Evidence map›Paper›PMID 30134474›Full record

ArticleApplied clinical informatics2018

Mapping the Flow of Pediatric Trauma Patients Using Process Mining.

Ashimiyu B Durojaiye, Nicolette M McGeorge, Lisa L Puett, Dylan Stewart, James C Fackler, Peter L T Hoonakker, Harold P Lehmann, Ayse P Gurses

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 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Review
  9. Article
  10. A Comparative Process Mining Analysis of Road Trauma Patient Pathways.International journal of environmental research and public health · 2020
    Article
  11. Article
  12. Article
  13. Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  14. Article
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.

Ashimiyu B DurojaiyeDivision of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Nicolette M McGeorgeArmstrong Institute Center for Health Care Human Factors, Johns Hopkins Medicine, Baltimore, Maryland, United States.
Lisa L PuettDepartment of Pediatric Nursing, Johns Hopkins Hospital, Baltimore, Maryland, United States.
Dylan StewartDepartment of Pediatric Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
James C FacklerDivision of Pediatric Anesthesiology and Critical Care Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Peter L T HoonakkerCenter for Quality and Productivity Improvement, University of Wisconsin, Madison, Wisconsin, United States.
Harold P LehmannDivision of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Ayse P GursesDivision of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.

Funding

Care Transitions and Teamwork in Pediatric Trauma: Implications for HIT DesignR01HS023837 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI GURSES, AYSE PINAR · 2015 to 2019
$2.5M
AHRQ HHS R01 HS023837
6 · The paper itself

Abstract

backgroundInhospital pediatric trauma care typically spans multiple locations, which influences the use of resources, that could be improved by gaining a better understanding of the inhospital flow of patients and identifying opportunities for improvement.

objectivesTo describe a process mining approach for mapping the inhospital flow of pediatric trauma patients, to identify and characterize the major patient pathways and care transitions, and to identify opportunities for patient flow and triage improvement.

methodsFrom the trauma registry of a level I pediatric trauma center, data were extracted regarding the two highest trauma activation levels, Alpha (

resultsThe process map for the cohort was similar to a validated process map derived through qualitative methods. The process map for Bravo encounters had a relatively low fitness of 0.887, and 96 (5.6%) encounters were identified as nonconforming with characteristics comparable to Alpha encounters. In total, 28 patient pathways and 20 care transitions were identified. The top five patient pathways were traversed by 92.1% of patients, whereas the top five care transitions accounted for 87.5% of all care transitions. A larger-than-expected number of discharges from the pediatric intensive care unit (PICU) were identified, with 84.2% involving discharge to home without the need for home care services.

conclusionProcess mining was successfully applied to derive process maps from trauma registry data and to identify opportunities for trauma triage improvement and optimization of PICU use.

Indexed as

Data ScienceTrauma CentersAlgorithmsChildCluster AnalysisHeuristicsHumansPatient Transfer

Identifiers

PMID30134474
PMCPMC6105335

What OpenQuestion holds

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Registered trials

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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.