PHARMACEUTICAL BIGDATA ANALYTICS



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Transcription:

PHARMACEUTICAL BIGDATA ANALYTICS ANDINSIGHTS December 2013 Strategic Research Insights, Inc. 2013

Sources of Big Data in rpharmaceutical and Healthcare Industry Challenges with Big Data in Pharma Oncology Case Study Strategic Partnership Between Agency and Pharma Client What s Next?

Sources of Big Data in Pharmaceutical and Healthcare Industry Patient-Level / Claims Data Electronic Medical Records (EMR) Patient registry data Clinical trial data Genomic Data PharmaR&D data Diagnostics data Social media data And much more Strategic Research Insights, Inc. 2013 3

Sources of Big Data (cont d) Patient-Level / Claims Data EMR Data Patient Registry Data Information related to the billable activities of a healthcare system for its patients Hospitalization costs Date of admission Date of discharge Diagnoses codes Insurance information Digital version of paper charts that contain allof a patient s medical history in one specific office : Surgical history Family history Immunization history Current medications and medical allergies Developmental history and growth chart Etc. Collections of observational study data related to all patients with a specific disease, diagnosis, or procedure, in order to evaluate specified outcomes for a defined population Used heavily in scientific, clinical, and clinical policy Strategic Research Insights, Inc. 2013 4

Integration of Data / Insights Sort through each data file; identify variables that are present Understand commonalities within data files so they can be merged with ease Perform a thorough runthrough of data for a deeper understanding of which data are relevant to objectives Utilize data integration to address oncology business questions Strategic Research Insights, Inc. 2013 5

Challenges with Big Data in Pharma Patient-Level / Claims Data Minor tests, diseases, and procedures rarely reported Incorrect information Limited space on documents for recording procedures EMR Data Lack of interconnectivity with other EMR and various external systems Metrics not often defined and consistent Hesitancy to implement EMR systems Patient Registry Data Missing data Difficult to detect adverse events Inconsistent data being reported Strategic Research Insights, Inc. 2013 6

Oncology Case Study: Business Questions Addressed Percent of Stage III and Stage IV patients initiating treatment with Regimen A vs. percent who have never undergone treatment How many / what types of practices are prescribing a specific treatment? Use of new agents in treatment of advanced conditions Strategic Research Insights, Inc. 2013 7

Analysis Framework and Insights EMR Data Patient flow Integration and Analysis Treatment Algorithm Use of Existing Products by Patient Type Claims Data Use of New Agents Strategic Research Insights, Inc. 2013 8

Model: Strategic Partnership Between Agency and Pharma Client Pharma Client Strategic Agency Strategic Research Insights, Inc. 2013 9

Roles of Stakeholders for a Successful Partnership High degree of collaboration is critical for success Pharma Client Acquire data from appropriate data providers and provide to vendor Sell internally the value of the Big Data Work with business partner to identify key business needs and relevant questions Maintain frequent and effective communication with vendor critical for project execution and success Strategic Partner Acquire data from client, with appropriate agreements Gain a thorough understanding of the data provided Design appropriate infrastructure for hosting and analyzing data Establish strategy for data analysis; efficient data processing is key Work closely with the client throughout the analysis phase Identify additional opportunities to make use of the data Strategic Research Insights, Inc. 2013 10

Caveats of Big Data Analytics Personnel with multidisciplinary skills needed (data, analytics, insights, and IT infrastructure) Low insight to data volume ratio Absence of common variables across data sources Coverage varies by data source Data definitions not consistent Strategic Research Insights, Inc. 2013 11

Pitfalls of Big Data / Rapid Analytics Data Complexity Data Size Evolving Nature of Data IT Infrastructure Strategic Research Insights, Inc. 2013 12

What next? Potential Opportunities from Big Data Better channeling of marketing efforts Improvement in R&D efforts Evaluation of alternative treatments Faster identification of high-risk patients Early identification of safety signals Better understanding of patient behavior Identification of effective treatments Better Forecasting Strategic Research Insights, Inc. 2013 13