2015 Data+ Editors' Choice Awards

Memorial Healthcare

Data analytics helps this healthcare provider find operating room cost efficiencies and improve patient care

Memorial Healthcare’s IT team [2015]

Memorial Healthcare’s IT team includes IT clinical systems supervisor Diane Dowdell; business intelligence developer Karin Fernandez; Martin Hadida, director, data architect; BI architect Alvaro Reis; BI developer Terry Garzon; and BI developer Juan Velez.

Credit: Colette Lau

In many hospital operating rooms, only the top 20% of equipment and supplies being used during surgery are closely monitored in order to improve costs and availability. But today, Memorial Healthcare System in Florida can keep track of everything, from surgical devices to gloves, sponges and sutures, and track each item's use by type of surgery, doctor and patient.

MHS gained the ability to do that when it deployed BI Office from Pyramid Analytics on top of Microsoft SQL Server in May 2013. The system analyzes 500GB of data from five different sources.

Initially, one of the biggest challenges was cultural, because the project required finance professionals and clinical personnel to work together for the first time, says clinical systems supervisor Diane Dowdell, who has worked on both the medical and technical sides of the OR. But eventually, "we won [resistant staffers] over by showing them the information," says Alvaro Reis, a business intelligence architect in surgical services.

Now, for example, people in the finance department can compare prices of stents from different manufacturers with a few mouse clicks and quickly estimate whether switching vendors will save money.

And clinical staffers can, say, check to see which procedures are in demand, measure how long each surgeon takes to do a particular procedure, and check demographic data to see which segments of the local population have specific surgical needs.

"This is amazing information that transfers to all healthcare settings," Dowdell says, noting that all hospital staff can take part in improving processes. "These are the people who can truly understand the implications of the analytics data they're seeing. They can make suggestions or change the way they work to maximize efficiency, cut costs and improve outcomes."

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