Literature DB >> 30278956

Sooner is better: use of a real-time automated bedside dashboard improves sepsis care.

Andrew D Jung1, Jennifer Baker1, Christopher A Droege2, Vanessa Nomellini1, Jay Johannigman1, John B Holcomb3, Michael D Goodman1, Timothy A Pritts4.   

Abstract

BACKGROUND: Minimizing the interval between diagnosis of sepsis and administration of antibiotics improves patient outcomes. We hypothesized that a commercially available bedside clinical surveillance visualization system (BSV) would hasten antibiotic administration and decrease length of stay (LOS) in surgical intensive care unit (SICU) patients.
METHODS: A BSV, integrated with the electronic medical record and displayed at bedside, was implemented in our SICU in July 2016. A visual sepsis screen score (SSS) was added in July 2017. All patients admitted to SICU beds with bedside displays equipped with a BSV were analyzed to determine mean SSS, maximum SSS, time from positive SSS to antibiotic administration, SICU LOS, and mortality.
RESULTS: During the study period, 232 patients were admitted to beds equipped with the clinical surveillance visualization system. Thirty patients demonstrated positive SSS followed by confirmed sepsis (23 Pre-SSS versus 7 Post-SSS). Mean and maximum SSS were similar. Time from positive SSS to antibiotic administration was decreased in patients with a visual SSS (55.3 ± 15.5 h versus 16.2 ± 9.2 h; P < 0.05). ICU and hospital LOS was also decreased (P < 0.01).
CONCLUSIONS: Implementation of a visual SSS into a BSV led to a decreased time interval between the positive SSS and administration of antibiotics and was associated with shorter SICU and hospital LOS. Integration of a visual decision support system may help providers adhere to Surviving Sepsis Guidelines.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Antibiotic treatment; Clinical decision support tools; Guideline compliance; Sepsis; Sepsis screening score; Septic shock

Mesh:

Substances:

Year:  2018        PMID: 30278956     DOI: 10.1016/j.jss.2018.05.078

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  6 in total

1.  Effectiveness of automated alerting system compared to usual care for the management of sepsis.

Authors:  Zhongheng Zhang; Lin Chen; Ping Xu; Qing Wang; Jianjun Zhang; Kun Chen; Casey M Clements; Leo Anthony Celi; Vitaly Herasevich; Yucai Hong
Journal:  NPJ Digit Med       Date:  2022-07-19

2.  Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review.

Authors:  Terrence C Lee; Neil U Shah; Alyssa Haack; Sally L Baxter
Journal:  Informatics (MDPI)       Date:  2020-07-25

Review 3.  Identification of nutritional risk in the acute care setting: progress towards a practice and evidence informed systems level approach.

Authors:  Diane Chamberlain; Sebastian Doeltgen; Reegan Knowles; Alison Yaxley; Michelle Miller
Journal:  BMC Health Serv Res       Date:  2021-11-30       Impact factor: 2.655

Review 4.  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

5.  A Dashboard Prototype for Tracking the Impact of Diabetes on Hospital Readmissions Using a National Administrative Database.

Authors:  Timothy Wong; Ethan Y Brovman; Nikhilesh Rao; Mitchell H Tsai; Richard D Urman
Journal:  J Clin Med Res       Date:  2020-01-06

6.  The Use of Patient Monitoring Systems to Improve Sepsis Recognition and Outcomes: A Systematic Review.

Authors:  Bryan M Gale; Kendall K Hall
Journal:  J Patient Saf       Date:  2020-09       Impact factor: 2.243

  6 in total

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