Evidence map›Paper›PMID 28050715›Full record

ArticleJournal of digital imaging2017

Workflow Lexicons in Healthcare: Validation of the SWIM Lexicon.

Chris Meenan, Bradley Erickson, Nancy Knight, Jewel Fossett, Elizabeth Olsen, Prerna Mohod, Joseph Chen, Steve G Langer

Abstract readValidation Study
In one paragraph

Article in Journal of digital imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Improving Triage of After-Hours Radiology Examinations Through Worklist Unification.Journal of the American College of Radiology : JACR · 2020
    Article
  3. Review
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

8 authors.

Chris MeenanDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Bradley EricksonMayo Clinic Radiology, Rochester, MN, USA.
Nancy KnightDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
Jewel FossettDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Elizabeth OlsenDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Prerna MohodUniversity of Maryland Medical Center, Baltimore, MD, USA.
Joseph ChenDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Steve G LangerMayo Clinic Radiology, Rochester, MN, USA. Langer.steve@mayo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For clinical departments seeking to successfully navigate the challenges of modern health reform, obtaining access to operational and clinical data to establish and sustain goals for improving quality is essential. More broadly, health delivery organizations are also seeking to understand performance across multiple facilities and often across multiple electronic medical record (EMR) systems. Interpreting operational data across multiple vendor systems can be challenging, as various manufacturers may describe different departmental workflow steps in different ways and sometimes even within a single vendor's installed customer base. In 2012, The Society for Imaging Informatics in Medicine (SIIM) recognized the need for better quality and performance data standards and formed SIIM's Workflow Initiative for Medicine (SWIM), an initiative designed to consistently describe workflow steps in radiology departments as well as defining operational quality metrics. The SWIM lexicon was published as a working model to describe operational workflow steps and quality measures. We measured the prevalence of the SWIM lexicon workflow steps in both academic and community radiology environments using real-world patient observations and correlated that information with automatically captured workflow steps from our clinical information systems. Our goal was to measure frequency of occurrence of workflow steps identified by the SWIM lexicon in a real-world clinical setting, as well as to correlate how accurately departmental information systems captured patient flow through our health facility.

Indexed as

ChecklistRadiology Department, HospitalVocabularyWorkflowDelivery of Health CareHumansMedical RecordsComputer systemsControlled vocabularyData mining

Identifiers

PMID28050715
PMCPMC5422228

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.