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Submission Type

Commentary/Editorial

Keywords

methods, learning health system, quality improvement

Abstract

Whether one reads Computerworld or Institute of Medicine issue briefs, it’s clear that most now accept the idea that existing electronic clinical data (ECD) and other health records can be used to manage and improve the processes, outcomes, and the quality of health care. Indeed the increasing popularity of the term “learning healthcare system” signals the broad acceptance of the idea that routinely collected clinical data can – indeed should – be used to advance knowledge and support continuous learning. But despite what the big data enthusiasts say, none of this is easy without the appropriate analytical methods.

This commentary introduces the seven papers in eGEMs’ second special issue, which are the result of invitations to researchers who have participated in EDM Forum activities as well as an open call for paper in early summer 2013. These papers offer a beginning snapshot of the ways innovative thinkers across the country are developing methodology to advance the national dialogue on the use of ECD to conduct CER, support QI, and generally to improve outcomes in a learning healthcare system.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

DOI

10.13063/2327-9214.1055

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