Mercy Healthcare

Analytics give doctors an objective way to assess different methods of caring for patients

Mercy Healthcare’s data analytics project team [2015]

Mercy’s data analytics project team includes Dr. Seth Barbanell, Curtis Dudley, Dan Magoc, Vance Moore and Ursula Wright.

Credit: Mercy Healthcare

Mercy, the seventh largest Catholic healthcare system in the U.S., believes there are about 80 paths of care that define 80% of the care provided in most hospitals.

The challenge is to sort through those options and find the best way to treat patients. Mercy has launched a "clinical pathways" initiative to do that, but the effort often yields broad courses of action that aren't optimized. Physicians are eager to share their own best practices, but each doctor has a unique approach to treating patients based on his or her own training and background.

Hoping to strengthen the clinical pathways initiative with objective analysis, St. Louis-based Mercy deployed advanced analytics software from Ayasdi, which uses reverse experimentation to identify patterns in data.

The Ayasdi software digs into Mercy's electronic health records data, harvests information on specific procedures and uncovers objective patterns. Physicians then evaluate the findings.

"We can analyze those [patterns] for variations that help optimize patient care," says Vance Moore, senior vice president of operations.

Early findings have been promising, but an immediate payoff isn't likely. "There's millions of dollars worth of opportunity there. The trick is for us to harvest that opportunity," Moore says.

"It has provided us the ability to visualize what exists and to objectively engage physicians to consider changes that can improve care. [But] there are some things we may not be willing to change," he says.

"We're in the infant stages of this, but initial results are interesting and promising."

This story, "Mercy Healthcare" was originally published by Computerworld.

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