Literature DB >> 21169824

Implementation of a real-time computerized sepsis alert in nonintensive care unit patients.

Amber M Sawyer1, Eli N Deal, Andrew J Labelle, Chad Witt, Steven W Thiel, Kevin Heard, Richard M Reichley, Scott T Micek, Marin H Kollef.   

Abstract

OBJECTIVE: Early therapy of sepsis involving fluid resuscitation and antibiotic administration has been shown to improve patient outcomes. A proactive tool to identify patients at risk for developing sepsis may decrease time to interventions and improve patient outcomes. The objective of this study was to evaluate whether the implementation of an automated sepsis screening and alert system facilitated early appropriate interventions.
DESIGN: Prospective, observational, pilot study.
SETTING: Six medicine wards in Barnes-Jewish Hospital, a 1250-bed academic medical center. PATIENTS: Patients identified by the sepsis screen while admitted to a medicine ward were included in the study. A total of 300 consecutive patients were identified comprising the nonintervention group (n=200) and the intervention group (n=100).
INTERVENTIONS: A real-time sepsis alert was implemented for the intervention group, which notified the charge nurse on the patient's hospital ward by text page.
MEASUREMENTS AND MAIN RESULTS: Within 12 hrs of the sepsis alert, interventions by the treating physicians were assessed, including new or escalated antibiotics, intravenous fluid administration, oxygen therapy, vasopressors, and diagnostic tests. After exclusion of patients without commitment to aggressive management, 181 patients in the nonintervention group and 89 patients in the intervention group were analyzed. Within 12 hrs of the sepsis alert, 70.8% of patients in the intervention group had received≥1 intervention vs. 55.8% in the nonintervention group (p=.018). Antibiotic escalation, intravenous fluid administration, oxygen therapy, and diagnostic tests were all increased in the intervention group. This was a single-center, institution- and patient-specific algorithm.
CONCLUSIONS: The sepsis alert developed at Barnes-Jewish Hospital was shown to increase early therapeutic and diagnostic interventions among nonintensive care unit patients at risk for sepsis.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21169824     DOI: 10.1097/CCM.0b013e318205df85

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  63 in total

1.  Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

Authors:  Joshua Rolnick; N Lance Downing; John Shepard; Weihan Chu; Julia Tam; Alexander Wessels; Ron Li; Brian Dietrich; Michael Rudy; Leon Castaneda; Lisa Shieh
Journal:  Appl Clin Inform       Date:  2016-06-22       Impact factor: 2.342

2.  Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Authors:  Jennifer C Ginestra; Heather M Giannini; William D Schweickert; Laurie Meadows; Michael J Lynch; Kimberly Pavan; Corey J Chivers; Michael Draugelis; Patrick J Donnelly; Barry D Fuchs; Craig A Umscheid
Journal:  Crit Care Med       Date:  2019-11       Impact factor: 7.598

3.  Development of a Multicenter Ward-Based AKI Prediction Model.

Authors:  Jay L Koyner; Richa Adhikari; Dana P Edelson; Matthew M Churpek
Journal:  Clin J Am Soc Nephrol       Date:  2016-09-15       Impact factor: 8.237

4.  Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward Patients.

Authors:  Matthew M Churpek; Frank J Zadravecz; Christopher Winslow; Michael D Howell; Dana P Edelson
Journal:  Am J Respir Crit Care Med       Date:  2015-10-15       Impact factor: 21.405

5.  Near-term prediction of sudden cardiac death in older hemodialysis patients using electronic health records.

Authors:  Benjamin A Goldstein; Tara I Chang; Aya A Mitani; Themistocles L Assimes; Wolfgang C Winkelmayer
Journal:  Clin J Am Soc Nephrol       Date:  2013-10-31       Impact factor: 8.237

6.  Investigating the Impact of Different Suspicion of Infection Criteria on the Accuracy of Quick Sepsis-Related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores.

Authors:  Matthew M Churpek; Ashley Snyder; Sarah Sokol; Natasha N Pettit; Dana P Edelson
Journal:  Crit Care Med       Date:  2017-11       Impact factor: 7.598

7.  Development, implementation, and impact of an automated early warning and response system for sepsis.

Authors:  Craig A Umscheid; Joel Betesh; Christine VanZandbergen; Asaf Hanish; Gordon Tait; Mark E Mikkelsen; Benjamin French; Barry D Fuchs
Journal:  J Hosp Med       Date:  2014-09-26       Impact factor: 2.960

8.  Triage sepsis alert and sepsis protocol lower times to fluids and antibiotics in the ED.

Authors:  Geoffrey E Hayden; Rachel E Tuuri; Rachel Scott; Joseph D Losek; Aaron M Blackshaw; Andrew J Schoenling; Paul J Nietert; Greg A Hall
Journal:  Am J Emerg Med       Date:  2015-08-28       Impact factor: 2.469

9.  Risk factors for acute kidney injury in older adults with critical illness: a retrospective cohort study.

Authors:  Sandra L Kane-Gill; Florentina E Sileanu; Raghavan Murugan; Gregory S Trietley; Steven M Handler; John A Kellum
Journal:  Am J Kidney Dis       Date:  2014-12-06       Impact factor: 8.860

Review 10.  A Review of Predictive Analytics Solutions for Sepsis Patients.

Authors:  Andrew K Teng; Adam B Wilcox
Journal:  Appl Clin Inform       Date:  2020-05-27       Impact factor: 2.342

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.