Analytics

'Our technology to produce data from genetic medicine is far more advanced than our ability to use it in a clinical environment.'

Researchers point to 'Total Active Risk' model to better address care coordination, patient activation.

Skillsets are changing rapidly. Hospitals must move quickly to keep pace. Experts from Advocate, Geisinger, University of California San Francisco and University of Mississippi Medical Center share best practices and lessons learned. 

Michael Draugelis, who spoke at the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum on Tuesday, also said healthcare organizations should collaborate to improve patient care.

"For every single problem you must have a multidisciplinary, interdisciplinary team," says Jeanne M. Huddleston, MD, associate professor of medicine at Mayo Clinic. "The low-hanging fruit in healthcare is gone. Now every problem is going to be hard."

At the HIMSS Big Data and Healthcare Analytics Forum, design and data visualization guru Teresa Larsen shows how to present information clearly, accurately and attractively.

The medical model focuses on customization of healthcare but a number of components need to be in place to make it successful.

The noted physician, software engineer and open science champion said that the hardest part of big data is knowing what questions to ask and finding people capable of figuring that out.

James E. Gaston, who is speaking at the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum, added that most healthcare organizations struggle with the balance between traditional decision making versus data-based decisions.

The goal is to rapidly design, develop, prototype, and showcase new healthcare solutions.