As big-data analysis takes on a bigger role in health care management, some health systems executives are forging agreements with outside companies to help them develop better ways to do that.

Health systems like Mayo Clinic, Intermountain Healthcare and Catholic Health Initiatives recently inked separate deals with companies that will help tackle big-data projects such as combining clinical data with outcomes data and identifying high-risk patient populations. The debuts of those partnerships follow previously established data-analysis efforts at providers such as the University of Pittsburgh Medical Center and Cleveland Clinic.

The move to accelerate advancements in big-data analysis comes as more clinical information becomes available through electronic health records and as insurers and other payers plan to increase the use of reimbursement tied to clinical results.

To this point, health care has lagged many other industries in its use of analytics, and providers are now trying to catch up, says Jonathan Weiner, a professor of health policy and director of the Center for Population Health IT at Johns Hopkins Bloomberg School of Public Health. In health care, big-data analysis often describes the large-scale analysis of multiple data sets, though the term can mean different things to different organizations and industries.

With clinical-results data at the core of such new care and reimbursement models based on accountable care organizations and value-based purchasing, more health care systems executives are looking to make sure they are using data to the fullest to improve their care and work efficiently.

"I'm more optimistic now than I have been in many years," Weiner says.

Mayo Clinic's effort includes working to marry its clinical-outcomes data with claims data, which will produce a view over time of its patient care results that is currently unavailable, says Veronique Roger, M.D., director of the Mayo Clinic Center for the Science of Health Care Delivery. "We want to make sure our care processes and outcomes are the absolute best," Roger says.

Mayo is performing the analysis as a founding partner of Optum Labs, a joint effort with Optum, a data and technology company owned by UnitedHealth Group. Optum Labs, which also is aiming to help Mayo to create more effective benchmarks of care, is seeking other health care providers to participate in the project.

Roger says that while having other systems participate would result in income for Mayo, they don't expect to do more than offset their own costs of participating. "The goal is to break even," she says.

Earlier this year, Intermountain Healthcare formed an alliance with Deloitte Consulting to perform analyses that build upon previous work analyzing information produced by electronic records.

"We're going to do what we do anyway, we're just going to extend it," says Marc Probst, vice president and chief information officer for Intermountain, of the five-year deal with Deloitte. Among the other benefits of having big-data analysis methods in place is that research can be done more quickly, according to Intermountain.

A nine-month joint effort announced in April between Catholic Health Initiatives and Accenture will focus on population health and expanding care management beyond just the hospital setting, says Evon Holladay, CHI's vice president of enterprise intelligence.

For example, one type of analysis would group people into four categories: generally healthy, pre-disease state, single-disease state or chronically ill with complex conditions, she says. Efforts the could be tailored with each category to try to maximize care quality and limit costs in all types of care settings.

"We're looking at how to bring in data across the continuum," Holladay says. "Now we'll have the full view."