Despite challenges such as a lack of standardization of data, the health care industry is taking steps to give doctors insight on how to improve patient outcomes.
In health care, the flow of data comes from a vast number of patients, whether it’s remote monitoring of vital signs or genomic or socioeconomic data.
The insurance companies have invested more heavily in big data analytics than hospitals, according to Cynthia Burghard, research director for accountable care IT strategies at IDC.
“The payers are a little more sophisticated from a tech point of view and have invested historically in the technology,” Burghard said.
Monitoring and predicting health data for patient populations will be essential to improving quality of care, lowering costs and finding cures, noted Michael Joseph, service area manager for Altarum Institute, a nonprofit health systems research and consulting firm.
To monitor and evaluate quality of care, doctors will be able to “bring together clinical, claims and demographic data in a unified platform for advanced analytics and development of longitudinal patient records,” Joseph said.
The data provides “near real-time evaluation of key metrics” to evaluate a physician’s performance, Joseph said.
At the University of Iowa Hospital and Clinics, big data and predictive analytics are playing a role in limiting postsurgical infections.
“Predictive analytics is allowing us to deal with the ever-increasing types of data that health care institutions need to deal with,” Dr. John Cromwell, director of gastrointestinal surgery for the University of Iowa Hospitals and Clinics, said in a case study.
The university is using Dell Statistica predictive analytics software to inform doctors of a patient’s risk level for infection. Doctors can determine risk by studying a patient’s medical history as well as monitoring real-time data during surgery, such as how much blood a patient has lost.
From a data pool of 1,600 patients, the university built its predictive model.
“We’re able to take information from electronic medical records (EMRs) and other enterprise sources, including real-time data from the operating room, to determine whether patients are likely to get a surgical site infection,” Cromwell said.
“This allows us to modify and individualize the type of care that we’re delivering in the operating room.”
Genomic research could be the biggest area of focus for big data in health care.
Organizations such as the National Cancer Institute are using high-performance computing to research the makeup of cancers and other illnesses.
“Nowhere in health care has big data been more pronounced and effective than in the field of genomics,” Joseph said.
“New gene therapies that can cure tissue cancers, blood cancers, diabetes and other diseases will be derived from this genetic information to create the era of precision medicine,” he added.
In another case, the University of Michigan Health System used advanced analytics tools to reduce the number of blood transfusions by 31 percent. The school saved $200,000 in expenses by using a predictive algorithm to determine when blood transfusions are necessary.