Will EHR-enabled AI size up doctors for data-demanding patients?

The COVID-19 crisis has worsened or exposed myriad problems in healthcare delivery. One is the way patients find physicians and hospitals. AI can help with that.

So say two executives with healthcare AI startup Health at Scale in San Jose, California. Mohammed Saeed, MD, PhD, and Zahoor Elahi, make their case in Quartz.

After running through the deficiencies in popular doctor-shopping options like online reviews (one person’s opinion is just that) and national rankings by informed media (subjective perceptions color objective findings), the authors highlight a sleeping giant ready to rise and (data) mine: under-tapped Big Data in far-flung EHRs.

The problem there is enormity and complexity. Which is where AI could come in.

“We’re on the threshold of a new age, with artificial intelligence able to comb vast quantities of longitudinal patient data to spot patterns, make comparisons and predict outcomes in ways that can dramatically improve provider selection and patient care,” Saeed and Elahi write.

During the pandemic, AI-based provider selection could be “far more scalable and flexible,” given COVID-19 constraints and future patient backlogs, they propose.

“New approaches can also be distributed over a larger catchment or allow for selecting providers from coast to coast through greater telehealth options. On top of this, AI systems and machine learning can spot where normal referral patterns might be broken to step in and recommend a better option.”

To read it all, click here.