Driven by healthcare reform and consumer-driven technology (mobile health), we are seeing an exponential growth in the volume and types of healthcare data. Healthcare decision makers have the opportunity to enhance clinical outcomes by unlocking this data to generate actionable intelligence. Analysts point out that the value derived from big data could potentially be worth $300 billion per year in the US healthcare industry.
However, in comparison to other industries where big data has already become mainstream, the healthcare industry is still behind the curve, as a majority of healthcare systems are not yet equipped to handle real-time data processing. To effectively make use of big data for clinical analytics, healthcare organizations today need to address a few key challenges:
With a large part of the healthcare industry, both on the provider and payer side, still using siloed, legacy healthcare systems, they are limited in their ability to manage, integrate and process a wide variety of structured and unstructured data. The primary challenge for organizations is to make current systems ready for future use and be able to handle big data requirements, in terms of scale as well as the variability for structure and format.
Analytics on Unstructured Data
Organizations need to invest in sophisticated BI and analytics that can combine clinical data with unstructured data (e.g. clinicians notes), non-clinical data (patient responses on a portal), or even analog data (diagnostic results, medical images).
The technology should be able to process extremely high volumes of data (as much as 5000 events / second) in real time. Also, traditional clinical BI/analytics tools have generally focused on structured patient and population data, and use predefined measures or KPIs for benchmarking and reporting. With unstructured data, users have multiple new analytics capabilities, e.g. trend analysis to identify clinical or lifestyle patterns within identified populations, locating "hotspots” and "outliers” to help providers control avoidable costs and ADEs. Decision makers will have to adopt a different approach to how they leverage reporting/analytics tools.
Big Data Use Cases
Big data has the potential to impact multiple areas across the continuum of care, such as improving clinical, financial and operational decision making, reducing the cost of care, greater savings under federal and pay-for-performance incentive programs. Organizations would need to identify and prioritize use-cases based on their near-term and long-term objectives and develop responsive architectures that can be easily used by identified stakeholders with basic technological proficiency.
There is no quick-fix solution to address these and many other challenges that the healthcare industry needs to address to maximize value from the healthcare data deluge. Organizations need to develop time-phased, scale-as-you grow, cross-enterprise strategic solutions, to integrate, manage, analyse and draw actionable intelligence from big data, to effectively improve care quality and derive significant monetary benefits.