Clinical decision support systems and infection prevention: to know is not enough.

Clinical decision support (CDS) systems are an increasingly used form of technology designed to guide health care providers toward established protocols and best practices with the intent of improving patient care. Utilization of CDS for infection prevention is not widespread and is particularly focused on antimicrobial stewardship. This article provides an overview of CDS systems and summarizes key attributes of successfully executed tools. A selection of published reports of CDS for infection prevention and antimicrobial stewardship are described. Finally, an individual organization describes its CDS infrastructure, process of prioritization, design, and development, with selected highlights of CDS tools specifically targeting common infection prevention quality improvement initiatives.

[1]  R. Scott Evans,et al.  Application of Information Technology: Rapid Identification of Hospitalized Patients at High Risk for MRSA Carriage , 2008, J. Am. Medical Informatics Assoc..

[2]  Matthew H Samore,et al.  Clinical decision support and appropriateness of antimicrobial prescribing: a randomized trial. , 2005, JAMA.

[3]  Margaret Williamson,et al.  Computerized clinical decision support for prescribing: provision does not guarantee uptake. , 2010, Journal of the American Medical Informatics Association : JAMIA.

[4]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[5]  R. Kullar,et al.  The "epic" challenge of optimizing antimicrobial stewardship: the role of electronic medical records and technology. , 2013, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[6]  J. Beaumont,et al.  Reporting Catheter-Associated Urinary Tract Infections: Denominator Matters , 2011, Infection Control & Hospital Epidemiology.

[7]  G. Stoddard,et al.  Clinical Decision Support and Appropriateness of Antimicrobial Prescribing , 2011 .

[8]  Jonathan M. Teich,et al.  Grand challenges in clinical decision support , 2008, J. Biomed. Informatics.

[9]  Jennifer L. Beaumont,et al.  Electronic Prediction Rules for Methicillin-Resistant Staphylococcus aureus Colonization , 2011, Infection Control & Hospital Epidemiology.

[10]  David Classen,et al.  Implementing Antibiotic Practice Guidelines through Computer-Assisted Decision Support: Clinical and Financial Outcomes , 1996, Annals of Internal Medicine.

[11]  B. French,et al.  Usability and Impact of a Computerized Clinical Decision Support Intervention Designed to Reduce Urinary Catheter Utilization and Catheter-Associated Urinary Tract Infections , 2014, Infection Control & Hospital Epidemiology.

[12]  J. Marc Overhage,et al.  Details of a Successful Clinical Decision Support System , 2007, AMIA.

[13]  A Majeed,et al.  Computerised decision support systems for healthcare professionals , 2013 .

[14]  Cynthia LeRouge,et al.  A nursing clinical decision support system and potential predictors of head-of-bed position for patients receiving mechanical ventilation. , 2010, American journal of critical care : an official publication, American Association of Critical-Care Nurses.

[15]  L. Hayden,et al.  Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality , 2011 .

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

[17]  E. Larson,et al.  Electronic surveillance systems in infection prevention: organizational support, program characteristics, and user satisfaction. , 2010, American journal of infection control.

[18]  Adam Wright,et al.  A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success , 2013, J. Am. Medical Informatics Assoc..

[19]  Randolph A. Miller,et al.  Focus on health information technology, electronic health records and their financial impact: A framework for evaluating the appropriateness of clinical decision support alerts and responses , 2012, J. Am. Medical Informatics Assoc..

[20]  Clinical decision support systems use in Wisconsin. , 2007, WMJ : official publication of the State Medical Society of Wisconsin.

[21]  Arch G. Mainous,et al.  Impact of a clinical decision support system on antibiotic prescribing for acute respiratory infections in primary care: quasi-experimental trial , 2013, J. Am. Medical Informatics Assoc..

[22]  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.

[23]  H. Warner,et al.  A mathematical approach to medical diagnosis. Application to congenital heart disease. , 1961, JAMA.

[24]  D. Bell,et al.  A Retrospective Analysis of Interruptive versus Non-interruptive Clinical Decision Support for Identification of Patients Needing Contact Isolation , 2013, Applied Clinical Informatics.

[25]  George Hripcsak,et al.  Automated Real-Time Detection and Notification of Positive Infection Cases , 2006, AMIA.

[26]  Charles E. Leonard,et al.  Unintended effects of a computerized physician order entry nearly hard-stop alert to prevent a drug interaction: a randomized controlled trial. , 2010, Archives of internal medicine.

[27]  C. McDonald.  Protocol-based computer reminders, the quality of care and the non-perfectability of man. , 1976, The New England journal of medicine.