Last week at the American Physicians Groups Spring Conference in San Diego, California, our team heard firsthand how physicians are leading efforts to integrate artificial intelligence (AI) applications into outpatient and inpatient environments at major health systems across the country. Physicians and IT leaders detailed their organizations' efforts to identify safe, cost-effective, and desirable ways to leverage AI to improve efficiency and quality of patient care and reduce administrative workload for physicians. Here, we highlight key approaches that have seen early success across a range of health systems and physician groups, as well as key pitfalls that attendees considering adopting these technologies should consider as they plan.
In describing their early successes, physicians and IT leaders focused on two key goals:
Streamlining patient care navigation and improving the patient experience
For organizations that receive millions of phone calls and website visits each year, care navigation is critical, even with advanced customer relationship management and electronic health record resources. Organizations participating in value-based and risk-based payer agreements must ensure high-quality care and contain costs. To do so, they must pay close attention to ensuring patients receive timely, appropriate care from the right provider in the right environment. AI has the potential to support consumers in patient care through symptom checkers and patient outreach efforts, and to streamline the administrative experience through virtual registration and pre-appointment screening. On either side, AI must be trained to accurately interpret patient requests and information in context and ensure patients receive appropriate instructions for self-care and follow-up. Ideally, it should move patients closer to a “one-touch” encounter, improving the patient experience.
Reducing provider burnout
When patients don't receive proper care or instructions, they often message their care team, which can overload their inbox. Unfortunately, physician burnout is now epidemic and its causes are manifold. Many organizations report that documentation and inbox overload are a major source of stress for physicians. AI is a potential tool to reduce healthcare worker engagement levels and the time they spend on simple, repetitive, high-volume tasks, such as basic messaging to patients, or to support highly complex tasks, such as complex image interpretation and decision support for critically ill patients.
Many providers reported using tools such as ambient note documentation software to draft medical notes for providers during patient encounters. We also heard great success using automated reporting of lab test results to reduce clinician administrative burden and communicate clinical interpretations and next steps to patients. Finally, we heard from value-based care experts about how they are identifying factors that most impact risk, capturing actual or near real-time data to predict patient outcomes, and accurately risk stratifying patients for targeted population health and chronic disease management activities. In the short term, these types of AI initiatives can improve the care team experience by reducing the stress associated with these tasks. In the long term, providers who feel they have sufficient resources and support are more likely to stay with an organization, potentially improving provider retention.
When describing their approach to evaluating potential AI solutions, physicians and IT leaders focused on two key concerns:
Legal and ethical considerations regarding patient confidentiality and safety
In every discussion about AI, physicians and health systems emphasized their efforts before deploying AI solutions to ensure the tools can produce accurate results when applied in real-world applications while controlling for potential biases and risks to patient confidentiality. Several health systems described methodical, evidence-based strategies to identify, test, and validate safety, reliability, and regulatory compliance. Leaders noted that it is critical to ensure that AI applications are validated in the real world with results that are consistent with their performance in test environments before they are widely adopted, and to ensure that applications are continually evaluated once deployed in real-world clinical settings. Leaders also spoke about the need for providers to work with legal counsel to ensure patients have given the necessary consent. AI can implicate a myriad of laws, including HIPAA and other state and federal privacy laws.
Ensure the safe use of AI through structured AI governance and vendor management
Multiple organizations discussed the need to identify key leaders responsible for setting corporate goals for AI adoption and establishing clear expectations for AI governance and operations. In addition to selecting high-impact areas where AI can be an effective tool, organizations must determine how to best select, validate, and optimize AI tools within their unique world. Implementing a governance program may include forming committees, task forces, and implementing policies and procedures. Developing an AI governance program should involve decision makers and stakeholders involved in procuring and deploying AI. This includes legal, compliance, clinical operations, finance, IT, procurement/supply chain, and other groups that can help establish and control risk management frameworks for ethical and legal risks. Robust internal governance can support in-house development of targeted solutions that meet specific organizational needs, where appropriate, especially those involving sensitive patient data or trade secrets. In addition to internal governance and operations, speakers also emphasized the importance of strategic partnerships, data curation, and smart vendor contracting for AI solutions, including full control over the organization's data when possible.
Conclusion
The journey of integrating AI into healthcare will be challenging, but the potential benefits to patient care, system efficiency, and clinician well-being are enormous. By adopting structured governance models, focusing on patient safety and equity, and ensuring a responsible lifecycle of AI technology, physicians at leading health systems are pioneering innovative approaches that leverage efficient and effective tools to solve patient and provider needs.
