Healthcare data: A beast best tamed by machine learning?

Healthcare data: A beast best tamed by machine learning?

Mercy Health took a cue from its supply chain management machine learning success to bolster clinical pathways. The result: $14 million saved the first year, and Mercy is already on track to surpass that. But a VP says it’s not just about money.

Healthcare is a ripe target for machine learning to both optimize processes and greatly improve care delivery.

Take Mercy Health, for instance. When the health system was considering ways to improve care delivery, hospital executives looked at one of the most successful initiatives it had undertaken in the last decade: supply chain management.

“We have a lot of experience with operational efficiency,” said Todd Stewart, MD, vice president of clinical integrated solutions at Mercy. Using the operative suite as an example, he noted that all the supplies that go into and through it are very expensive. And there were many base concerns that needed to be addressed, including issues that seem obvious but are not, such as block time for a surgical case, including how you define start and stop times.

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