Physician providers and hospital systems aren’t the only healthcare organizations looking to advance their big data analytics capabilities, and they aren’t the only ones struggling with the complexity and sheer scale of information required to generate actionable insights and breakthroughs in treatment and care.
Life sciences organizations, including pharmaceutical, biotech, and medical device companies, are even more reliant than providers on the possibilities inherent in big data, and they are encountering many of the same data quality, reliability, completeness, and accuracy issues that are starting to plague analytics-minded practitioners.
A new survey by Reltio, a data management service vendor, reveals that healthcare big data analytics is at the core of most life science companies’ agendas. Fifty-five percent of organizations consider themselves “very data driven,” and 70 percent of their data comes from external sources, yet three-quarters of companies have deep concerns about how a lack of data integrity is affecting their ability to produce meaningful results.
The use of big data analytics is unevenly distributed across the life sciences field. More than two-thirds of biotech and pharmaceutical companies believe they are highly competent at using collecting and managing large volumes of data, but only 30 percent of medical device companies said the same. Over the next eighteen months, all three types of organizations hope to improve their capabilities with master data management (MDM), customer relationship management, and the collection of external data sources, including patient data.
Clinical data is becoming increasingly important for life science companies, especially those focused on developing and launching new products. More than 70 percent of companies said that the need for quality patient data is among their top priorities, followed closely by the desire for more detailed consumer affiliation and interaction data to complete the picture.
But as healthcare providers still wrestling with their EHRs are well aware, this type of information is difficult to collect, problematic to standardize, and sometimes near impossible to move or exchange. Life sciences companies are feeling the same interoperability and data integrity pain points as providers.
More than a quarter admit that they still struggle with data silos despite their MDM infrastructure. Seventy-four percent are worried about completeness, accuracy, and data integrity. Only four percent of companies have compiled critical data into a big data lake or Hadoop solution. Fifty percent say that despite being able to extract certain insights from their information, few of the results are meaningful or actionable.
Life science companies recognize that more robust collaboration with other healthcare stakeholders, including provider organizations, will be key to seeing success in a big data analytics world, especially as external data sources become more integral to their mission. As providers work alongside their R&D peers to bring big data analytics solutions and precision medicine to the healthcare industry as a whole, the link between development and application of new patient-facing technologies is likely to get much stronger.
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