Yearb Med Inform 2013; 22(01): 13-19
DOI: 10.1055/s-0038-1638827
Original Article
Georg Thieme Verlag KG Stuttgart

State of the Art in Clinical Informatics: Evidence and Examples

A. B. McCoy
1  The University of Texas School of Biomedical Informatics at Houston, Houston, Texas, USA
A. Wright
2  Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
G. Eysenbach
3  University Health Network, Techna Institute, Toronto & Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
B. A. Malin
4  Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, Tennessee, USA
5  Department of Electrical Engineering and Computer Science, School of Engineering, Vanderbilt University, Nashville, Tennessee, USA
E. S. Patterson
6  School of Health and Rehabilitation Sciences, College of Medicine, The Ohio State University, Columbus, Ohio, USA
H. Xu
1  The University of Texas School of Biomedical Informatics at Houston, Houston, Texas, USA
D. F. Sittig
1  The University of Texas School of Biomedical Informatics at Houston, Houston, Texas, USA
› Author Affiliations
Further Information

Publication History

Publication Date:
05 March 2018 (online)


Objective: The field of clinical informatics has expanded substantially in the six decades since its inception. Early research focused on simple demonstrations that health information technology (HIT) such as electronic health records (EHRs), computerized provider order entry (CPOE), and clinical decision support (CDS) systems were feasible and potentially beneficial in clinical practice.

Methods: In this review, we present recent evidence on clinical informatics in the United States covering three themes: 1) clinical informatics systems and interventions for providers, including EHRs, CPOE, CDS, and health information exchange; 2) consumer health informatics systems, including personal health records and web-based and mobile HIT; and 3) methods and governance for clinical informatics, including EHR usability; data mining, text mining, natural language processing, privacy, and security.

Results: Substantial progress has been made in demonstrating that various clinical informatics methodologies and applications improve the structure, process, and outcomes of various facets of the healthcare system.

Conclusion: Over the coming years, much more will be expected from the field. As we move past the “early adopters” in Rogers' diffusion of innovations' curve through the “early majority” and into the “late majority,” there will be a crucial need for new research methodologies and clinical applications that have been rigorously demonstrated to work (i.e., to improve health outcomes) in multiple settings with different types of patients and clinicians.