The Big Data Problem in Healthcare: Extracting Insights and Value Posted January 25, 2016With the healthcare industry swimming in an “ocean of consumer and health data,” future success – including both improved clinical and business outcomes – depends on the ability of healthcare providers, pharmaceutical companies, insurers and others to convert the information into actionable and practical insights. So says a new report from PwC, outlining the top healthcare issues and trends of 2106. Electronic health records have been touted as the solution to the big data problem in healthcare, but these traditional relational databases are only one of many data components that the healthcare industry can put to work. And they have their limits when compared to more flexible platforms and tools that can join and compare many different data types. Take two female consumers, both age 57, with the same chronic condition — asthma. In a relational database, these two women may appear to be virtually the same: female, 57, asthma. And yet, digging deeper reveals that one is a triathlete who only uses her rescue inhaler before training, while the other uses hers during hay fever season — insights buried in handwritten physician notes that had been converted to PDFs. New database tools could help clinicians distinguish between these two women, offering insights to drug makers about how the inhalers are being used, to pharmacies about these patients’ unique buying patterns, and to the patients’ clinicians about how best to treat them. Real-world data that comes directly from patients via social media may be even more valuable. The issue is that many pharmaceuticals don’t have the capacity and processes to effectively filter and analyze such data. As PwC sees it: New databases and database tools will allow industry players to analyze data from many sources in novel ways, finally unlocking insights embedded in the reams of information being collected about health consumers. All of this unstructured health data, from population health analytics to clinician notes and transcripts, are especially valuable when they are combined with structured records to improve insights and personalize care. But pharmas, health systems and other organization need the platforms or tools to “make it easier to bypass the rigid structure and analyze many different forms of data together.” The PwC report also highlights how the new databases can deliver value in a few ways: Boost the value of existing EHR systems by providing “richer, more flexible data modeling and a range of analytical techniques” that will help clinicians extract new information. “Reduce costs and voiced mistakes … for specific functions such as drug development, prevention of duplicative experiments, prediction of drug performance in clinical trials.” Improve patient segmentation to “address specific needs and perspectives across (their) customer base.” Better use of multi-sourced data can also help with finding the right levels of drug pricing, according to the report. Drug pricing is a controversial issue for the industry at the moment, and a pricing approach based on credible information represents a vast improvement over the common pricing-in-a-vacuum model. Collaborative data collection and analysis efforts between insurers, drug companies and third parties will help lay the groundwork for new, mutually agreed-upon pricing and value models based on robust and credible information. Jointly developed value models will help avoid shifting criteria and defend against arbitrary drug access decisions by purchasers or legislators. The Data2Life mission is directly aligned to the need to manage and generate insights from diverse data sets. And our platform and toolsets are designed to handle the scale of multi-sourced, real-world data – including tens of millions of patient records to be accessed, hundreds of millions of patient-generated posts and Tweets, millions of claims reports and a vast range of regulatory records.