The term Big Data has been a buzz word in the health IT world for a few years, along with Cloud Computing, Interoperability, and IoT. And these buzz words usually follow the same cycle—trend identified, buzzword created, term defined, and term applied. Big Data has come full cycle to to the application phase. Its applicability is especially evident in health care, where millions and millions of unique health records weave a pattern that often reveals trends and offer real-world health solutions. But the task of analyzing enormous piles of data – and doing so efficiently and effectively – is no small task.
Enter the follow-on trend of Software as a Service (SaaS), which is defined as a “delivery model that is centrally hosted. However, SaaS is not really new. It actually started in the 1960s when the computer industry began hosting business applications for government agencies and large manufacturing firms such as General Electrics. But CNSI was the first to apply this approach in the Medicaid space.
The idea is simple. Organizations outsource their system to a cloud-based SaaS. Using machine learning (i.e., advanced computer systems that can analyze information and adapt as they progress), the smallest of organizations can reap the benefits of big data.
To quote Jennifer Bresnick of Health IT Analytics, “These cloud-based tools reduce development burdens and infrastructure requirements… that can make it difficult to move forward with the clinical analytics and population health management programs that underpin value-based care.”
As an award-winning innovator of SaaS for Medicaid, we love to see this solution at work. And of course, we root for any solution that can improve health outcomes for patients.