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A big data project should be part of hospitals' future plans

There are a few steps to take before implementing a big data system, including building a team and identifying goals.

Over the past few years much has been revealed about the power of big data. Insights have been identified and extracted from the wealth of digital information locked within the existing silos of information available within hospital systems. As a result, many hospital IT executives are wondering when it's a good time to begin to dig in and experiment with their own big data project.

While most IT executives are focused on critical priorities (meaningful use, ICD-10, system upgrades, EHR implementations and other ongoing projects) that overtake all other experimental projects, big data still must have a place on the project list in the future. There are some easy steps to take for healthcare technology directors and executives that will enable them to lay out the foundation for chipping away at the big data project.

Building the team. This is one of the critical areas which will enable the success of the project. The team will consist of technical and nontechnical folks who will help build the use case, as well as define the desired outcome for your big data project.

Building the use cases. Possible use cases for big data will be narrowed by defining the desired outcomes through brainstorming sessions, research and interviews. Outlining specific use cases will provide clear visibility of the goals and priorities that a big data initiative will help resolve.

Other big data use cases

Plenty of available data, lack of big data analysis

Natural language processing benefitting from big data

A few issues plaguing big data analytics

Discovering and translating data. Hospitals manage patient information under numerous systems. This can pose significant challenges for the technical team as they must sort through the information, build data warehouses, parse and massage it in order to analyze and extract insights from it. This requires expertise in interfacing, data conversions and named entity recognition.

Designing and implementing the system. Once the data sources and end goal have been identified, the IT leadership must evaluate and implement the platform that will allow that goal to be reached. There are numerous systems in the marketplace from which to choose. Upon the selection of the system, you can then begin the data analytics stage and review the outcomes and results.

Insights and discovery. In many cases big data has been able to provide powerful insights. Other times, findings surprise all the stakeholders and provide a way to validate certain processes or find opportunities for changes to correct issues that would otherwise have gone undetected. No matter what the result is, the IT leadership and big data team must prepare a game plan to use the findings to drive change and make the process a part of the ongoing conversation with the rest of the organization.

Big data can seem like a significant undertaking, but healthcare CIOs have all they need to make for a successful implementation. By taking small steps and going the do-it-yourself route, they are able to start small and slowly move on to a much bigger scale as they get more comfortable.

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