We have all seen the headlines around what big data can do for the healthcare industry and patient care. Today let’s take a step back and look at what a successful architecture might look like with every day healthcare data sources in mind.
Krish Krishnan breaks down data sources for IBM’s Big Data & Analytics Hub. He writes, “Big data is information that is both traditionally available (doctors’ notes, clinical trials, insurance claims data, drug information), plus new data generated from social media, forums and hosted sites (for example, WebMD) along with machine data.” He breaks down these data sources among Volume, Velocity and Variety or the three Vs of Big Data.
- Volume: data sizes are varied and range from “megabytes to multiple terabytes”
- Velocity: “the data production by machines, doctors’ notes, nurses’ notes and clinical trials are all produced at different speeds and are highly unpredictable”
- Variety: data produced in different formats but not necessarily with the same standards
The key is to harness the data in an integrated solution that reduces complexity and latency as well as allows for scale, collaboration and agile analytics. Of course, the solution should also be “useful,” Mr. Krishnan explains, “getting the right information to the right resource at the right time.”
Mr. Krishnan also underlines the benefits of using metadata, “Using metadata-based integration of data and creating different types of solutions—including evidence-based statistics, clinical trial versus clinical diagnosis types of insights, patient dashboards for disease state management based on machine output and so on—lets us generate information that is rich, auditable and reliable. This information can be used to provide better care, reduce errors and create more confidence in sharing data with physicians in a social media outlet, thus providing more insights and opportunities.”
Getting started with big data may seem daunting at first, but a trusted, experienced business partner can guide you down the path so your organization (and patients!) can soon start to realize the benefits of big data.