Most modern healthcare innovation relies heavily on the collection and analysis of massive amounts of patient data, but in order to pursue even more impactful innovation, researchers and clinicians must fully understand the advantages of this big data approach.
In a commentary article in The Lancet Digital Health, two genomics researchers from Stanford University’s Snyder Lab described the steps needed to utilize big data to its fullest extent.
Systems for the collection and analysis of health data will need to be standardized, easily interpreted and fully secured, they wrote, and the public will need to be fully educated about the benefits of committing to sharing their information. Additionally, clinicians and researchers must understand what makes data clinically relevant, and what information will merely overcomplicate analysis. “Smart and relevant data, not just data for data’s sake, will be crucial for healthcare adoption,” they wrote.
Should these goals be achieved, big data has the potential to lead to major breakthroughs in precision medicine, providing personalized diagnoses and treatment options and creating “a greater focus on health preservation,” rather than on reactive healthcare, according to the authors.
“We need to find creative ways to incentivize broad adoption of precision health, which will require participation from insurers, healthcare providers, employers and consumers,” they concluded. “Robust evidence of the health benefits of big data, together with financial incentives, will make precision health a reality.”
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