Even if AI only plays a supporting role, experts say the technology could eliminate the enormous workload that clinicians currently face.
Dr. Eve Cunningham knows this stuff. She is group vice president and director of virtual care and digital health at Providence, and founder and CEO of MedPearl. The MedPearl platform is an AI-powered clinical intelligence tool designed by clinicians, for them.
Cunningham will speak on this topic at HIMSS’s AI in Healthcare Forum in a The case study session is scheduled for Thursday, September 5.
We interviewed Cunningham to talk about AI and burnout and get a preview of her presentation.
Q. In your session, how exactly will you address the topic of AI and clinician burnout?
ONE. The focus of the session was to provide three real-world examples of AI applications in our health system, specifically related to clinical workflow and clinician burnout.
I plan to provide examples of: in-house AI-enhanced technology (build), MedPearl; examples of partnering with vendors (buy) to deploy an AI-enhanced solution; and examples of desired solutions stalled due to technical challenges related to infrastructure, technical debt, and misaligned incentives.
While AI has the potential to revolutionize healthcare by improving decision-making and optimizing workflows, its implementation is not without challenges. A key aspect of our discussion revolves around ensuring AI applications and capabilities serve as beneficial tools rather than becoming a burden to clinicians.
The relevance of this topic is highlighted by ongoing discussions in healthcare settings about the balance between technological advancement and the delivery of person-centered care.
Q. What is an example of AI being applied at your organization?
ONE. An example of AI technology at our organization is the MedPearl platform, a clinical intelligence tool designed specifically by and for clinicians. This platform illustrates our approach to integrating AI into healthcare settings.
MedPearl enhances clinical decision-making by consolidating clinical knowledge, patient data, and next best action recommendations at the point of care into a single interface, thereby optimizing clinician workflow and reducing cognitive load.
The development of this platform was guided by collaboration between clinicians and technology experts, and the AI roadmap was carefully constructed, considering not only technological aspects but also clinical safety and relevant human factors.
By viewing AI as a tool and capability embedded within a larger product designed to support clinicians, rather than as a standalone entity, we are thoughtful in layering the AI capabilities we enable within the platform.
This example serves as a microcosm for our broader approach to AI in healthcare – thoughtful integrations specifically designed to enhance the clinician’s role and build trust in the product from a quality and safety perspective.
Q. What two things do you hope seminar attendees will learn and be able to apply back to their service organizations?
ONE. The first lesson is that AI integration should be viewed as a deliberate, incremental process tailored to specific clinical needs and strategic goals, rather than a quick, one-size-fits-all solution. Implementing AI in healthcare settings requires careful consideration of the problems it aims to solve and an understanding of the potential impacts on clinical workflow and provider well-being.
Second, we emphasize the importance of being strategic in selecting use cases. It is important to prioritize AI applications that align with the organization’s strategic priorities and solve high-value clinical or operational problems.
We will share real-world examples from our experience at Providence, where AI use case selection and implementation were closely aligned with our strategic goals and designed to support, not replace, human expertise.
Attend this session at the HIMSS AI Forum in Healthcare scheduled for September 5-6 in Boston. Learn more and sign up.
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Healthcare IT News is a publication of HIMSS Media.
