Literature DB >> 30357777

User Testing an Information Foraging Tool for Ambulatory Surgical Site Infection Surveillance.

Dean J Karavite1, Matthew W Miller1, Mark J Ramos1, Susan L Rettig2, Rachael K Ross3, Rui Xiao4, Naveen Muthu1,5, A Russell Localio4, Jeffrey S Gerber3,5, Susan E Coffin3,5, Robert W Grundmeier1,5.   

Abstract

BACKGROUND: Surveillance for surgical site infections (SSIs) after ambulatory surgery in children requires a detailed manual chart review to assess criteria defined by the National Health and Safety Network (NHSN). Electronic health records (EHRs) impose an inefficient search process where infection preventionists must manually review every postsurgical encounter (< 30 days). Using text mining and business intelligence software, we developed an information foraging application, the SSI Workbench, to visually present which postsurgical encounters included SSI-related terms and synonyms, antibiotic, and culture orders.
OBJECTIVE: This article compares the Workbench and EHR on four dimensions: (1) effectiveness, (2) efficiency, (3) workload, and (4) usability.
METHODS: Comparative usability test of Workbench and EHR. Objective test metrics are time per case, encounters reviewed per case, time per encounter, and retrieval of information meeting NHSN definitions. Subjective measures are cognitive load using the National Aeronautics and Space Administration (NASA) Task Load Index (NASA TLX), and a questionnaire on system usability and utility.
RESULTS: Eight infection preventionists participated in the test. There was no difference in effectiveness as subjects retrieved information from all cases, using both systems, to meet the NHSN criteria. There was no difference in efficiency in time per case between the Workbench and EHR (8.58 vs. 7.39 minutes, p = 0.36). However, with the Workbench subjects opened fewer encounters per case (3.0 vs. 7.5, p = 0.002), spent more time per encounter (2.23 vs. 0.92 minutes, p = 0.002), rated the Workbench lower in cognitive load (NASA TLX, 24 vs. 33, p = 0.02), and significantly higher in measures of usability.
CONCLUSION: Compared with the EHR, the Workbench was more usable, short, and reduced cognitive load. In overall efficiency, the Workbench did not save time, but demonstrated a shift from between-encounter foraging to within-encounter foraging and was rated as significantly more efficient. Our results suggest that infection surveillance can be better supported by systems applying information foraging theory. Georg Thieme Verlag KG Stuttgart · New York.

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Year:  2018        PMID: 30357777      PMCID: PMC6200553          DOI: 10.1055/s-0038-1675179

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  9 in total

1.  Identifying surgical site infections in electronic health data using predictive models.

Authors:  Robert W Grundmeier; Rui Xiao; Rachael K Ross; Mark J Ramos; Dean J Karavite; Jeremy J Michel; Jeffrey S Gerber; Susan E Coffin
Journal:  J Am Med Inform Assoc       Date:  2018-09-01       Impact factor: 4.497

Review 2.  Data requirements for electronic surveillance of healthcare-associated infections.

Authors:  Keith F Woeltje; Michael Y Lin; Michael Klompas; Marc Oliver Wright; Gianna Zuccotti; William E Trick
Journal:  Infect Control Hosp Epidemiol       Date:  2014-09       Impact factor: 3.254

3.  Quality assessment of hospital discharge database for routine surveillance of hip and knee arthroplasty-related infections.

Authors:  Leslie Grammatico-Guillon; Sabine Baron; Christophe Gaborit; Emmanuel Rusch; Pascal Astagneau
Journal:  Infect Control Hosp Epidemiol       Date:  2014-04-22       Impact factor: 3.254

4.  Estimating health care-associated infections and deaths in U.S. hospitals, 2002.

Authors:  R Monina Klevens; Jonathan R Edwards; Chesley L Richards; Teresa C Horan; Robert P Gaynes; Daniel A Pollock; Denise M Cardo
Journal:  Public Health Rep       Date:  2007 Mar-Apr       Impact factor: 2.792

5.  The effect of two different electronic health record user interfaces on intensive care provider task load, errors of cognition, and performance.

Authors:  Adil Ahmed; Subhash Chandra; Vitaly Herasevich; Ognjen Gajic; Brian W Pickering
Journal:  Crit Care Med       Date:  2011-07       Impact factor: 7.598

Review 6.  Automated surveillance for healthcare-associated infections: opportunities for improvement.

Authors:  Maaike S M van Mourik; Annet Troelstra; Wouter W van Solinge; Karel G M Moons; Marc J M Bonten
Journal:  Clin Infect Dis       Date:  2013-03-26       Impact factor: 9.079

Review 7.  Consensus paper on the surveillance of surgical wound infections. The Society for Hospital Epidemiology of America; The Association for Practitioners in Infection Control; The Centers for Disease Control; The Surgical Infection Society.

Authors: 
Journal:  Infect Control Hosp Epidemiol       Date:  1992-10       Impact factor: 3.254

8.  Cognitive and usability engineering methods for the evaluation of clinical information systems.

Authors:  Andre W Kushniruk; Vimla L Patel
Journal:  J Biomed Inform       Date:  2004-02       Impact factor: 6.317

9.  The scientific basis for using surveillance and risk factor data to reduce nosocomial infection rates.

Authors:  R W Haley
Journal:  J Hosp Infect       Date:  1995-06       Impact factor: 3.926

  9 in total
  3 in total

1.  Visualizing Infection Surveillance Data for Policymaking Using Open Source Dashboarding.

Authors:  Monika Maya Wahi; Natasha Dukach
Journal:  Appl Clin Inform       Date:  2019-07-24       Impact factor: 2.342

2.  Prevention of Surgical Site Infections in Neonates and Children: Non-Pharmacological Measures of Prevention.

Authors:  Aniello Meoli; Lorenzo Ciavola; Sofia Rahman; Marco Masetti; Tommaso Toschetti; Riccardo Morini; Giulia Dal Canto; Cinzia Auriti; Caterina Caminiti; Elio Castagnola; Giorgio Conti; Daniele Donà; Luisa Galli; Stefania La Grutta; Laura Lancella; Mario Lima; Andrea Lo Vecchio; Gloria Pelizzo; Nicola Petrosillo; Alessandro Simonini; Elisabetta Venturini; Fabio Caramelli; Gaetano Domenico Gargiulo; Enrico Sesenna; Rossella Sgarzani; Claudio Vicini; Mino Zucchelli; Fabio Mosca; Annamaria Staiano; Nicola Principi; Susanna Esposito
Journal:  Antibiotics (Basel)       Date:  2022-06-27

3.  Novel Method to Flag Cardiac Implantable Device Infections by Integrating Text Mining With Structured Data in the Veterans Health Administration's Electronic Medical Record.

Authors:  Hillary J Mull; Kelly L Stolzmann; Marlena H Shin; Emily Kalver; Marin L Schweizer; Westyn Branch-Elliman
Journal:  JAMA Netw Open       Date:  2020-09-01
  3 in total

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