Introduction
In work that started before COVID-19 spread to the U.S. and has accelerated since, two health care organizations discussed how each is advancing patient engagement strategies with artificial intelligence (AI).
Providence and Whiterabbit, in fact, are separately applying Amazon Prime-like thinking and tactics to the consumer experience. And while many providers are focusing on COVID-19 right now, for Providence and Whiterabbit (in conjunction with the RadNet radiology network), this work is simultaneously preparing for a future in which health care systems, much like the more advanced retail and financial services sectors, will interact with patients in a modern fashion.
This article, based on the Health Evolution AI-enabled Patient Engagement virtual gathering in which Martin and Mathur shared insights this week, will explore the following:
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- Why patient engagement needs retail methodologies
- Where to begin AI-enabled patient engagement
- Key elements of AI in patient engagement
- Post-pandemic challenges and opportunities
Why patient engagement needs retail methodologies
Engaging patients is difficult for many reasons. Regulatory issues that inhibit data sharing to a certain extent, client-server and legacy architecture, and a lack of common practices in other sectors.
“If you look at health care from the lens of the rest of our lives, it’s almost Soviet era,” Mathur said. “It’s archaic in terms of the way that a patient deals with the system.”
Rakesh added that retail notions such as same store sales growth, consumer experience and even simply understanding the total available market will be important to patient engagement in the future, which is coming quickly because of COVID-19’s impact.
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