Volume 8, Issue 5 p. 236-242
Original Research

A trial of a real-time Alert for clinical deterioration in Patients hospitalized on general medical wards

Thomas C. Bailey MD

Corresponding Author

Thomas C. Bailey MD

Division of Infectious Diseases, Washington University School of Medicine, St. Louis, Missouri

Address for correspondence and reprint requests: Thomas Bailey, MD, Division of Infectious Diseases, Washington University School of Medicine, 660 S. Euclid Ave., Campus Box 8051, St. Louis, MO 63110; Telephone: 314-454-8293; Fax: 314-454-5392; E-mail: [email protected]Search for more papers by this author
Yixin Chen PhD

Yixin Chen PhD

School of Engineering and Applied Sciences, Washington University in St. Louis, St. Louis, Missouri

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Yi Mao

Yi Mao

School of Engineering and Applied Sciences, Washington University in St. Louis, St. Louis, Missouri

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Chenyang Lu PhD

Chenyang Lu PhD

School of Engineering and Applied Sciences, Washington University in St. Louis, St. Louis, Missouri

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Gregory Hackmann PhD

Gregory Hackmann PhD

School of Engineering and Applied Sciences, Washington University in St. Louis, St. Louis, Missouri

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Scott T. Micek PharmD

Scott T. Micek PharmD

Department of Pharmacy, Barnes-Jewish Hospital, St. Louis, Missouri

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Kevin M. Heard

Kevin M. Heard

Center for Clinical Excellence, BJC HealthCare, St. Louis, Missouri

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Kelly M. Faulkner

Kelly M. Faulkner

Center for Clinical Excellence, BJC HealthCare, St. Louis, Missouri

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Marin H. Kollef MD

Marin H. Kollef MD

Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, Missouri

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First published: 25 February 2013
Citations: 68

Abstract

BACKGROUND

With limited numbers of intensive care unit (ICU) beds available, increasing patient acuity is expected to contribute to episodes of inpatient deterioration on general wards.

OBJECTIVE

To prospectively validate a predictive algorithm for clinical deterioration in general–medical ward patients, and to conduct a trial of real-time alerts based on this algorithm.

DESIGN

Randomized, controlled crossover study.

SETTING/PATIENTS

Academic center with patients hospitalized on 8 general wards between July 2007 and December 2011.

INTERVENTIONS

Real-time alerts were generated by an algorithm designed to predict the need for ICU transfer using electronically available data. The alerts were sent by text page to the nurse manager on intervention wards.

MEASUREMENTS

Intensive care unit transfer, hospital mortality, and hospital length of stay.

RESULTS

Patients meeting the alert threshold were at nearly 5.3-fold greater risk of ICU transfer (95% confidence interval [CI]: 4.6-6.0) than those not satisfying the alert threshold (358 of 2353 [15.2%] vs 512 of 17678 [2.9%]). Patients with alerts were at 8.9-fold greater risk of death (95% CI: 7.4-10.7) than those without alerts (244 of 2353 [10.4%] vs 206 of 17678 [1.2%]). Among patients identified by the early warning system, there were no differences in the proportion of patients who were transferred to the ICU or who died in the intervention group as compared with the control group.

CONCLUSIONS

Real-time alerts were highly specific for clinical deterioration resulting in ICU transfer and death, and were associated with longer hospital length of stay. However, an intervention notifying a nurse of the risk did not result in improvement in these outcomes. Journal of Hospital Medicine 2013;8:236–242. © 2013 Society of Hospital Medicine