Breaking Down Research and Clinical Data Silos


Healthcare is infamous for its data silos. But increasingly there is a need to combine numerous types of research data with a variety of clinical data to improve patient treatments and enable more robust clinical research.

At the heart of most patient care and clinical research work is the need to make the right decision based on the available information. The challenge is pulling together the various patient health records, test results, and genomic, proteomic, metabolomic, and other data. Once this information is available, researchers then need to apply intelligence analysis techniques to make decisions based on the most recent information.

“Wall Street has used these techniques for years,” said Gary Kennedy, president and CEO of RemedyMD, a provider of decision support and clinical research software. He noted that healthcare could benefit by adopting this approach.

Indeed, while data silos have always existed and thwarted efforts to perform more sophisticated analysis, researchers now increasingly need access to clinical data and clinicians increasingly need access to research data to support new efforts such as predictive-based medicine and the customization of treatments based on biomarker analysis.

One feature of RemedyMD’s solution is that it lets organizations consolidate their varied research and clinical, specialty-specific databases into a single data repository without changing the data collection process. Each group that collects clinical or research data can continue to do so using their unique methods. In other words, the people collecting the data do not all have to conform to a single rigid database structure that is often the case when trying to pool data into a repository.

Recently, a large mid-West clinic selected RemedyMD’s Investigate solution to improve the efficiency of its clinical investigators. RemedyMD Investigate provides researchers with Web-based tools for managing research studies. For example, it includes a workbench that allows researchers to define, manage, and execute complex research protocols.

The clinic uses Investigate to first aggregate data from disparate clinical and research systems into a RemedyMD data repository called Mosaic. Clinical researchers can note patient progress by adding information to Mosaic such as the surgical procedures a patient undergoes, the time the patient spent in the operating room, surgery outcomes, complications, average length of stay, readmissions, and other items.

Once this data is assembled into Mosaic, the researchers can perform queries against any field. These queries can be done in an ad hoc manner and do not require any programming on the investigator’s part nor does it require any knowledge of the database’s structure.

Using the information in Mosaic, researchers can analyze the efficacy of different treatments. One key to the RemedyMD approach is its flexibility. “With little or no programming, our research coordinator can rapidly modify the software to collect data that is relevant to [a new project] and still maintain a standardized research data set that is used across the organization for studies, quality management, and outcomes reporting,” said the chief of surgery at the clinic.

The benefits realized by this clinic can also work on a smaller scale. For instance, another RemedyMD client needed to pull together information relevant to eight pediatric specialties such as pediatric cardiology and pediatric urology. This particular client already had some of the specialty-specific databases in place, while others had to be developed. For this effort, RemedyMD was able to pull together information from all eight specialties within a week.

RemedyMD has a number of solutions including electronic health records and tools to build and create queries and reports. The solutions are provided as ASP (application service provider) services.

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