Cerner Corporation has partnered with the Duke Clinical Research Institute (DCRI) to pilot the Cerner Learning Health Network, an evolving database that aims to automate data collection for rapid access to contemporary medical information.
A pilot project and study, dubbed the Learning Registry, will leverage the Cerner Learning Health Network to evaluate the use and potential impact of proven therapies for chronic CVD, according to a release from the DCRI. Ideally, the network will automate swift data collection from multiple sources, including electronic health records, and provide researchers access to the most up-to-date data.
During the pilot project, DCRI researchers will reportedly use Cerner technology to analyze de-identified patient data from the University of Missouri Health Care and Ascension Seton with the goal of identifying the most effective treatment options for CVDs. After the project, the DCRI said the Cerner Learning Health Network “is expected to have wide-reaching applications in life sciences, pharmaceuticals and healthcare at large” and could help speed up research and “life-saving insights.”
Clients who use the Learning Health Network will have access to Cerner’s HealtheDataLab, a tool they can use to aggregate de-identified patient data from both Cerner and non-Cerner EHRs. The HealtheDataLab, which draws on the capabilities of Cerner’s big data platform HealtheIntent, enables users to transform datasets into research-ready formats and build complex models and algorithms. It also supports predictive modeling and intelligence.
“Current models for clinical research and registries that rely on mostly manual chart abstraction are too expensive, too slow and too small to continue,” Ann Marie Navar, MD, PhD, principal investigator and CV prevention researcher at the DCRI, said in the release. “We have to figure out better ways to leverage existing electronic resources to transform how we do clinical research.
“The EHR is an obvious starting point and HealtheIntent has all the right ingredients. It incorporates data from multiple EHRs, can link to national mortality and claims databases and helps us to harness the power and information security of cloud computing.”