VIDEO: Use of AI to address health equity and health consumerization

AI is starting to be used in many applications to help increase access to higher value clinical care, even in remote, economically disadvantaged or resource poor areas. Examples include AI now being leveraged to help review and flag imaging exams in patient screening programs in developing countries where there are not enough physicians to review all the exams. It is also being used in rural clinics to help guide cardiac ultrasound exams or to offer initial clinical decision support for disease presentations that are not commonly seen.   

"What AI can do is augment your clinical decision support or your clinical pathways," Bogan explains. "In the future, we also will be less reliant on location. We will not need a clinic down the street because we will become more reliant on telehealth resources where physicians, or AI assisted physicians, will be able to help you."

He also said AI is helping healthcare systems address the growing demand for a more consumer-driven healthcare model, where care fits better with the patient's work or life schedule and there is less time waiting on hold.

"One of the things we need to be mindful of is that healthcare, like other industries, is going through a consumerization phase, where consumers and now demanding healthcare on their terms," Bogdan said. He explained AI can help with some areas of this process to reduce the number of staff needed to adjust to meet more immediate patient demands.

The U.S. Food and Drug Administration (FDA) has cleared more than 240 AI algorithms for use in healthcare to date, with many more pending final review. Bogdan said AI will be used to help augment staff shortages, streamline operations, data analytics, population health, scheduling, answering basic question and to flag critical findings for human doctors. He said AI is already being used across healthcare and it is expected to grow rapidly in the coming years. 

"If you don't have a strategy around artificial intelligence, there is a high likelihood you will be at a disadvantage, whether it is competitive or in producing the outcomes you are looking to produce in the health system," he explained. 

This is part of a 5-part series of interviews with Bogdan on various aspects of AI in healthcare. Here are the other videos in the series:

VIDEO: 9 key areas where AI is being implemented in healthcare

VIDEO: How hospital IT teams should manage implementation of AI algorithms

VIDEO: AI can help prevent clinician burnout

VIDEO: Understanding biases in healthcare AI

Find more AI news and video

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