Over the past few years, the healthcare industry has made a strong case for the use of artificial intelligence to augment clinical decision-making to improve patient outcomes.¹ Yet, Jason Jones, Chief Analytics and Data Science Officer at Health Catalyst, said these algorithms can also help organizational leadership make better strategic business decisions.

“Augmented intelligence [AI] – the term I prefer to artificial intelligence because we have no hope or desire to replace human beings – can be used to address the quality, the cost and the experience of everyone involved in healthcare,” said Jones. “But we often overlook how AI can be used with healthcare executives to help them with these objectives.”

Clinicians often have a decade or more of specific training and education in their specialty, Jones highlighted. Leaders in healthcare rarely benefit from the same level of education and training to guide them as they make vital business decisions that have the power to impact care. But the right AI platform can help fill in those gaps, helping them to better focus their attention and allocate resources in the right places.

“You can think of AI kind of like X-ray technology,” he explained. “If you think of a gunshot victim, back before the X-ray, you might never be able to locate the bullet. But with the advent of the X-ray, you can see exactly where that bullet is and see what needs to happen – and everyone can work from a common understanding of what they are looking at to make decisions.”

AI provides the same capabilities to healthcare leaders – it makes insights more accurate, consistent and explainable.

“Studies show that if you give leaders, at various levels, the same basic time series plot of performance in a particular area, only 4% can answer where the organization is at baseline, whether there are any extreme outliers, if there are any persistent shifts or trends, or where the organization is going,” he said. “But AI can raise that number to 40% to 45% – and help people interpret the information correctly so they can determine what should happen next.”

Such capabilities, Jones argued, are already readily available and attainable. And, he said, they will be essential to addressing not only clinical and financial improvements – but also to better deal with pervasive issues such as health equity and population health initiatives.

“It’s very rare today to have an organization that does not have a diversity, equity and inclusion officer. Yet what is rare is that so many of these brilliant, passionate people have little to no quantitative support whatsoever,” Jones said. “But when you have AI, you can start to ask the algorithm questions about disparities in care. Instead of asking if hospital readmissions have to do with blood sugar control or hypertension, you can ask whether they may be linked to age, race, primary spoken language or gender. You can gain insights so that very talented people you have in your leadership can apply their judgment and values to determine next steps.”

Learn more at www.healthcatalyst.com

Reference

1. Giordano, C., Brennan, M., Mohamed, B., Rashini, P., Modave, F., and Tighe., P. 2021. Accessing artificial intelligence for clinical decision-making. Frontiers in Digital Health. June 25. https://doi.org/10.3389/fdgth.2021.645232.