By Doug Adamson, CTO, HealthCatalyst
Big data is generating a lot of hype in every industry including healthcare. As my colleagues and I talk to leaders at health systems, we’ve learned that they’re looking for answers about big data. They’ve heard that it’s something important and that they need to be thinking about it. But they don’t really know what they’re supposed to do with it. So they turn to us with questions like:
- When will I need big data?
- What should I do to prepare for big data?
- What’s the best way to use big data?
- What is Health Catalyst doing with big data?
This piece will tackle such questions head-on. It’s important to separate the reality from the hype and clearly describe the place of big data in healthcare today, along with the role it will play in the future.
A number of use cases in healthcare are well suited for a big data solution. Some academic- or research-focused healthcare institutions are either experimenting with big data or using it in advanced research projects. Those institutions draw upon data scientists, statisticians, graduate students, and the like to wrangle the complexities of big data. In the following sections, we’ll address some of those complexities and what’s being done to simplify big data and make it more accessible.
Most health systems can do plenty today without big data, including meeting most of their analytics and reporting needs. We haven’t even come close to stretching the limits of what healthcare analytics can accomplish with traditional relational databases—and using these databases effectively is a more valuable focus than worrying about big data.
Two roadblocks to the general use of big data in healthcare are the technical expertise required to use it and a lack of robust, integrated security surrounding it.
Read the source article at HealthCatalyst.