Appl Clin Inform 2019; 10(02): 272-277
DOI: 10.1055/s-0039-1685221
Letter to the Editor
Georg Thieme Verlag KG Stuttgart · New York

Quality Informatics: The Convergence of Healthcare Data, Analytics, and Clinical Excellence

Nathan A. Coppersmith
1  Warren Alpert Medical School and Center for Biomedical Informatics, Brown University, Rhode Island, United States
,
Indra Neil Sarkar
1  Warren Alpert Medical School and Center for Biomedical Informatics, Brown University, Rhode Island, United States
,
Elizabeth S. Chen
1  Warren Alpert Medical School and Center for Biomedical Informatics, Brown University, Rhode Island, United States
› Author Affiliations
Funding This work was supported in part by the Brown Center for Biomedical Informatics and Institutional Development Award Number U54GM115677 from the National Institute of General Medical Sciences of the National Institutes of Health, which funds Advance Clinical and Translational Research (Advance-CTR). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Further Information

Publication History

13 September 2018

06 March 2019

Publication Date:
24 April 2019 (online)

Background and Significance

The convergence of electronic health record (EHR) adoption, increased availability of electronic health data, development of analytical techniques, and healthcare payment reform has created an environment ripe for using information technology to improve delivery of healthcare services.[1] [2] [3] The lack of unification has manifested itself in EHR systems used by providers, quality measures developed by different groups, and use of quality measures in different ways by different organizations.[4] The organization and coordination of formal approaches for using health information systems and their data to improve clinical effectiveness is needed.

Quality informatics is defined here as the discipline that “uses healthcare data collected from healthcare information systems to improve clinical effectiveness.[5]” As part of clinical informatics that broadly studies the organization and use of information to improve healthcare delivery,[6] [7] quality informatics is rooted in collecting accurate healthcare quality data, analyzing those data, and applying findings toward quality improvement programs ([Fig. 1]). Coordination of this work allows clinicians, analysts, and researchers to unify, align, and share in the work of connecting large-scale data with improvement in healthcare delivery. These efforts complement and contribute to parallel efforts to using EHR data for clinical decision support, research, and public health.[8] [9] [10]

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Fig. 1 The work, tools, challenges, and opportunities of quality informatics.

This letter outlines why quality informatics should be recognized, provides an overview of the work of quality informatics, and describes the opportunities and challenges facing the work. Electronic clinical quality measures (eCQMs), part of the Centers for Medicare and Medicaid Services (CMS) Promoting Interoperability EHR Incentive Program, will serve as an exemplar of quality informatics in practice.[11]

Protection of Human and Animal Subjects

Human and/or animal subjects were not included in the project.