Guest Column | February 25, 2016

5 Best Practices For Overcoming Data Integration Challenges

Overcoming Data Integration Challenges

By David K. Nace, MD and Bill Fox

Improving patient care, clinical outcomes, empowering patients, improving quality while reducing overall costs — what’s the common denominator for all of these? Data integration.

It’s not the sexiest or number one topic that comes up when discussing healthcare industry challenges, but it should be. Data integration puts the enterprise in a position to deliver comprehensive, up-to-date information to physicians and their teams so they can make real-time decisions that improve quality and outcomes with more accurate diagnoses and more effective treatments. In addition leadership can make better business decisions that drive cost reductions and quality improvement

Market leaders do in fact understand data integration is the number one underlying challenge for healthcare agencies and companies today. This is not surprising with the information glut facing these organizations: Data is running rampant in our industry with clinical, claims, pharma, R&D, patient monitoring, behavioral, and sentiment data all increasing. For example, an IDC report projects the volume of healthcare data will reach 2,314 exabytes by 2020.

Data integration is widely seen as the number one key to success for evolving accountable care, organizations’ management of population health and new payment models. Successful companies are embarking on data integration strategies and finding success. Kaiser identified patients within its population vulnerable to heart disease and “using standard screening and management techniques, has brought the number of heart attacks down by 24 percent, and serious heart attacks by 68 percent. Kaiser targets people with asthma, obese people and other groups for special attention.”

Following are some best practices healthcare leaders can implement to find similar success.

  1. Reduce or eliminate data silos. Silos sound great in theory: keep data like EHRs, billing, and research separate and secure, particularly in our HIPPA- and privacy-driven world. But this strategy is flawed in execution. While data can be protected in specific silos, it also means that data cannot easily be integrated. Silos don’t make data safe, proper data management does, and that can be done in an agile, integrated environment.

Further complicating the issue is the various types of data: Most technologies support specific data formats and with so many new types of data (images, texts, videos, etc.), even if organizations wanted to assimilate their data, they are hard pressed to do so without wasting massive amounts of time and money on ETL (Extract-Transform-Load) tools. These organizations need to explore ways to cut down the time wasted on unnecessary ETL.  

  1. Implement new generation technologies. Modern technologies like the cloud, mobile, wearables and remove telemonitoring devices and new generation databases all work together to help healthcare entities improve business processes, patient care and more. New generation technologies are designed to meet today’s lifestyle and data challenges, allowing users to integrate valuable data “as is” and distribute it in a secure manner.
  2. Make data integration a key part of any business strategy. Whether your company is attempting a merger or acquisition, entering a new market or restructuring IT infrastructure, a data integration strategy must play a crucial role in the success of any business endeavor. Data integration is essential to unlocking the value of data, whether it’s creating a 360 customer view, conducting analysis for cost savings, and more.
  3. Enrich data to make it more useful and therefore more powerful. Evolving data integration technologies like semantics enrich data to help add context and deeper and more meaningful integration of data from different sources.

For example, a broken arm is represented as an image in an EMR, but in claims data a broken arm is represented as ICD-9 code 813.8. Semantics can help users understand that, despite the different descriptors, they are in fact the same thing. Also, enriching data helps data fluidity, easily merging data from different silos. By eliminating complex master data schema more complete and real time understanding from multiple data sources can be achieved.

  1. Strive for agility. With massive increases the types, sources and speed of data, tighter and more complex regulations, seemingly frenzied M&A activity, and rampant competition, healthcare organizations and entities need to establish an agile infrastructure that can help them pivot to address or even get ahead of changing market conditions. New generation technologies are designed for today’s modern data challenges, and they can deliver the agility that many healthcare organizations seek.

The vast majority of objectives for improving the cost and quality of healthcare in the U.S. are heavily dependent on data integration as the foundation for ensuring success in the new environment. While the topic of “data integration” may seem boring, technical and/or too daunting, business as well as IT leaders in all healthcare companies and agencies looking for success must embrace the challenge. In fact, successful organizations will find that the challenge can be turned into a triumph.

MarkLogic will be attending HIMSS16 with 40,000+ health IT professionals clinicians, executives, and vendors from around the world.  The MarkLogic team will be at Booth #11650 showing how new a generation database is integrating data from silos to exceed business goals, and welcoming discussions about ways healthcare organizations are becoming more agile and realizing benefits such as reduced costs, improved care and decreased time to value for M&A activity.