Computer-Assisted Decision Support for Changing Practice in Severe Sepsis and Septic Shock

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.

[1]  M. Levy,et al.  Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2008 , 2007, Intensive Care Medicine.

[2]  Mitchell M. Levy,et al.  Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock , 2004, Critical care medicine.

[3]  M. Levy,et al.  Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2008 , 2007, Intensive Care Medicine.

[4]  M. Levy,et al.  Improvement in process of care and outcome after a multicenter severe sepsis educational program in Spain. , 2008, JAMA.

[5]  R. Wears,et al.  Computer technology and clinical work: still waiting for Godot. , 2005, JAMA.

[6]  F Doyon,et al.  Incidence, risk factors, and outcome of severe sepsis and septic shock in adults. A multicenter prospective study in intensive care units. French ICU Group for Severe Sepsis. , 1995, JAMA.

[7]  J M Hughes,et al.  CDC definitions for nosocomial infections, 1988. , 1988, American journal of infection control.

[8]  K. Wernecke,et al.  Impact of adherence to standard operating procedures for pneumonia on outcome of intensive care unit patients* , 2009, Critical care medicine.

[9]  Jesús Blanco,et al.  Incidence, organ dysfunction and mortality in severe sepsis: a Spanish multicentre study , 2008, Critical care.

[10]  S. Michie,et al.  Interventions to improve antibiotic prescribing practices for hospital inpatients. , 2017, The Cochrane database of systematic reviews.

[11]  CDC definitions for nosocomial infections, 1988. , 1989, The American review of respiratory disease.

[12]  J. Stockman,et al.  Clinical Decision Support and Appropriateness of Antimicrobial Prescribing: A Randomized Trial , 2007 .

[13]  J. Vincent,et al.  Classification, incidence, and outcomes of sepsis and multiple organ failure. , 2007, Contributions to nephrology.

[14]  H. Mcdonald,et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. , 2005, JAMA.

[15]  J. Vincent,et al.  Clinical review: Scoring systems in the critically ill , 2010, Critical care.

[16]  T. Clemmer,et al.  A computer-assisted management program for antibiotics and other antiinfective agents. , 1998, The New England journal of medicine.

[17]  R. Wigton,et al.  Prediction of Community-Acquired Pneumonia Using Artificial Neural Networks , 2003, Medical decision making : an international journal of the Society for Medical Decision Making.

[18]  M. Bonten,et al.  treatment of , 2004 .

[19]  François Gouin,et al.  Incidence, Risk Factors, and Outcome of Severe Sepsis and Septic Shock in Adults: A Multicenter Prospective Study in Intensive Care Units , 1995 .

[20]  Daniel Talmor,et al.  Implementation and outcomes of the Multiple Urgent Sepsis Therapies (MUST) protocol* , 2006, Critical care medicine.

[21]  J. A. Kruse,et al.  The influence of early hemodynamic optimization on biomarker patterns of severe sepsis and septic shock* , 2007, Critical care medicine.

[22]  C. Spies,et al.  Adherence to Standard Operating Procedures is Crucial for Intensive Care Unit Survival of Elderly Patients , 2008, The Journal of international medical research.

[23]  D. Nathwani,et al.  Navigating the Web in search of resources on antimicrobial stewardship in health care institutions. , 2009, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[24]  Ricard Ferrer,et al.  Effectiveness of treatments for severe sepsis: a prospective, multicenter, observational study. , 2009, American journal of respiratory and critical care medicine.

[25]  Eli N. Perencevich,et al.  Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use: a randomized controlled trial. , 2006, Journal of the American Medical Informatics Association : JAMIA.

[26]  M. Deja.  Anhang zu Strategien für die Verordnung von Antibiotika in der Intensivmedizin: Standards für die mikrobiologische Diagnostik , 2007 .

[27]  K. Wood,et al.  Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock* , 2006, Critical care medicine.

[28]  A. Morris.  Rational use of computerized protocols in the intensive care unit , 2001, Critical care.

[29]  G. Clermont,et al.  Epidemiology of severe sepsis in the United States: Analysis of incidence, outcome, and associated costs of care , 2001, Critical care medicine.

[30]  Enrico W. Coiera,et al.  Application of Information Technology: Handheld Computer-based Decision Support Reduces Patient Length of Stay and Antibiotic Prescribing in Critical Care , 2005, J. Am. Medical Informatics Assoc..

[31]  A. Morris,et al.  Pro/con debate: Should antimicrobial stewardship programs be adopted universally in the intensive care unit? , 2010, Critical care.