Evidence map›Paper›PMID 34637393›Full record

ArticleJournal of medical Internet research2021

Assessing Neonatal Intensive Care Unit Structures and Outcomes Before and During the COVID-19 Pandemic: Network Analysis Study.

Hannah Mannering, Chao Yan, Yang Gong, Mhd Wael Alrifai, Daniel France, You Chen

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Assessing Intrahospital Care Transition Structures Before and During the COVID-19 Pandemic: Network Analysis Study.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  5. Article
  6. 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

6 authors.

Hannah ManneringDepartment of Computer Science, Loyola University, Baltimore, MD, United States.ORCID 0000-0002-1441-3303
Chao YanDepartment of Computer Science, Vanderbilt University, Nashville, TN, United States.ORCID 0000-0002-6719-1388
Yang GongSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID 0000-0002-0864-8368
Mhd Wael AlrifaiDepartment of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0003-0761-4905
Daniel FranceDepartment of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0002-5648-8223
You ChenDepartment of Computer Science, Vanderbilt University, Nashville, TN, United States.ORCID 0000-0001-8232-8840

Funding

Discovering Care Coordination Practice Patterns in the EMR: Interpretation and Impact on Patient OutcomesR01LM012854 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHEN, YOU · 2019 to 2022
$1.5M
NLM NIH HHS R01 LM012854
6 · The paper itself

Abstract

backgroundHealth care organizations (HCOs) adopt strategies (eg. physical distancing) to protect clinicians and patients in intensive care units (ICUs) during the COVID-19 pandemic. Many care activities physically performed before the COVID-19 pandemic have transitioned to virtual systems during the pandemic. These transitions can interfere with collaboration structures in the ICU, which may impact clinical outcomes. Understanding the differences can help HCOs identify challenges when transitioning physical collaboration to the virtual setting in the post-COVID-19 era.

objectiveThis study aims to leverage network analysis to determine the changes in neonatal ICU (NICU) collaboration structures from the pre- to the intra-COVID-19 era.

methodsIn this retrospective study, we applied network analysis to the utilization of electronic health records (EHRs) of 712 critically ill neonates (pre-COVID-19, n=386; intra-COVID-19, n=326, excluding those with COVID-19) admitted to the NICU of Vanderbilt University Medical Center between September 1, 2019, and June 30, 2020, to assess collaboration between clinicians. We characterized pre-COVID-19 as the period of September-December 2019 and intra-COVID-19 as the period of March-June 2020. These 2 groups were compared using patients' clinical characteristics, including age, sex, race, length of stay (LOS), and discharge dispositions. We leveraged the clinicians' actions committed to the patients' EHRs to measure clinician-clinician connections. We characterized a collaboration relationship (tie) between 2 clinicians as actioning EHRs of the same patient within the same day. On defining collaboration relationship, we built pre- and intra-COVID-19 networks. We used 3 sociometric measurements, including eigenvector centrality, eccentricity, and betweenness, to quantify a clinician's leadership, collaboration difficulty, and broad skill sets in a network, respectively. We assessed the extent to which the eigenvector centrality, eccentricity, and betweenness of clinicians in the 2 networks are statistically different, using Mann-Whitney U tests (95% CI).

resultsCollaboration difficulty increased from the pre- to intra-COVID-19 periods (median eccentricity: 3 vs 4; P<.001). Nurses had reduced leadership (median eigenvector centrality: 0.183 vs 0.087; P<.001), and neonatologists with broader skill sets cared for more patients in the NICU structure during the pandemic (median betweenness centrality: 0.0001 vs 0.005; P<.001). The pre- and intra-COVID-19 patient groups shared similar distributions in sex (~0 difference), race (4% difference in White, and 3% difference in African American), LOS (interquartile range difference in 1.5 days), and discharge dispositions (~0 difference in home, 2% difference in expired, and 2% difference in others). There were no significant differences in the patient demographics and outcomes between the 2 groups.

conclusionsManagement of NICU-admitted patients typically requires multidisciplinary care teams. Understanding collaboration structures can provide fine-grained evidence to potentially refine or optimize existing teamwork in the NICU.

Indexed as

COVID-19Intensive Care Units, NeonatalHumansInfant, NewbornIntensive Care UnitsPandemicsRetrospective StudiesSARS-CoV-2collaborationCOVID-19discharge dispositionselectronic health recordshealth care organization structuresintensive carelength of stayneonatal intensive care unitnetwork analysistemporal network analysis

Identifiers

PMID34637393
PMCPMC8530253

What OpenQuestion holds

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LicenceCC BY
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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.