a five-year $100 million investment to create a comprehensive data warehouse that brings together clinical, financial, administrative, genomic, and other information from more than 200 sources across UPMC, UPMC Health Plan, and other affiliated entities.
To collect, store, manage, and analyze the information maintained in the data warehouse, UPMC will use the Oracle Exadata Database Machine, a high-performance database platform; IBM's Cognos software for business intelligence and financial management; Informatica's data integration platform; and dbMotion's SOA-based interoperability platform that integrates patient records from healthcare organizations and health information exchanges. These tools will manage the 3.2 petabytes of data that flows across UPMC's business divisions.
Officials at the Pittsburgh, Penn.-based integrated health enterprise said its big data strategy will boost clinical and financial analytics, which will complement the data physicians already have in an electronic health record (EHR).
The goal is to help physicians, for example, take an intelligent EHR and flag patients at risk for kidney failure based on subtle changes in lab results, or predict the most effective, least toxic treatment plan for an individual breast cancer patient based on her genetic and clinical information. In the case of breast cancer, much of this work will be done through analyzing groups of patients so that researchers and physicians can follow their reaction to treatments and their health status over time.
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Officials at UPMC explained that they will begin using their new analytical tools on data gathered from a group of 140 breast cancer patients that were previously studied. Researchers already have both genomic and EHR data for these patients, which will give researchers a head start in their quest to understand the nuances of individuals and their response to medical treatment.
Another bonus of upgrading to more sophisticated analytical tools, officials at UPMC said, will be to help research clinicians compare and share a deluge of medical data while reducing their reliance on Excel spreadsheets, paper forms, and proprietary data systems that manually process information.
Lisa Khorey, VP of enterprise systems and data management at UPMC, said in an interview with InformationWeek Healthcare: "It's a lot of information. The typical clinician has more information coming at him than he has the cognitive capacity to really comprehend and react to and that's where the intelligence layer between the computer and the digital data and the human being has to be."
Neil de Crescenzo, senior VP and general manager of Oracle Health Sciences, said the initiative is important both for Oracle and UPMC because the enterprise healthcare analytics platform they're developing integrates data from clinical, genomics, financial, administrative, and operations across the organization. These are all areas that need to drive greater efficiency into their workflows as UPMC tackles the challenges of coping with the exponential growth in data.
With regard to UPMC's operational data, the organization may realize previously untapped benefits as analytical tools enhance the collection of data and translate it into actionable insights. One instance of this is identifying the utilization rates of operating rooms. According to de Crescenzo, operating room utilization data "does not sit in the financial system or in the EHR, it sits either in other systems or frankly in a few systems where the data needs to be integrated."
To sort through its data challenges, UPMC will use a wide range of Oracle tools, including Oracle Health Sciences applications like Oracle Enterprise Healthcare Analytics and Oracle Health Sciences Network. UPMC will also implement Oracle Fusion Analytics, as well as multiple components of Oracle Fusion Middleware such as Oracle Hyperion Profitability and Cost Management to support cost-based accounting and Oracle Identity and Access Management Suite Plus for regulatory compliance and data protection.