The Collaboration Structure in COVID-19 Critical Care: A Network Analysis.

BACKGROUND: Few ICU staffing studies examine collaboration structures among healthcare workers. Knowledge about how healthcare workers (HWs) are connected to care for critically ill COVID-19 (C19) patients provides evidence for characterizing the relationship between team structures, care quality, and patient safety.

OBJECTIVE: To discover the distinctions of teamwork structures in C19 critical care by comparing HW collaboration associated with the management of critically ill patients with and without C19.

METHODS: In this retrospective study, we apply network analysis to the utilization of electronic health records (EHRs) of 76 critically ill patients (38 with and 38 without C19) admitted to a large academic medical center to learn HW collaboration. We use the EHRs for adult patients admitted to the C19 ICU at Vanderbilt University Medical Center (Nashville, Tennessee, USA) between March 17, 2020 and May 31, 2020. We matched each C19 patient on age, gender, and length of stay, with NC19 patients admitted to the Medical ICU (MICU) between December 1, 2019 and February 29, 2020. Then we use two sociometric measurements, including eigencentrality and betweenness, to quantify HWs' status in the networks. Eigencentrality characterizes the degree to which an HW is likely to be a core person in the collaboration. Betweenness centrality refers to whether an HW lies on the path of others who are not directly connected, which is leveraged to characterize the broad skillsets of an HW. We further measure patient staffing intensity in terms of the number of HWs interacting with the EHR of a patient. We assess the extent to which the core and betweenness status of HWs, as well as patient staffing intensity, in C19 and Non-C19 (NC19) critical care are statistically different using Mann-Whitney U tests at the 95% confidence level.

RESULTS: HWs are likely to more frequently work with each other in C19 than NC19 critical care (median eigencentrality values of 0.096 vs. 0.057, respectively; p = 1.5×10e-9). Internal medicine physicians exhibit a higher core status in the C19 critical care than NC19 (p = 1.2 ×10e-3). Nurse practitioners exhibit a more betweenness status in the C19 than NC19 care (p = 3.10 ×10e-4). In comparison to the NC19 setting, the EHRs of C19 critically ill patients were utilized by a larger number of internal medicine nurse practitioners (p = 1.27 ×10e-5), cardiovascular nurses (p = 8.48 ×10e-6) and surgical ICU nurses (p = 1.62 ×10e-3), as well as a smaller number of resident physicians (p = 5.96 ×10e-4).

CONCLUSIONS: Network analysis methodologies and EHR utilization data provide a novel way to learn distinctions of collaboration structures in C19 critical care, which can be leveraged by healthcare organizations to understand the novel additions the C19 brings to the collaboration structure in urgent care.