Big data holds the promise of helping to unlock key insights in the move to value-based care and precision medicine. The digitization of healthcare records and integration of research-grade clinical data and analytics has allowed practices to offer patients optimal, value-based care like never before.
The Institute for Health Technology Transformation estimated that the US healthcare industry produced around 150 exabytes of data in 2011. This vast amount of information was mainly comprised of patient care data, record keeping, and regulation adherence requirements. Since then, with healthcare costs continuing to spiral out of control—surpassing the initial benchmark by a staggering $600 billion— there is a continued interest in using data and evidence to make savvier, value-based decisions.
McKinsey Global Institute reported that if US healthcare providers were to use big data analytics effectively, they could generate more than $300 billion in value annually. This prediction is likely to encourage more healthcare providers and government agencies to embrace big data models as they aim to offer effective patient care while reducing costs for the population served.
Big data technologies enable providers to understand a number of institutional challenges, including reducing treatment variance, lowering readmission rates, and measuring performance against quality measures for value-based programs. These technologies permit providers to analyze relevant data, such as patient electronic health records (EHR), claims details, and patient generated With the ability to extract unstructured data as well as structured information, data that was previously destined to be warehoused is now available for insights, enabling practices to make evidence-based business and treatment decisions.
Access to data is also powering many of the positive developments happening in oncology research today. The odds of surviving cancer have increased dramatically over the last forty years primarily because research has led to better treatments. Given oncology's complexities—a single tumor can consist of more than a hundred billion cells, which have the ability to mutate individually—it has been a prime area for evidence-based, data-driven innovation and research.
Advances in research mean that a cancer diagnosis is no longer confined to types of organ cancer; it is now understood at a molecular level. This research has led to a better understanding of how cancers might react to certain treatments while taking into account patient medical history and comorbidities. Providing precision therapies with this amount of data can dramatically improve survival rates.
Having access to a range of research-grade oncology patient data—real-world data—allows researchers and life science companies to accelerate trials, studies, and developments of new therapies. Recently, a study presented at ASCO found that cancer drugs already approved to treat specific types of cancer could also be effective in treating other cancers. With the research was conducted on 129 patients, 29 patients responded to drugs that were already available. This shows that as well as looking for new treatments, access to real world data provides an opportunity to improve existing treatment methods for optimal patient outcomes.
These days, medical data is more than just a collection of patient notes or research confined to a notebook or filing cabinet; it is the key to unlocking value-based care and potentially life-saving treatments for patients.