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Life sciences companies must develop robust pharma analytics capabilities to support new business models, such as health outcome analytics and personalized medicine.
The life sciences industry now understands the importance of distributed data and data as a service (where data is provided on demand). Advanced pharma analytics can help harness the potential of Big Data to efficiently enable new business services and reimbursement models.
For example, patient-specific longitudinal electronic medical record (EMR) data, genomic and genetic data, financial data and electronic patient-reported data is being used to deliver real insights into how to optimize healthcare management and determine the therapies that provide the highest overall value to patients and healthcare systems.
Action item for the CIO: Technology leaders must enable life sciences companies to combine data management and pharma analytics capabilities to get real-time actionable insights. They should identify data owners in the business and work with them to discover business processes that can leverage data as a platform.
Learn about the other life sciences technology trends:
Industrialized data services
Social-driven information technology
Platform-as-a-Service (PaaS)-enabled agility
Orchestrated analytical security
Read the full point of view Life Sciences Technology Trends 2012 or view the infographic to get a quick insight into these trends.
October 5, 2012
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