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Monday
Nov302020

EPIC Health Research Network: Pandemic-inspired innovation in medical outcomes research

Early announcements of the Epic Health Research Network (EHRN) this past spring didn’t grab my attention the way they should have. But a recent article by John Lynn in HealthcareITToday caught my eye, in large part because of the way he described EHRN as a “near real-time medical journal”.

Epic’s announcement of the EHRN described it as a network for bringing together “healthcare professionals, researchers, and data scientists to publish early data-driven observations” and included the following quote from Judy Faulkner:

“We have a tremendous opportunity to help healthcare professionals and researchers share their discoveries with the world,” said Judy Faulkner, CEO of Epic. “We have been interested in creating this site for years to share new knowledge. With the COVID-19 crisis, the need for fast dissemination of knowledge has become critical.”

On the EHRN.org website, EHRN is further described as follows:

EHRN is a journal for the 21st century, designed for rapid sharing of knowledge with researchers, healthcare professionals, and learners to help solve medical problems.

Electronic health record data collected over decades, spanning millions of patients, could provide clues to help solve medical problems.

EHRN reports are reviewed internally and externally prior to publication. To expedite information sharing, they are published without traditional peer review. It’s important that good data be available sooner, rather than perfect data be available too late—especially in times of public health crisis.

EHRN is where you’ll find our reports. We invite others to contribute as well, from health systems and higher learning institutions to government agencies.

Our goal is for EHRN to light the way for fast, collaborative research.

[EHRN.org/About-Us]

Value of Outcomes Data

Unleashing the value of data stored in EHRs has been at the center of my interest in health IT from the time I first started attending HIMSS conferences over a decade ago. However, in retrospect, I realize that the health IT community had little-to-no experience in conceiving new applications for EHR data or in developing complex data products.

Furthermore, patient privacy concerns and data sharing roadblocks curtailed investment in platforms for sharing research derived from outcomes data. The EHRN doesn’t solve these problems, although it may serve as a catalyst for knocking down some of the obstacles across institutions, especially institutions that use EPIC systems (with some help from the ONC’s Cures Act).

Comparison to Usage of Real World Evidence in Life Sciences Research

The life sciences sector has been quicker to develop platforms for including outcomes data, which they refer to as “real world evidence” (RWE) or “real world data” (RWD). Three notable players in this space, TriNetX, Datavant and Medidata, recently announced a partnership to leverage the technology and data assets of the trio to accelerate advances in clinical trial research. It would behoove medical professionals involved in developing evidence-based decision support tools to study the progress made, and methods used, in clinical trial research.

Future for Medical Journals

Under the scenario where outcomes data research platforms gain momentum and become a primary channel for disseminating research, reputable journal publishers can continue to play an important role in amplifying new research developments and putting new evidence in context. However, traditional publishers need to be aware of the new digital research platforms and consider the impact that research networks like EHRN will have on legacy publishers’ role in the research workflow.

With flat or declining budgets from their traditional library market and a push to adopt open access business models, which constrain publisher revenue, medical journal publishers face a dismal future if they fail to recognize the disruption that is occurring and fail to respond by creating—or partnering to create—innovative methods of adding value to the research workflow and implementation process.

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