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. 2022 Jun 6:290:359-363.
doi: 10.3233/SHTI220096.

Perioperative Care Structures and Non-Routine Events: Network Analysis

You Chen  1 , Mhd Wael Alrifai  1 , Yang Gong  2 , Rhodes Evan  1 , Jason Slagle  1 , Bradley Malin  1 , Daniel France  1
Affiliations

Perioperative Care Structures and Non-Routine Events: Network Analysis

You Chen et al. Stud Health Technol Inform. .

Abstract

Non-routine events (NREs) are any aspect of care perceived by clinicians as a deviation from optimal care. The reporting of NREs to peers (or care teams) may help healthcare organizations improve patient safety in high-risk work environments (e.g., surgery). While various factors, including care structure and organizational factors may influence a clinician's NRE reporting behavior, their role has not been systematically studied. We conducted a retrospective study relying on NREs and electronic health records to determine if perioperative interaction structures among clinicians are associated with the frequency of NRE reporting in a large academic medical center. The data covers November 1, 2016, to January 31, 2019 and includes 295 perioperative clinicians, 225 neonatal surgical cases, and 543 NREs. Using network analysis, we measured a clinician's status in interaction structures according to the sociometric factors of degree, betweenness, and eigenvector centrality. We applied a proportional odds model to measure the relationship between each sociometric factor and NRE reporting frequency. Our findings indicate that the centrality of clinicians is directly associated with the quantity of NREs per surgical case.

Keywords: Network analysis; neonatal intensive care unit; perioperative interaction structure.

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Figures

Figure 1
Figure 1
Distribution of the NRE reporting frequency per surgical case per clinician (top) and per patient (bottom).
Figure 2.
Figure 2.
Each node is a clinician, the color of which corresponds to their role. The size of the node is proportional to its degree.
Figure 3.
Figure 3.
Associations between values of sociometric factors of a clinician (degree-top, betweenness-middle, eigenvector-bottom) and the number of patients managed by the clinician. The number of patients and sociometric values were normalized using min-max normalization.
Figure 4
Figure 4
Distribution of the number of NREs reported per case for clinicians with a degree Left) greater than and Right) less than 0.1935.
Figure 5
Figure 5
Distributions of weight (top) and gestational age (bottom) in higher and lower degree groups
Figure 6
Figure 6
Distributions of procedures (top) and emergent care (bottom) received by patients in higher and lower degree groups
See this image and copyright information in PMC

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