While hospitals and health systems are steadily moving beyond the collection and management of electronic data and toward analyzing the data to improve patient outcomes, the lack of clear objectives is frustrating a number of stakeholders in their quest for realistic goals and outcomes.

Recently, a number of hospital executives gathered at the American Hospital Association’s Annual Membership Meeting in Washington, D.C., to discuss how their organizations were pursuing value through data analytics.

While much of the value sought is still unrealized, the discussion highlighted the perceived potential of data analytics, and the organizations’ respective first steps toward implementation provide insights into where the field is headed.

For example, Boston Medical Center, a safety-net hospital with a Medicaid insurance plan serving about 420,000 people, is using data analytics in its Medicaid accountable care organization (ACO). The ACO is in partnership with the state of Massachusetts, which has developed a risk-adjustment methodology, which, in addition to clinical factors, recognizes social determinants of health such as homelessness, housing and security, severe mental illness and substance abuse. 

With approximately 3 percent of patients driving about 40 percent of spend, the medical center is searching for a data analytics platform that finds patients at risk of becoming those few high-cost patients so providers can intervene earlier. 

"Our pilot data indicate that typical high-spend Medicaid patients are 57 years old, so we believe intervening when patients are in their 30s and 40s could help bend the cost curve," said Kate Walsh, president of Boston Medical Center. "If we could find a way to appropriately outreach to and better manage the health of those patients before they become the 3 percent, I think we'd do a much better job," she said. 

Similarly, Grady Health System, a public-private safety-net system in Atlanta, uses a predictive analytics tool called mobile integrated health to conduct outreach to patients in the community. Seventy teams of medical and behavioral health professionals are on the road providing care to patients, and each day they get a list of patients to visit, provided through an analytics tool.

"We run one of the largest hospital-based EMS agencies in the country," explained John Haupert, president and CEO of Grady Health System, adding that like Boston Medical Center, Grady Health System is combining analytics with social determinants of health research.

A predictive analytics tool used by Grady Health System providers tracks 20 social determinants of health on patients to identify which patients are more likely to be readmitted to the hospital within 30 days or to show up in the emergency department (ED). By knowing which patients to target for more intensive intervention, "we can better care manage those patients and a bit more effectively keep them healthy in our ambulatory environment and prevent readmissions and over-utilization of the emergency department and high-cost care.”

Concerning another social determinant, a high rate of obesity among youth in Bristol, Conn., spurred a novel community partnership. Bristol Hospital, a 150-bed facility, partnered with community groups to address the issue. Identifying at-risk children through the Women, Infants and Children (WIC) Food and Nutrition Service, the children and their families participated in cooking, nutrition, gardening and movement classes. "The improvement in [body mass index] for these kids was outstanding," said Kurt Barwis, president and CEO of Bristol Hospital.

In sum, Rob Nelson, global marketing director of artificial intelligence and analytics at GE Healthcare, said analytics models must be sustainable to create value in health organizations, adding that artificial intelligence (AI) applications can help to improve efficiencies in clinician workflow, helping to sustain value.

"AI can take care of some routine tasks," Nelson said. "No human intervention is needed any longer once you do it well. The one thing that we have a lot of are devices and there's a lot of data on those devices. So, we're starting to connect those devices and utilize AI to drive better processes, for improved asset utilization, throughput and capacity."