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Building Big Datasets

Do Not Forget the EMR

Freundlich, Robert E., MD, MS; Wanderer, Jonathan P., MD, MPhil; Ehrenfeld, Jesse M., MD, MPH

doi: 10.1213/ANE.0000000000001809
Letters to the Editor: Letter to the Editor

Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee

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To the Editor

We read with great interest the recent article by Vener et al1 on the use of large databases in anesthesiology research. The authors acknowledge many of the challenges researchers face when working with large perioperative databases, particularly when they are attempting to merge administrative and clinical data sources to generate new knowledge. As the authors discuss, the better we are able to link diverse data sources, the more robust the inferences we will be able to draw from the resulting combined datasets. Unfortunately, however, most available data remain fragmented, and although probabilistic linkages are increasingly common in the literature, they have limitations that may be poorly understood and appreciated.2

Although the authors briefly acknowledge the role that electronic medical record (EMR) and anesthesia information and monitoring systems (AIMS) vendors may play in this process, it is predominantly in the context of their role in facilitating data transmission to registries. We would contend that the authors fail to discuss the full potential of EMR/AIMS vendors in adequate detail. Enterprise EMRs, such as EPIC (Epic Systems Corp, Verona, WI) and Cerner (Cerner Corp, North Kansas City, MO), offer the potential to significantly facilitate the combination of data from a wide variety of sources and maintain identifiable linkages. As more and more centers, both academic and nonacademic, increase their adoption of enterprise EMRs, there exists an opportunity to link records from a single patient seen at multiple institutions for both clinical and research purposes. Tools such as CareEverywhere by EPIC, which is already in place at hundreds of hospital networks in 4 countries to facilitate continuity of care between institutions, could be adapted to facilitate this process.3

We would argue that this is only the beginning, and that the full potential of these tools is only just being realized. In the coming years, we anticipate that even more EMR and AIMS vendors will appreciate the demand for a central repository of patient data and will offer new and improved tools for storing and linking patient data. Policymakers will need to evaluate the needs of researchers and clinicians to determine whether policy changes, such as revisions to the Federal Policy for the Protection of Human Subjects (45 CFR 46, the so-called Common Rule), are necessary to meet this demand while taking privacy concerns carefully into consideration. Some vendors, such as EPIC, have already begun to offer integration with research databases, such as collaboration with the Multicenter Perioperative Outcomes Group. As vendors begin to appreciate the latent demand for improved linkages and integration between diverse datasets, even more useful tools and products are likely to emerge—beyond those currently made available through participation in registries.

Robert E. Freundlich, MD, MS

Jonathan P. Wanderer, MD, MPhil

Jesse M. Ehrenfeld, MD, MPH

Department of Anesthesiology

Vanderbilt University Medical Center

Nashville, Tennessee

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1. Vener DF, Pasquali SK, Mossad EB. Anesthesia and databases: pediatric cardiac disease as a role model. Anesth Analg. 2017;124:572–581.
2. Sayers A, Ben-Shlomo Y, Blom AW, Steele F. Probabilistic record linkage. Int J Epidemiol. 2016;45:954–964.
3. Epic: Organizations on the Epic CareEverywhere Network. Available at: Accessed October 20, 2016.
© 2017 International Anesthesia Research Society