Evidence map›Paper›PMID 30506061›Full record

ArticleProceedings. IEEE International Conference on Healthcare Informatics2018

Process Mining the Trauma Resuscitation Patient Cohorts.

Sen Yang, Fei Tao, Jingyuan Li, Dawei Wang, Shuhong Chen, Ivan Marsic, Omar Z Ahmed, Randall S Burd

Abstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Healthcare Informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sen YangRutgers University, Piscataway, NJ.
Fei TaoRutgers University, Piscataway, NJ.
Jingyuan LiRutgers University, Piscataway, NJ.
Dawei WangRutgers University, Piscataway, NJ.
Shuhong ChenRutgers University, Piscataway, NJ.
Ivan MarsicRutgers University, Piscataway, NJ.
Omar Z AhmedChildren's Nat'l Medical Center, Washington, DC.
Randall S BurdChildren's Nat'l Medical Center, Washington, DC.

Funding

Intention-aware Recommender System for Improving Trauma Resuscitation OutcomesR01LM011834 · NLM · CHILDREN'S RESEARCH INSTITUTE · PI BURD, RANDALL S., MARSIC, IVAN · 2014 to 2023
$4.7M
NLM NIH HHS R01 LM011834
6 · The paper itself

Abstract

In this study, we present a framework for analyzing associations between patient cohorts and the trauma resuscitation procedures their patients received. Our framework works by quantifying associations between discovered patient cohorts and treatment patterns. We evaluated our framework on a trauma resuscitation dataset collected in a level 1 trauma center. Our experimental results show that using weights learned by our algorithm improves measurements of patient similarity. Four patient cohorts were then found via clustering, and statistically significant resuscitation patterns were discovered using process mining techniques. Though only tested on the trauma resuscitation process, our framework can be generalized to analyze other medical processes.

Indexed as

Medical Workflow AnalysisPatient Cohorts AnalysisProcess MiningTrauma Resuscitation

Identifiers

PMID30506061
PMCPMC6262881

What OpenQuestion holds

Textmetadata
LicenceTDM
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.