Teradata, Knowledgent Team on predictive analytics product for healthcare

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Two analytics providers, Teradata and Knowledgent, have teamed to produce a product for healthcare providers and payers that combines predictive analytic models and behavior-based analytics. Specifically, the product is designed to reduce hospitalizations and improve preventive care for patients.

This is all about complying with the new patient-outcome pay structures and containing healthcare delivery costs. And there's the not so little matter of fines to avoid too. Obamacare penalizes institutions that fail to reduce their 30-day readmission rates.

"Risk Scoring by disease state has shown impressive results among early adopters that seek to reduce admissions and readmissions by leveraging their stores of patient data," said Matthew Arellano, Healthcare Partner at Knowledgent, in the announcement.

"Knowledgent's predictive analytic models are being used to identify patients that are admitted to a hospital with the highest probability of readmission due to a specific disease state, enabling providers to focus follow-up efforts and resources – including case management, nursing attention, and specialist visits – on the most vulnerable individuals. The addition of Teradata Aster Analytics adds multiple behaviour-based analytic dimensions to understanding patient risk factors." 

Analytics of this nature are crucial to making the shift from fee-based to patient outcome models as dictated by law. Ultimately this will benefit patients, as the focus is on their getting better and staying that way rather than simply treating each incident as a single, isolated event.

However, there really is only so much providers and payers can do to prevent hospital admissions and readmissions since factors neither they nor the patient can control come into play. Those factors include, for example, the patient's ability to buy medicines and healthful food. At some point, these issues will have to be addressed by society and lawmakers, as healthcare providers cannot provide these very necessary things for patients. Yet without these things, hospital admissions and readmissions will be almost impossible to prevent in some patients.

Patient compliance – following the doctor's orders on everything from taking medications to drinking fluids, controlling diet, getting adequate rest, to doing rehab exercises – also remain a challenge for providers and practitioners.  However, predictive analytics can help spot these troubles before they occur so support services, such as patient education, home health services, and well-timed followups with the doctor, can improve patient compliance.

Expect predictive analytics to become increasingly more central to patient care and hospital services delivery realignment.

For more:
- see the press release

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