Large-scale health systems hold the responsibility of addressing health concerns specific to their regions and providing diverse patient populations with access to new medical advances. With a total of over 700 beds and over 1,200 medical staff members representing more than 50 specialties, Northeast Georgia Health System (NGHS) felt a duty to accelerate their ability to discover new scientific innovations to improve the health and quality of life of the people of Northeast Georgia. However, several obstacles hindered the speed and effectiveness of research processes.
Dr. Shravan Kethireddy, who works as System Director for Medical Intensive Care at NGHS, had made efforts in the past to use healthcare data to build a more sustainable approach to medical research processes. But he was set back by conflicts between IT-driven enterprise solutions, legacy systems, and clinician-led researcher innovations. According to Kethireddy, previous data investments “just did not meet the needs that we needed to satisfy in our rapid clinical environment.”
NGHS needed to collect multiscale time-variant data that would integrate easily with other project collaborators in a data environment that could grow and adapt to new sources, types of data, and computational needs. To drive future efficiency, NGHS also needed to be able to automate the time-consuming and error-prone steps in the research process. But researchers at NGHS were not used to navigating complex data systems while working against tight budgets and timeframes. NGHS would need a scalable, integrated data solution that also operated on a user-friendly interface.
IPC Global, a data and analytics consulting solutions firm in healthcare and higher education, identified NGHS’s need for a user-friendly interface that could complete complex data functions. IPC Global brought together Amazon Web Services Cloud and VizLib with Qlik Sense and their InProcess Research platform. These technologies together supported the ability to pull data from multiple data sources in near real time. From there, IPC Global’s data processing and validation innovations paved the way to quality data objects which could be used to reliably support findings and repeatable results. This platform enabled NGHS researchers to quickly develop hypotheses, run their research models, and create quality outcomes.
With a new data-driven research on-demand platform, NGHS was able to procure funding to produce a complete, peer-reviewed research publication within a year. This included narrowing down a patient population of over 36,000 patients across over 40 million encounters to find an appropriate cohort for the study. Mark Meersman, Founder and Managing Partner at IPC Global, described how a Principle Investigator at NGHS can now rely on automated processes for what used to be multi-step research approach: “A Principle Investigator will come up with an idea, discover information about it, see if grant funding may be available to support that finding and then turn that into an automated way to model that data and validate that model so that we can engineer those results and then from there produce results that turn into actual published findings.”
As healthcare systems are under increasing pressure to respond to public health issues in the areas that they serve, it’s important to make sure the medical research process stays reliable and efficient. NGHS’s investment in data integration has shown that modern data solutions have the potential to accelerate research processes in an increasingly complex healthcare environment. Through quantifiable results, data interoperability can bring automation and scalability to research processes.