Evidence map›Paper›PMID 29302379›Full record

ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2017

Change-Point Detection for Monitoring Clinical Decision Support Systems with a Multi-Process Dynamic Linear Model.

Siqi Liu, Adam Wright, Dean F Sittig, Milos Hauskrecht

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 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. Using automated methods to detect safety problems with health information technology: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  2. Review
  3. Smashing the strict hierarchy: three cases of clinical decision support malfunctions involving carvedilol.Journal of the American Medical Informatics Association : JAMIA · 2018
    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

4 authors.

Siqi LiuDepartment of Computer Science, University of Pittsburgh, Pittsburgh, Pennsylvania.
Adam WrightBrigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Dean F SittigSchool of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas.
Milos HauskrechtDepartment of Computer Science, University of Pittsburgh, Pittsburgh, Pennsylvania.

Funding

Real-time detection of deviations in clinical care in ICU data streamsR01GM088224 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CLERMONT, GILLES, COOPER, GREGORY F. · 2009 to 2017
$3.7M
Improving clinical decision support reliability using anomaly detection methodsR01LM011966 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WRIGHT, ADAM T · 2014 to 2017
$2.4M
NIGMS NIH HHS R01 GM088224NLM NIH HHS R01 LM011966
6 · The paper itself

Abstract

A clinical decision support system and its components may malfunction due to different reasons. The objective of this work is to develop computational methods that can help us to monitor the system and assure its proper operation by promptly detecting and analyzing changes in its behavior. We develop a new change-point detection method using the Multi-Process Dynamic Linear Model. The experiments on real and simulated data show that our method outperforms existing change-point detection methods, leading to higher accuracy and shorter delay in the detection.

Identifiers

PMID29302379
PMCPMC5749419

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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.