Solutions for your new data reality


The adoption of the electronic health record (EHR) has created a tidal wave of data inquest. We now have this electronic system in place and everyone is hungry for the promise of information. However, we are still in our infancy of understanding how data is captured in the EHR and just scraping the surface of mining the EHR for clinical data. As we continue on this journey toward measuring outcomes and lowering costs, we are discovering that turning data into information that drives behavior isn’t so easy.

Some may say EHRs have been around for a while, but the reality is that implementation of the EHR is only now starting to become scalable, and the financial incentives for “meaningful use” and outcome reporting is bringing to light the resources required to turn data into information.

Health care organizations are facing data hurdles
Mining EHR data is new, but even newer is trying to transform clinical data into significant information. We are only just starting to explore all the different ways that data can be collected, counted and measured. Manufacturing and financial data, for example, is uniform and fits nicely into a “row-and-column” world. Clinical data capture, however, is extremely complex, nuanced and in most EHRs, is collected in free-text fields. What makes things even more problematic is the extreme lack of uniformity. Every system operates differently, and the few standards that do exist for data capture are not universally followed by any of the EHRs.

Translating these data text fields is a tremendously daunting task that has created hurdles for healthcare organizations as they discover they didn’t plan for the resources required to manage their new data reality.

It’s time to deal with our new reality
Eventually, we will find solutions to the lack of standards and discover smarter ways to translate the data, but today, as the demand for information continues to grow, we need data intelligence tools to deal with our new data reality.

It’s time to adapt to the current world we live in by identifying exactly what data is being entered, who is entering the data, how it is being entered, what processes are working, and what needs changing. These are important pieces of our new world, but it is essential that you understand your EHR data in order to know that you are meeting the required standards of Quality Improvement (QI) initiatives. You simply cannot control the future success of your organization if you do not truly know your data.

Our new data reality is also creating the need for a fresh position in healthcare organizations: a "data steward." The data steward is a designated individual who can manage clinical data and identify the most effective ways to capture the data so it can be translated into information that can be measured, reported and acted on. Ultimately, the data steward is like a "CDO" (chief data officer) who identifies what the data is saying about the organization and whether it is accurate.

This is critical because in the very near future, data will define your destiny. Data will determine the future of how healthcare organizations will be paid, how they will be measured, and ultimately, whether they are an effective, viable and successful organization.

In today’s new data reality, it will take time to resolve all the data problems. Technology will have to advance before clinical data can be effectively transformed into accessible information. In the interim, it is extremely important for healthcare organizations to develop a thorough understanding of their data if they want to control their future.

In the end, data helps to tell the true story about the organization. It is, however, up to the organization to determine whether the data is telling the right story and whether this is the story they want told.

Janice Nicholson is co-founder and CEO of i2i Systems. 

With over 20 years focusing on the needs of healthcare organizations, Janice has experienced firsthand the challenges of managing the flow of clinical data. Before founding i2i Systems, she had an extensive background as a software engineer. She has played a major role in developing a patient management system for private practice; has successfully managed over 10 major product releases; and, prior to its acquisition by WebMD, was vice president of product engineering at HealthPro Solutions.