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Surgical Team Mapping: Implications for Staff Allocation and Coordination
Author(s) -
Sykes Mark,
Gillespie Brigid M.,
Chaboyer Wendy,
Kang Evelyn
Publication year - 2015
Publication title -
aorn journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.222
H-Index - 43
eISSN - 1878-0369
pISSN - 0001-2092
DOI - 10.1016/j.aorn.2014.03.018
Subject(s) - staffing , surgical team , bivariate analysis , perioperative , harm , perioperative nursing , nursing , medicine , descriptive statistics , surgical procedures , psychology , medical emergency , surgery , computer science , social psychology , statistics , mathematics , machine learning
Perioperative team membership consistency is not well researched despite being essential in reducing patient harm. We describe perioperative team membership and staffing across four surgical specialties in an Australian hospital. We analyzed staffing and case data using social network analysis, descriptive statistics, and bivariate correlations and mapped 100 surgical procedures with 171 staff members who were shared across four surgical teams, including 103 (60.2%) nurses. Eighteen of 171 (10.5%) staff members were regularly shared across teams, including 12 nurses, five anesthetists, and one registrar. We found weak but significant correlations between the number of staff ( P < .001), procedure start time ( P < .001), length of procedure ( P < .05), and patient acuity ( P < .001). Using mapping, personnel can be identified who may informally influence multiple team cultures, and nurses (ie, the majority of team members in surgery) can lead the development of highly functioning surgical teams.