Evidence map›Paper›PMID 31070719›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2020

How Introducing a Registry With Automated Alerts for Carbapenem-resistant Enterobacteriaceae (CRE) May Help Control CRE Spread in a Region.

Bruce Y Lee, Sarah M Bartsch, Mary K Hayden, Joel Welling, Jay V DePasse, Sarah K Kemble, Jim Leonard, Robert A Weinstein, Leslie E Mueller, Kruti Doshi and 3 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

13 authors.

Bruce Y LeePublic Health Computational and Operations Research, Baltimore, Maryland.
Sarah M BartschPublic Health Computational and Operations Research, Baltimore, Maryland.
Mary K HaydenRush University Medical Center, Chicago, Illinois.
Joel WellingPublic Health Applications, Pittsburgh Supercomputing Center, Pennsylvania.
Jay V DePassePublic Health Applications, Pittsburgh Supercomputing Center, Pennsylvania.
Sarah K KembleRush University Medical Center, Chicago, Illinois.
Jim LeonardPublic Health Applications, Pittsburgh Supercomputing Center, Pennsylvania.
Robert A WeinsteinRush University Medical Center, Chicago, Illinois.
Leslie E MuellerPublic Health Computational and Operations Research, Baltimore, Maryland.
Kruti DoshiCook County Health, Chicago, Illinois.
Shawn T BrownMcGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada.
William E TrickRush University Medical Center, Chicago, Illinois.
Michael Y LinRush University Medical Center, Chicago, Illinois.

Funding

MULTILEVEL SYSTEMS-ORIENTED CHILDHOOD OBESITY STUDY IN CHINAU54HD070725 · NICHD · JOHNS HOPKINS UNIVERSITY · PI WANG, YOUFA · 2011 to 2016
$15.9M
Virtual Population Obesity Prevention (VPOP) Labs: Computational, Multi-Scale Models for Obesity SolutionsU01HD086861 · NICHD · JOHNS HOPKINS UNIVERSITY · PI LEE, BRUCE Y · 2015 to 2019
$2.8M
Regional Healthcare Ecosystem Analyst for Healthcare Associated InfectionsR01HS023317 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI LEE, BRUCE Y · 2014 to 2014
$2.4M
AHRQ HHS R01 HS023317NCEZID CDC HHS U54 CK000481NCEZID CDC HHS U54 CK000607NICHD NIH HHS U01 HD086861NICHD NIH HHS U54 HD070725
6 · The paper itself

Abstract

backgroundRegions are considering the use of electronic registries to track patients who carry antibiotic-resistant bacteria, including carbapenem-resistant Enterobacteriaceae (CRE). Implementing such a registry can be challenging and requires time, effort, and resources; therefore, there is a need to better understand the potential impact.

methodsWe developed an agent-based model of all inpatient healthcare facilities (90 acute care hospitals, 9 long-term acute care hospitals, 351 skilled nursing facilities, and 12 ventilator-capable skilled nursing facilities) in the Chicago metropolitan area, surrounding communities, and patient flow using our Regional Healthcare Ecosystem Analyst software platform. Scenarios explored the impact of a registry that tracked patients carrying CRE to help guide infection prevention and control.

resultsWhen all Illinois facilities participated (n = 402), the registry reduced the number of new carriers by 11.7% and CRE prevalence by 7.6% over a 3-year period. When 75% of the largest Illinois facilities participated (n = 304), registry use resulted in a 11.6% relative reduction in new carriers (16.9% and 1.2% in participating and nonparticipating facilities, respectively) and 5.0% relative reduction in prevalence. When 50% participated (n = 201), there were 10.7% and 5.6% relative reductions in incident carriers and prevalence, respectively. When 25% participated (n = 101), there was a 9.1% relative reduction in incident carriers (20.4% and 1.6% in participating and nonparticipating facilities, respectively) and 2.8% relative reduction in prevalence.

conclusionsImplementing an extensively drug-resistant organism registry reduced CRE spread, even when only 25% of the largest Illinois facilities participated due to patient sharing. Nonparticipating facilities garnered benefits, with reductions in new carriers.

Indexed as

Carbapenem-Resistant EnterobacteriaceaeCross InfectionEnterobacteriaceae InfectionsChicagoEcosystemHumansIllinoisRegistriesCREelectronic registrymodelingtransmission

Identifiers

PMID31070719
PMCPMC7931833

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.