Literature DB >> 21309474

Computer-assisted decision support for changing practice in severe sepsis and septic shock.

S Tafelski1, I Nachtigall, M Deja, A Tamarkin, T Trefzer, E Halle, K D Wernecke, C Spies.   

Abstract

Computer-assisted decision support systems (CDSS) are designed to improve infection management. The aim of this prospective, clinical pre- and post-intervention study was to investigate the influence of CDSS on infection management of severe sepsis and septic shock in intensive care units (ICUs). Data were collected for a total of 180 days during two study periods in 2006 and 2007. Of the 186 patients with severe sepsis or septic shock, 62 were stratified into a low adherence to infection management standards group (LAG) and 124 were stratified into a high adherence group (HAG). ICU mortality was significantly increased in LAG versus HAG patients (Kaplan-Meier analysis). Following CDSS implementation, adherence to standards increased significantly by 35%, paralleled with improved diagnostics, more antibiotic-free days and a shortened time until antibiotics were administered. In conclusion, adherence to infection standards is beneficial for patients with severe sepsis or septic shock and CDSS is a useful tool to aid adherence.

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Year:  2010        PMID: 21309474     DOI: 10.1177/147323001003800505

Source DB:  PubMed          Journal:  J Int Med Res        ISSN: 0300-0605            Impact factor:   1.671


  10 in total

1.  An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Authors:  Shamim Nemati; Andre Holder; Fereshteh Razmi; Matthew D Stanley; Gari D Clifford; Timothy G Buchman
Journal:  Crit Care Med       Date:  2018-04       Impact factor: 7.598

Review 2.  Computerized decision support in adult and pediatric critical care.

Authors:  Cydni N Williams; Susan L Bratton; Eliotte L Hirshberg
Journal:  World J Crit Care Med       Date:  2013-11-04

Review 3.  The impact of digital interventions on antimicrobial stewardship in hospitals: a qualitative synthesis of systematic reviews.

Authors:  Bethany A Van Dort; Jonathan Penm; Angus Ritchie; Melissa T Baysari
Journal:  J Antimicrob Chemother       Date:  2022-06-29       Impact factor: 5.758

4.  Standard operating procedures for antibiotic therapy and the occurrence of acute kidney injury: a prospective, clinical, non-interventional, observational study.

Authors:  Irit Nachtigall; Sascha Tafelski; Karsten Günzel; Alexander Uhrig; Robert Powollik; Andrey Tamarkin; Klaus D Wernecke; Claudia Spies
Journal:  Crit Care       Date:  2014-06-12       Impact factor: 9.097

Review 5.  The effectiveness of computerised decision support on antibiotic use in hospitals: A systematic review.

Authors:  Christopher E Curtis; Fares Al Bahar; John F Marriott
Journal:  PLoS One       Date:  2017-08-24       Impact factor: 3.240

6.  Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning.

Authors:  Steven Horng; David A Sontag; Yoni Halpern; Yacine Jernite; Nathan I Shapiro; Larry A Nathanson
Journal:  PLoS One       Date:  2017-04-06       Impact factor: 3.240

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

Review 8.  Systematic review of clinical decision support interventions with potential for inpatient cost reduction.

Authors:  Christopher L Fillmore; Bruce E Bray; Kensaku Kawamoto
Journal:  BMC Med Inform Decis Mak       Date:  2013-12-17       Impact factor: 2.796

9.  Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age.

Authors:  Angela L P Chow; David C Lye; Onyebuchi A Arah
Journal:  Sci Rep       Date:  2015-11-30       Impact factor: 4.379

10.  Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact.

Authors:  Matthew I Hwang; William F Bond; Emilie S Powell
Journal:  West J Emerg Med       Date:  2020-08-24
  10 in total

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