Evidence map›Paper›PMID 30357777›Full record

ArticleApplied clinical informatics2018

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

Dean J Karavite, Matthew W Miller, Mark J Ramos, Susan L Rettig, Rachael K Ross, Rui Xiao, Naveen Muthu, A Russell Localio, Jeffrey S Gerber, Susan E Coffin and 1 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Dean J KaraviteDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Matthew W MillerDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Mark J RamosDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Susan L RettigDepartment of Infection Prevention and Control, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Rachael K RossDivision of Infectious Disease, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Rui XiaoDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Naveen MuthuDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
A Russell LocalioDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Jeffrey S GerberDivision of Infectious Disease, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Susan E CoffinDivision of Infectious Disease, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Robert W GrundmeierDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.

Funding

Electronic Surveillance for Wound Infections after Ambulatory Pediatric SurgeryR01HS020921 · AHRQ · CHILDREN'S HOSP OF PHILADELPHIA · PI COFFIN, SUSAN MD · 2011 to 2015
$2.5M
AHRQ HHS R01 HS020921
6 · The paper itself

Abstract

backgroundSurveillance 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.

objectiveThis article compares the Workbench and EHR on four dimensions: (1) effectiveness, (2) efficiency, (3) workload, and (4) usability.

methodsComparative 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.

resultsEight 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,

conclusionCompared 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.

Indexed as

Ambulatory CareChildElectronic Health RecordsFemaleHumansMaleMedical InformaticsSurgical Wound Infection

Identifiers

PMID30357777
PMCPMC6200553

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.