Big Data Analytics Can Predict Individualized Risk of Metabolic Syndrome in Patients: Study | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Big Data Analytics Can Predict Individualized Risk of Metabolic Syndrome in Patients: Study

June 27, 2014
by John DeGaspari
| Reprints
Large-scale patient data analytics can help create personalized, early intervention for patients

Analysis of patient records using state-of-the-art data analytics can predict future risk of metabolic syndrome, according to research published in The American Journal of Managed Care.

More than a third of the U.S. population has metabolic syndrome, a condition that can lead to chronic heart disease, stroke and diabetes. These conditions combine to account for almost 20 percent of overall health care costs in the U.S. The study was conducted by Aetna and GNS Healthcare Inc, a provider of big data analytics products and services in health care.

“This study demonstrates how integration of multiple sources of patient data can help predict patient-specific medical problems,” said lead author Dr. Gregory Steinberg, head of clinical innovation at Aetna Innovation Labs, in a prepared statement. “We believe the personalized clinical outreach and engagement strategies, informed by data from this study, can help improve the health of people with metabolic syndrome and reduce the associated costs.”

GNS analyzed data from nearly 37,000 members of one of Aetna’s employer customers who had voluntarily participated in screening for metabolic syndrome. The data analyzed included medical claims records, demographics, pharmacy claims, lab tests and biometric screening results over a two-year period. For this study, the Aetna and GNS teams used two distinct analytical models:

  • A claims-based-only model to predict the probability of each of the five metabolic syndrome factors occurring for each study subject.
  • A second model based on both claims and biometric data to predict whether each study subject is likely to get worse, improve or stay the same for each metabolic syndrome factor.

Both analytical models predicted future risk of metabolic syndrome on both a population and an individual level. The researchers were able to develop detailed risk profiles for individual participants, enabling a deep understanding of exactly which combination of the five metabolic syndrome factors each of the study subjects exhibit and are at risk for developing. For every Aetna member whose data was used in the study, the researchers used a scale that measures the percentage risk that individuals have of exhibiting each of the five metabolic syndrome factors. For example, in an individual patient who exhibited two of the five risk factors, researchers could predict which third factor is the most likely to develop.

The analytical models also helped identify individual variable impact on risk associated with adherence to prescribed medications, as well as adherence to routine, scheduled outpatient doctor visits. A scheduled, outpatient visit with a primary care physician lowers the one-year probability of having metabolic syndrome in nearly 90 percent of individuals. In addition, the study found that improving waist circumference and blood glucose yielded the largest benefits on patients’ subsequent risk and medical costs.

 

Get the latest information on Health IT and attend other valuable sessions at this two-day Summit providing healthcare leaders with educational content, insightful debate and dialogue on the future of healthcare and technology.

Learn More

Topics

News

Trump will Nominate Acting VA Secretary Wilkie for Permanent Position

Just a day after the Department of Veterans Affairs (VA) and Cerner inked their $10 billion EHR (electronic health record) deal, President Trump said he would be nominating Acting VA Secretary Robert Wilkie for the permanent position.

ONC Names API Server Showdown Stage 2 Winner

The Office of the National Coordinator for Health Information Technology (ONC) has named 1UpHealth as the Stage 2 winner of the “Secure API Server Showdown” challenge.

EHNAC Developing Trusted Exchange Accreditation Program

To align with the Trusted Exchange Framework and Common Agreement, the Electronic Healthcare Network Accreditation Commission, a nonprofit standards development organization and accrediting body, is working with other organizations to establish a new Trusted Exchange Accreditation Program.

Lawmakers Demand New VA CIO, Citing “Malign Neglect” on EHR Project

A group of Democratic federal lawmakers, five senators and six members of Congress, are calling out the U.S. Department of Veterans Affairs (VA) for what they call “malign neglect” in the agency’s efforts to achieve electronic health record (EHR) modernization.

Medical Record Access Proves Costly for Some Patients, GAO Report Finds

Federal law requires healthcare providers to give patients access to their medical records, but according to a new GAO report, some patients believe they’re being charged too much to access their records.

Parkland’s Innovation Bridge Takes ‘Genius Bar’ Approach to Digital Health Apps

Taking inspiration from the Apple Genius Bar and Ochsner Health System’s O Bar, the Dallas-based Parkland Center for Clinical Innovation in collaboration with Parkland Health & Hospital System has opened an “Innovation Bridge” to assist patients with health-related apps.