A new collaboration between big data analytics technology provider Teradata and big data strategy consultancy Knowledgent aims to provide deeper insight into patient health risks and as a result improve patient experiences while reducing costs.

The companies have announced a partnership to leverage predictive analytics in making health risk analysis more effective.

The partnership comes as healthcare insurers and providers look to reduce hospital admission and readmission rates. Improving the ability for payers to quantify and analyze member health based on the likelihood of hospital admission leads to targeted care for the patients most in need of intervention, the companies said.

The resulting health improvements lead to fewer hospitalizations and reduce associated medical expenses.

Healthcare providers are increasingly pursuing a data-driven approach to reducing their 30-day readmission rates, trying to avoid penalties imposed by the Patient Protection and Affordability Care Act’s Hospital Readmissions Reduction Program, the companies said. Regulatory and financial pressures make it more important than ever that providers be able to identify the patients at most risk for readmission and take steps to individualize preventative care to pre-empt readmissions.

“Healthcare organizations are being challenged to increase the quality of patient care while reducing cost, and most existing risk scoring solutions don’t provide deep insight into individual patient needs,” Jason Janetzke, senior global marketing director at Teradata, said in a statement.

“The time is right for healthcare communities to benefit from advanced, disease-specific risk scoring analytics—based on a broader, big data scale, which can improve patient experiences, prevent illness, and reduce costs,” Janetzke said.

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Bob Violino

Bob Violino

Bob Violino is a freelance technology and business writer who covers a variety of topics, including big data and analytics, cloud computing, information security and mobile technology.