3 min read
How Bioinformatics Identifies Patient Groups and Augments Research Output
Sophia Kapchinsky, PhD.
Jan 25, 2021 8:00:00 AM
Using a bioinformatics platform to narrow in on patient cohorts that match precise inclusion and exclusion criteria in 5 minutes or less allows researchers to prepare grant applications grounded in data, save time on recruitment, build collaborations across institutions, and increase their research capacity.
Experiment with inclusion and exclusion criteria before starting patient recruitment
While this seems impossible when using the traditional research pipeline, it is very easy to do with bioinformatics tools like Logibec NOAH. Researchers can perform queries that scan through health records at their own institution and across collaborating sites. They can do as many queries as they like and generate summary reports in only a few minutes.
The reports always include information on patient counts and which research centers house the information, but they can also be customized to include the number of patient encounters, comorbidities, medications, and group analytics for gender, race, and age. In addition, the database can be augmented in a number of ways, including clinical notes, research findings, and is applicable to any specialty, with notable examples being Pediatrics, Genomics, Proteomics, Radiology, Neurology, Cardiology, Oncology, and Psychiatry. The tool becomes a sandbox for researchers to explore various parameters and questions, and quickly see the number of patients they could study.
Identify which research centers have the type of data needed and how to contact them
Logibec NOAH allows researchers to search through EHR data from multiple institutions. Not only do users gain visibility on patient cohorts they are looking for, but also on the research centers that house the data of interest and their contact information.
Searching the EHR database to identify patients is easy and fast. Researchers simply drag-and-drop their criteria and use AND and OR boolean functions to quickly see how many patients match their unique query and which of the collaborating institutions house their patients-of-interest.
The search queries and report-generation do not impact or modify the EHR in the database. Each research partner remains in full control and maintains ownership of their EHR. The collaboration networks allow for data federation while also maintaining the fidelity of the data. This type of collaboration and data sharing has been successfully applied in over 200 research institutions worldwide resulting in hundreds of successful cross-disciplinary publications.
Creating a single reference point to identify patient cohorts either within a single organization or across a federation of partners is invaluable and facilitates cross-center collaborations with researchers around the world, as cohorts for a clinical trial can be recruited from multiple sites.
Accelerate the research pipeline and augment research output, without compromising the integrity of the research, data, or patient privacy
Regardless of the size of the research center and access to IT infrastructure and staff, new IT solutions like Logibec NOAH make it possible for small and large research centers to build their competitive advantage at scale. Since the platform uses cloud computing, it eliminates the need for in-house infrastructure, staff, and maintenance, while ensuring fast processing speed with around-the-clock availability.
Researchers can query the EHR database when they need and as many times as they need, without affecting the original data or infringing on patient privacy, while also gaining access to potential collaborators. This significantly accelerates the process of patient identification, recruitment, and data collection, thus not only increasing the chances of carrying out the research but also of publishing the results sooner.
Logibec NOAH, a user-friendly IT solution
Logibec aims to support clinical researchers with identifying and recruiting patient cohorts, as well as building inter-and intra-industry collaborations, in an autonomous way.