4 Near-Term AI Predictions from ViVE

Thousands of health care leaders gathered last week at the ViVE conference in Los Angeles to explore challenges and opportunities facing health care delivery and how they might be solved or advanced from a health information-management and technology perspective. Speakers highlighted the potential benefits of emerging digital health technology, particularly artificial intelligence (AI). Here are four predictions on the use of AI in health care, all of which could be realized in the next 12 to 24 months.

1 | AI-enabled ambient listening technologies will reduce clinician burden.

By far, the hottest new solution category at the event was ambient listening technology that uses AI to create clinical documentation in real time for clinicians to review, thereby reducing clinician time spent on this nonpatient-facing activity. Organizations using these technologies must be transparent about their use, but should expect strong uptake. John Brownstein, chief innovation officer at Boston Children’s Hospital, noted that 99% of its patients’ caregivers consent to using the technology when informed.

2 | Clinicians will invite an AI co-pilot into their decision-making.

While there seems to be little interest in letting AI make actual clinical decisions at this time, clinical decision support that focuses on advising the next best action can serve as a co-pilot to clinicians, said Eve Cunningham, M.D., chief of virtual care and digital health at Providence. “Medical knowledge doubles every 73 days,” she said, making it impossible for providers to keep up without some sort of augmented intelligence. Providence is using MedPearl, a digital-assistant tool developed by Cunningham, with select primary care providers, and has found that it increases appropriate referrals to specialty care and more complete workups for those patients before their specialty appointment, thereby reducing the time to diagnosis and treatment. The tool analyzes patient data in the electronic health record (EHR) and displays related medical information and actions within the same EHR screen.

3 | Patients and providers will come to trust in AI, if transparency is prioritized.

While trust is hard-earned and easily lost, organizations that are transparent about its use likely will face less resistance from providers and patients when deploying new use cases. Richard Clark, chief analytics officer at Highmark Health, recommended that organizations create transparency reports that include the intention of the AI model, the data sets it was trained on and details about how it was tested across various patient populations.

4 | Patient-centered and provider-centered care will become less dichotomous.

We have traditionally thought of legacy care models as provider-centered, built more around provider schedules and less around patient convenience. New patient-centered approaches generally are viewed to be in opposition of provider-centered approaches, but AI tools, such as those described, are positioned to reduce friction for both patients and providers, said Brendan Carr, M.D., CEO of Mount Sinai Health System. “Delivery of care is better for both sides,” he added.