Teradata, Knowledgent Team Up to Help Healthcare Firms Better Identify Patient Risk

2016년 2월 8일 | DAYTON, Ohio

Using big data analytics for Risk Scoring Analysis by Disease State results in improved patient experiences, illness prevention, reduced costs

A new collaboration between top-rated data analytics leaders will provide deeper insight into patient health risks - which promises to improve patient experiences while reducing costs. Teradata (NYSE: TDC), the big data analytics and marketing applications company, and Knowledgent, a big data strategy and information consultancy that improves lives and business through data, today announced a partnership to leverage predictive analytics in making health risk analysis more effective.

The partnership is timely as healthcare payers (insurers and the federal government) and providers (physicians and medical services organizations) seek to reduce hospital admission and readmission rates. Enhancing the ability for payers to quantify and analyze member health based upon the likelihood of hospital admission leads to targeted care delivery for the patients most in need of intervention. 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, due to fines imposed by the Patient Protection and Affordability Care Act's Hospital Readmissions Reduction Program. These regulatory and financial pressures make it more critical than ever that providers are able to identify the patients most likely to seek readmission and take measures to individualize preventative care.

"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," said Jason Janetzke, Senior Global Marketing Director at Teradata. "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. Our collaboration with Knowledgent offers a winning outcome in every dimension of the healthcare equation."

Big data technologies enable healthcare organizations to leverage all relevant enterprise data when calculating a patient's disease state-specific Risk Score. In a big data environment, data from Claims, Electronic Medical Records (EMRs), Lab Results, Medical Images, Care Management notes, member surveys, and demographic and psychographic data sources can be collectively analyzed to Risk Score patients and derive insights that were previously impossible to collect. Knowledgent's Unified Patient Record collates disparate data points into a longitudinal view of the patient, facilitating analysis of and reporting on the patient data.  The combination of Knowledgent's data science and healthcare expertise with Teradata Aster Analytics enable advanced analytics and new predictive insights. 

"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. "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."  

Numerous examples of the benefits of implementing Risk Scoring analytics include a Pennsylvania health insurer that has been able to reduce its expected admission rate for heart failure by over 40 percent through the use of predictive risk-scoring analytics coupled with proactive preventative care. A healthcare provider network in the Carolinas leveraged predictive analytics to calculate a COPD (Chronic Obstructive Pulmonary Disease) readmission Risk Score; since doing so, they have reduced their COPD readmission rate from 21 percent to 14 percent. By looking at their patients' health by disease condition and not in the aggregate, these organizations were able to direct resources to their most vulnerable patients, improving patient health while significantly reducing hospitalizations and readmissions. 

Relevant News Links

  • To learn why Teradata Aster is the most powerful Big Data Discovery platform on the planet, click here now.
  • To view the new Forrester WAVE report naming Teradata a leader in enterprise data warehousing for big data analytics, visit the Teradata microsite.
  • To learn more about Teradata solutions for the Healthcare Industry, visit the web page.

To learn more about Knowledgent, visit the organization's web site.



Knowledgent is an industry information consultancy that improves lives and business through data. Our expertise seamlessly integrates industry experience, data analyst and scientist capabilities, and data architecture and engineering skills to uncover actionable insights. We have not only the technical knowledge to deliver game-changing solutions at all phases of development, but also the business acumen to evolve data initiatives from ideation to operationalization, ensuring that organizations realize the full value of their information. For more information, visit knowledgent.com.

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