Characterizing intensive care unit rounding teams using meta-data from the electronic health record

• Published in: Journal of critical care 2022-12, Vol.72, p.154143-154143, Article 154143
• Main Authors: Kahn, Jeremy M., Minturn, John S., Riman, Kathryn A., Bukowski, Leigh A., Davis, Billie S.
• Format: Article
• Language: English
• Subjects: Critical Care; Electronic Health Records; Humans; Intensive care; Intensive Care Units; Interprofessional relations; Mechanical ventilation; Nurses; Patient Care Team; Therapists; Ventilators
• ISSN: 0883-9441; 1557-8615
• DOI: 10.1016/j.jcrc.2022.154143

Teamwork is an important determinant of outcomes in the intensive care unit (ICU), yet the nature of individual ICU teams remains poorly understood. We examined whether meta-data in the form of digital signatures in the electronic health record (EHR) could be used to identify and characterize ICU teams. We analyzed EHR data from 27 ICUs over one year. We linked intensivist physicians, nurses, and respiratory therapists to individual patients based on selected EHR meta-data. We then characterized ICU teams by their members' overall past experience and shared past experience; and used network analysis to characterize ICUs by their network's density and centralization. We identified 2327 unique providers and 30,892 unique care teams. Teams varied based on their average team member experience (median and total range: 262.2 shifts, 9.0–706.3) and average shared experience (median and total range: 13.2 shared shifts, 1.0–99.3). ICUs varied based on their network's density (median and total range: 0.12, 0.07–0.23), degree centralization (0.50, 0.35–0.65) and closeness centralization (0.45, 0.11–0.60). In a regression analysis, this variation was only partially explained by readily observable ICU characteristics. EHR meta-data can assist in the characterization of ICU teams, potentially providing novel insight into strategies to measure and improve team function in critical care. •Meta-data from the EHR can be used to identify which critical care providers worked together to care for a given patient on a given day.•Critical care teams vary across key characteristics, including team members’ overall clinical experience and shared clinical experience.•Critical care units can be differentiated using network analysis measures such as density and centralization.•These insights could yield actionable targets for improving outcomes by better understanding the structure and function of critical care teams.