Literature DB >> 30854401

Assessment of Nursing Response to a Real-Time Alerting Tool for Sepsis: A Provider Survey.

Kristen Miller1, Rebecca Kowalski2, Muge Capan2, Pan Wu2, Danielle Mosby1, Ryan Arnold2.   

Abstract

Background: An information technology solution to provide a real-time alert to the nursing staff is necessary to assist in identifying patients who may have sepsis and avoid the devastating effects of its late recognition. The objective of this study is to evaluate the perception and adoption of sepsis clinical decision support.
Methods: A cross-sectional survey over a three-week period in 2015 was conducted in a major tertiary care facility. A sepsis alert was launched into five pilot units (including: surgery, medical-ICU, step-down, general medicine, and oncology). The pilot unit providers consisted of nurses from five inpatient units. Frequency, summary statistics, Chi-square, and nonparametric Kendall tests were used to determine the significance of the association and correlation between six evaluation domains.
Results: A total of 151 nurses responded (53% response rate). Questions included in the survey addressed the following domains: usability, accuracy, impact on workload, improved performance, provider preference, and physician response. The level of agreeability regarding physician response was significantly different between units (p=0.0136). There were significant differences for improved performance (p=0.0068) and physician response (p=0.0503) across levels of exposure to the alert. The strongest correlations were between questions related to usability and the domains of: accuracy (τ=0.64), performance (τ=0.66), and provider preference (τ=0.62), as well as, between the domains of: provider performance and provider preference (τ=0.67). Discussion: Performance and preference of providers were evaluated to identify strengths and weaknesses of the sepsis alert. Effective presentation of the alert, including how and what is displayed, may offer better cognitive support in identifying and treating septic patients.

Entities:  

Keywords:  Sepsis; alert; clinical decision support tool; usability testing

Year:  2017        PMID: 30854401      PMCID: PMC6402839          DOI: 10.24150/ajhm/2017.021

Source DB:  PubMed          Journal:  Am J Hosp Med        ISSN: 2474-7017


  15 in total

1.  Clinical decision support systems for the practice of evidence-based medicine.

Authors:  I Sim; P Gorman; R A Greenes; R B Haynes; B Kaplan; H Lehmann; P C Tang
Journal:  J Am Med Inform Assoc       Date:  2001 Nov-Dec       Impact factor: 4.497

Review 2.  Surviving severe sepsis: early recognition and treatment.

Authors:  Tom Ahrens; Deborah Tuggle
Journal:  Crit Care Nurse       Date:  2004-10       Impact factor: 1.708

3.  Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Authors:  Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde
Journal:  J Biomed Inform       Date:  2008-09-30       Impact factor: 6.317

4.  Joint commission warns of alarm fatigue: multitude of alarms from monitoring devices problematic.

Authors:  Mike Mitka
Journal:  JAMA       Date:  2013-06-12       Impact factor: 56.272

5.  Monitor alarm fatigue: standardizing use of physiological monitors and decreasing nuisance alarms.

Authors:  Kelly Creighton Graham; Maria Cvach
Journal:  Am J Crit Care       Date:  2010-01       Impact factor: 2.228

6.  Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis.

Authors:  Jessica L Nelson; Barbara L Smith; Jeremy D Jared; John G Younger
Journal:  Ann Emerg Med       Date:  2011-01-12       Impact factor: 5.721

Review 7.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference.

Authors:  Mitchell M Levy; Mitchell P Fink; John C Marshall; Edward Abraham; Derek Angus; Deborah Cook; Jonathan Cohen; Steven M Opal; Jean-Louis Vincent; Graham Ramsay
Journal:  Crit Care Med       Date:  2003-04       Impact factor: 7.598

8.  Hospital deaths in patients with sepsis from 2 independent cohorts.

Authors:  Vincent Liu; Gabriel J Escobar; John D Greene; Jay Soule; Alan Whippy; Derek C Angus; Theodore J Iwashyna
Journal:  JAMA       Date:  2014-07-02       Impact factor: 56.272

9.  Assessing health care setting readiness for point of care computerized clinical decision support system innovations.

Authors:  R Snyder-Halpern
Journal:  Outcomes Manag Nurs Pract       Date:  1999 Jul-Sep

10.  A survey of factors affecting clinician acceptance of clinical decision support.

Authors:  Dean F Sittig; Michael A Krall; Richard H Dykstra; Allen Russell; Homer L Chin
Journal:  BMC Med Inform Decis Mak       Date:  2006-02-01       Impact factor: 2.796

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  2 in total

1.  Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis.

Authors:  Laura Schubel; Danielle L Mosby; Joseph Blumenthal; Muge Capan; Ryan Arnold; Rebecca Kowalski; F Jacob Seagull; Ken Catchpole; J Sanford Schwartz; Ella Franklin; Robin Littlejohn; Kristen E Miller
Journal:  Health Informatics J       Date:  2019-05-13       Impact factor: 2.681

Review 2.  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

  2 in total

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