Is Big Data a marketing buzzword? A sales pitch? Can we get a translation?
You’ll get all of those sentiments about the term big data these days. The resident experts who design and build massively parallel, distributed systems know this well. Whether through the open source community or not, the term big data includes those experts developing the algorithms, the indexing schemas, the infrastructure and all the rest. They’ll tell you that the term has been around for years and the phrase big data is superfluous to them. They’re certainly spot on.
Big data is not a new phenomenon, but rather a term coined to market the collection and usage of extremely large and complex data sets. This includes the tools used to share and visualize results, the intelligence behind indexing, searching, and analyzing data, and the infrastructure behind capturing, storing and transferring it. It’s the ecosystem behind the massive amounts of data being collected instant by instant, all over the world. One of the most important outcomes of having all this information is going to be what we choose to do with it.
What does it have to do with healthcare?
You’ve undoubtedly heard of Accountable Care Organizations, Health Information Exchanges, ICD- 10, HL7, EMRs, APIs, and the like; the list goes on and on. All of these tools, frameworks, standards and organizations, combined with the power of data analytics, enable our ability to capture, store, manage, extract, share and make sense of clean data. Ultimately, all of this will ensure critical information is in the hands of physicians and clinical staff to improve the quality of care, at the point of care.
In short, there are many implications of big data in the healthcare space and some are more apparent than others. En mass, once the proper infrastructure, software, applications, security, compliance and interfaces are in place, the power of all of that patient data is overwhelmingly impactful and in many capacities.
Think about it from a demographics perspective. On a community, regional, statewide and national level, the point of care is going to be impacted tremendously.
When you combine the data harnessing power of EMRs with HIEs and ACOs, you have a recipe for acute diagnostics, trend analysis, variance analysis and of course predictive analysis on specific populations, which may be the most important of all.
With this information, we will be able to answer these questions and many more:
- Who is at risk for certain ailments? When and why?
- What is this person’s risk profile?
- What is the best course of remediation? Prevention?
- What works and what does not work? Why?
By using the power of big data in the finance and operation teams within health systems, the given automation capabilities are extensive. Together, these tools will save organizations time and ultimately, money – both of which can be used to better serve the patient.
As these trends progress, you may hear more about terms such as:
- Hadoop: open-source framework
- DBMS: database management systems
- NoSQL: non relational databases
- Cassandra: open source database
- Hbase: open source database
- The Cloud: internet storage services
- Zettabytes/Exabytes: quantities of data
- Clustering: groups of servers/resources
Case Study: Atigeo
There are hundreds, if not thousands, of companies in various stages that will help serve our healthcare community’s desire for data analytics. One such company, Atigeo, is working to utilize data intelligence to directly impact our quality of life.
Atigeo’s health solutions apply xPatterns intelligence across EHRs and other clinical tools to improve organizational performance. According to their SVP of Engineering, some of what Atigeo’s experts and tools are currently focused on center around clinical process automation and decision support, fraud detection and evidence based medicine.
“If you really want to solve these problems correctly, you have to have localized models and proper feedback loops. In the infrastructure, other than just getting good architecture and compliance, the true value is in doing the analytics very well. It’s in the intelligence layer where we’re most unique – we have the fastest time to market, with measurably better analytics, and it benefits everyone.”
There are a plethora of companies out there that are working diligently to bridge the gap between massive amounts of data and better patient care.
Soon to be gone are the hand written notes scribbled into a spiral pad. Welcome to fully integrated user interfaces, with data intelligence engines behind them and the technical infrastructure to bring mission critical data to a myriad of devices, all at the push of a button.