Leveraging the Value of EHRs through Research Networks (CDRNs)

CDRNs Help Improve EHR Reputation

I recently had the opportunity to watch a webinar where the speaker, an associate director in the Office of Research Informatics at Duke University School of Medicine, spoke about the use of Clinical Data Research Networks (CDRNs). With the advent and rush of EHR adoption over the past decade or so, it has allowed for growth in not only functionality but also usability as well. While there has been growth for sure, the growth has proceeded in a terribly slow pace. Medicine is already a stagnant and slow field, changes are rarely adopted quickly and are often ignored and avoided. While the increase use in healthcare technology has provided a stimulus in continued growth, the presence of something is not always enough to push potential improvements. It is one thing to have it, but it is another thing to be able to effectively and efficiently use it. The world of medicinal science and research is often met with obstacles and hurdles and the traditional way of identifying cohorts and collection of clinical data is often strenuous, difficult, and unorganized.

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As a result, the talk focused around on how EHR systems can actually provide a benefit to researchers and various types of research to pool together data to support research efforts. Especially because of MACRA, which shifts from a volume to value based payment environment, clinical trials and pooled together healthcare information and data can help provide a tremendous benefit overall, not only to just patients. A group of healthcare delivery organizations can aggregate clinical data together to be shared in supporting clinical research, of course, all of the information is de-identified so that there are no specific traces. This allows for organizations to quickly respond to requests for data and requests for collaboration and study participants. Organizations no longer only have to rely on their own resources, but a pool of shared resources. Another great thing is because the information is de-identified, the healthcare data is all vendor neutral, meaning there are no additional steps or costs in order to convert information from Epic into Cerner, as an example. The following image is taken from the Spring 2017 slide deck, presented by Janis Curtis.

Despite the tremendous benefit provided by CDRNs, they require a diverse skillset to manage and support. It requires administration to provide oversight of data provision and recruitment functions, and they help develop and maintain policies and procedures for the CDRN. It also requires the researchers themselves to not only help with furthering their own research, but also to help recruit other researchers and participants. Lastly, the most important aspect, at least in my eyes, is the IT infrastructure that must be created to maintain the all of the EHR data. There is already a large volume of data, but then it must be kept secure, the quality must be maintained, and there must be capabilities for constant interactions and data manipulations as needed. The strong interdisciplinary collaboration and coordination is crucial for effective CDRN usage. The information flows from healthcare organizations into a research data warehouse, before it can be made for enterprise uses in research networks. The following image is an example workflow of information transmission for i2b2 (Informatics for Integrating Biology & the Bedside).

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One point that was mentioned earlier was about the transition towards a value based payment environment and its effects. I have written countless posts about MACRA, what it is, and how it will affect the healthcare field in the future. However, I believe that CDRNs are useful because it allows researchers and clinicians to ask questions and receive answers that they did not have the opportunity to ask before. With increased pool of healthcare data, it can now be analyzed to determine the best course of medical action, without inefficient usage of resources. Not only does a large pool of data allow for big data analytics, but it can help with influencing generalizability of study results and enables for more regional or national focused studies.

Article by Sir. Lappleton III

I'm a happy-go-lucky recent graduate that started a blog as a way to not only document my education and my experiences, but also to share it with whoever stumbles upon my site! Hopefully I can keep you guys entertained as well as learn about a few things from IT as well as from my time and experiences as I plunge deeper and deeper into healthcare! A couple of my areas of focus is data management, system security (cyber security), as well as information technology policy.

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