Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 18, 2021
Date Accepted: Oct 8, 2021
Date Submitted to PubMed: Oct 12, 2021
Assessing Neonatal Intensive Care Unit Structures and Outcomes Before and During the COVID-19 Pandemic: Network Analysis Study
ABSTRACT
Background:
Healthcare organizations (HCOs) adopt strategies (e.g., physical distancing) to protect clini-cians and patients in intensive care units (ICUs) during the COVID-19 (C19) pandemic. Many care activities physically performed before C19 have been moving to virtual systems during the C19. The transitions from the physical to the virtual settings 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 in the post-C19 era.
Objective:
This study aims to leverage network analysis to determine the changes in neonatal ICU (NICU) collaboration structures from pre- to intra-C19.
Methods:
In this retrospective study, we apply network analysis to the utilization of electronic health rec-ords (EHRs) of 712 critically ill patients (386 pre-C19 and 326 intra-C19, excluding those with C19 infection) admitted to a large academic medical center to learn collaboration between cli-nicians. We use the EHRs for neonates admitted to the NICU at Vanderbilt University Medical Center (Nashville, Tennessee, USA) between September 1, 2019, and June 30, 2020. We char-acterized pre-C19 as September through December of 2019 and intra-C19 as March through June of 2020. These two groups are compared using patients’ clinical characteristics, including their age, sex, race, length of stay (LOS), and discharge dispositions. We leverage the actions committed to the EHRs of patients by clinicians to measure clinician-clinician connections. We characterize a collaboration relationship (tie) between two clinicians as they performed actions to EHRs of the same patient within the same day. Upon the definition of collaboration relation-ship, we build pre- and intra-C19 networks. We use three sociometric measurements, including eigenvector centrality, eccentricity, and betweenness, to quantify a clinician’s leadership, col-laboration difficulty, and broad skillsets, respectively in a network. We assess the extent to which the eigenvector centrality, eccentricity, and betweenness of clinicians, in pre- and intra-C19 networks, are statistically different using Mann-Whitney U tests at the 95% confidence level.
Results:
Our analysis results show the collaboration difficulty increases from pre- to intra-C19 (median eccentricity: 3 vs. 4, p = 2.2 × 10-6). In addition, nurses have reduced leadership (median eigen-vector centrality: 0.183 vs. 0.087, p = 2.64 × 10-15), and neonatologists who have broader skill-sets care for a wider spectrum of patients in the NICU structure during the C19 pandemic (me-dian betweenness centrality: 0.0001 vs. 0.005, p = 5.43 × 10-3). The pre- and intra-C19 patient groups share 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 dis-charge dispositions (~0 difference in home, 2% difference in expired, and 2% difference in others). There are no significant differences in the patient demographics and outcomes be-tween the two groups.
Conclusions:
Management of NICU patients typically requires multidisciplinary care teams. Understanding collaboration structures can provide fine-grained evidence to potentially refine or optimize ex-isting teamwork in the NICU.
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