Literature DB >> 25741959

Reduction in time to first action as a result of electronic alerts for early sepsis recognition.

Lisa Kurczewski1, Michael Sweet, Richard McKnight, Kevin Halbritter.   

Abstract

The use of an electronic alerting system to notify practitioners when a patient meets modified systemic inflammatory response syndrome criteria was hypothesized to decrease the time to goal-directed therapy initiation. This retrospective, before-and-after study analyzed adult patients identified with sepsis or septic shock and compared 30 patients prior to electronic alert initiation with 30 patients after initiation. The primary endpoint was time to any sepsis-related intervention. Patients in the post-alert group demonstrated a shorter time to any sepsis-related intervention by a median difference of 3.5 hours (P = .02). Using computerized medical records to create an electronic alerting system has the potential to identify high-risk patients and initiate interventions sooner. At our institution, the creation of an alerting system with real-time data has decreased the time it takes to begin sepsis workup and treatment.

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Mesh:

Year:  2015        PMID: 25741959     DOI: 10.1097/CNQ.0000000000000060

Source DB:  PubMed          Journal:  Crit Care Nurs Q        ISSN: 0887-9303


  8 in total

1.  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

2.  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

3.  The Nature and Variability of Automated Practice Alerts Derived from Electronic Health Records in a U.S. Nationwide Critical Care Research Network.

Authors:  Cody Benthin; Sonal Pannu; Akram Khan; Michelle Gong
Journal:  Ann Am Thorac Soc       Date:  2016-10

Review 4.  Multi-Omics Techniques Make it Possible to Analyze Sepsis-Associated Acute Kidney Injury Comprehensively.

Authors:  Jiao Qiao; Liyan Cui
Journal:  Front Immunol       Date:  2022-07-07       Impact factor: 8.786

Review 5.  Identifying Patients With Sepsis on the Hospital Wards.

Authors:  Poushali Bhattacharjee; Dana P Edelson; Matthew M Churpek
Journal:  Chest       Date:  2016-07-01       Impact factor: 9.410

6.  An electronic warning system helps reduce the time to diagnosis of sepsis.

Authors:  Glauco Adrieno Westphal; Aline Braz Pereira; Silvia Maria Fachin; Geonice Sperotto; Maurício Gonçalves; Lucimeri Albino; Rodolfo Bittencourt; Vanessa de Rossi Franzini; Álvaro Koenig
Journal:  Rev Bras Ter Intensiva       Date:  2018-12-13

Review 7.  Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review.

Authors:  Khalia Ackermann; Jannah Baker; Malcolm Green; Mary Fullick; Hilal Varinli; Johanna Westbrook; Ling Li
Journal:  J Med Internet Res       Date:  2022-02-23       Impact factor: 7.076

8.  Systematic screening is essential for early diagnosis of severe sepsis and septic shock.

Authors:  Glauco Adrieno Westphal; Adriana Silva Lino
Journal:  Rev Bras Ter Intensiva       Date:  2015 Apr-Jun
  8 in total

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