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

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

Author information

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.

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.

[Indexed for MEDLINE]

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