Network analysis of team structure in the neonatal intensive care unit

The goal was to examine nursing team structure and its relationship with family satisfaction. We used electronic health records to create patient-based, 1-mode networks of nursing handoffs. In these networks, nurses were represented as nodes and handoffs as edges. For each patient, we calculated net...

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Veröffentlicht in:Pediatrics (Evanston) 2010-06, Vol.125 (6), p.e1460-e1467
Hauptverfasser: Gray, James E, Davis, Darcy A, Pursley, DeWayne M, Smallcomb, Jane E, Geva, Alon, Chawla, Nitesh V
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Sprache:eng
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Zusammenfassung:The goal was to examine nursing team structure and its relationship with family satisfaction. We used electronic health records to create patient-based, 1-mode networks of nursing handoffs. In these networks, nurses were represented as nodes and handoffs as edges. For each patient, we calculated network statistics including team size and diameter, network centrality index, proportion of newcomers to care teams according to day of hospitalization, and a novel measure of the average number of shifts between repeat caregivers, which was meant to quantify nursing continuity. We assessed parental satisfaction by using a standardized survey. Team size increased with increasing length of stay. At 2 weeks of age, 50% of shifts were staffed by a newcomer nurse who had not previously cared for the index patient. The patterns of newcomers to teams did not differ according to birth weight. When the population was dichotomized according to median mean repeat caregiver interval value, increased reports of problems with nursing care were seen with less-consistent staffing by familiar nurses. This relationship persisted after controlling for factors including birth weight, length of stay, and team size. Family perceptions of nursing care quality are more strongly associated with team structure and the sequence of nursing participation than with team size. Objective measures of health care team structure and function can be examined by applying network analytic techniques to information contained in electronic health records.
ISSN:0031-4005
1098-4275
DOI:10.1542/peds.2009-2621