AI in 'high-stakes' clinical environments: 2 chief medical officers weigh in

The healthcare industry is poised to see more clinically-facing uses of artificial intelligence as the technology rapidly advances, creating a new set of challenges and opportunities for chief medical officers. 

To date, healthcare's most common AI applications have focused on hospital operations or the analytics space. But AI is set to significantly transform care, with potential developments in areas such as predictive medicine, precision treatment, improved diagnosis, remote patient monitoring and mental health support, according to Shlomit Schaal, MD, PhD, executive vice president and chief physician executive of Houston Methodist. 

Clinically-focused AI applications will grow exponentially in the coming years, and AI will be better integrated into everyday tools, predicts Erik Summers, MD, chief medical officer of Wake Forest Baptist Medical Center in Winston-Salem, N.C.

Healthcare workers will have to become more comfortable and adept at working with AI-based augmentation tools, as nearly every solution will still require some "person-in-the-middle" validation or other interaction with the AI output before putting that output into action, according to Dr. Summers.

"This is especially important for clinical applications, where the stakes are high," he told Becker's. "AI governance will mature rapidly, but organizations will struggle to keep up with the technology development and deployment pace. AI tools' utility and efficiency gains will drive the adoption, but many organizations will have a steep learning curve on how to effectively and safely deploy the tools."

Dr. Schaal, who also serves as president and CEO of the Houston Methodist Physician Organization, pointed to several key challenges with adopting AI in the clinical space that hospitals will need to overcome. Core obstacles include data privacy and security, avoiding ethical issues and bias, maintaining regulatory compliance, providing logic and transparency of AI decisions, and achieving interoperability with various data sources.

"These issues need careful navigation to ensure the benefits of AI are realized without compromising patient safety, privacy or trust," she said. 

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