Impact of an Electronic Clinical Decision Support Tool for Emergency Department Patients With Pneumonia

Nathan C Dean; Barbara E Jones; Jason P Jones; Jeffrey P Ferraro; Herman B Post; Dominik Aronsky; Caroline G Vines; Todd L Allen; Peter J Haug

doi:10.1016/j.annemergmed.2015.02.003

Impact of an Electronic Clinical Decision Support Tool for Emergency Department Patients With Pneumonia

Ann Emerg Med. 2015 Nov;66(5):511-20. doi: 10.1016/j.annemergmed.2015.02.003. Epub 2015 Feb 26.

Authors

Nathan C Dean¹, Barbara E Jones², Jason P Jones³, Jeffrey P Ferraro⁴, Herman B Post⁴, Dominik Aronsky⁵, Caroline G Vines⁶, Todd L Allen⁷, Peter J Haug⁴

Affiliations

¹ Division of Pulmonary and Critical Care Medicine, Intermountain Medical Center, Murray, UT; Division of Respiratory, Critical Care and Occupational Pulmonary Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT. Electronic address: nathan.dean@imail.org.
² Division of Respiratory, Critical Care and Occupational Pulmonary Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT.
³ Clinical Intelligence and Decision Support-Kaiser Permanente, Pasadena, CA.
⁴ Homer Warner Center for Informatics Research, Murray, UT.
⁵ Department of Biomedical Informatics, Vanderbilt University, Nashville, TN.
⁶ Department of Emergency Medicine, Intermountain Medical Center, Murray, UT.
⁷ Department of Emergency Medicine, Intermountain Medical Center, Murray, UT; Institute for Healthcare Delivery and Research, Intermountain Healthcare, Salt Lake City, UT.

PMID: 25725592
DOI: 10.1016/j.annemergmed.2015.02.003

Abstract

Study objective: Despite evidence that guideline adherence improves clinical outcomes, management of pneumonia patients varies in emergency departments (EDs). We study the effect of a real-time, ED, electronic clinical decision support tool that provides clinicians with guideline-recommended decision support for diagnosis, severity assessment, disposition, and antibiotic selection.

Methods: This was a prospective, controlled, quasi-experimental trial in 7 Intermountain Healthcare hospital EDs in Utah's urban corridor. We studied adults with International Classification of Diseases, Ninth Revision codes and radiographic evidence for pneumonia during 2 periods: baseline (December 2009 through November 2010) and post-tool deployment (December 2011 through November 2012). The tool was deployed at 4 intervention EDs in May 2011, leaving 3 as usual care controls. We compared 30-day, all-cause mortality adjusted for illness severity, using a mixed-effect, logistic regression model.

Results: The study population comprised 4,758 ED pneumonia patients; 14% had health care-associated pneumonia. Median age was 58 years, 53% were female patients, and 59% were admitted to the hospital. Physicians applied the tool for 62.6% of intervention ED study patients. There was no difference overall in severity-adjusted mortality between intervention and usual care EDs post-tool deployment (odds ratio [OR]=0.69; 95% confidence interval [CI] 0.41 to 1.16). Post hoc analysis showed that patients with community-acquired pneumonia experienced significantly lower mortality (OR=0.53; 95% CI 0.28 to 0.99), whereas mortality was unchanged among patients with health care-associated pneumonia (OR=1.12; 95% CI 0.45 to 2.8). Patient disposition from the ED postdeployment adhered more to tool recommendations.

Conclusion: This study demonstrates the feasibility and potential benefit of real-time electronic clinical decision support for ED pneumonia patients.

Publication types

Multicenter Study
Research Support, Non-U.S. Gov't

MeSH terms

Community-Acquired Infections / diagnosis*
Community-Acquired Infections / mortality
Community-Acquired Infections / therapy*
Decision Support Systems, Clinical*
Electronic Health Records
Emergency Service, Hospital*
Female
Humans
Male
Middle Aged
Pneumonia / diagnosis*
Pneumonia / mortality
Pneumonia / therapy*
Prospective Studies
Severity of Illness Index
Utah / epidemiology