Measuring Team Hierarchy During High-Stakes Clinical Decision Making: Development and Validation of a New Behavioral...

Hierarchy is often cited as a cause of health care team failure; however, there are no validated measures of team hierarchy. Research on group processes in sociology provides a theoretical framework-status characteristics and expectation states (SCES)-that explains the mechanisms that produce the observable power and prestige order (status hierarchy) of the team. The authors use this formal theoretical framework to gather evidence of validity by adapting the method to measure the status hierarchy of medical teams.

In this retrospective, secondary analysis, the authors analyzed archived videorecorded training exercises conducted between 2007 and 2010 of mixed-gender health care teams of first-year residents and nurses engaged in simulated, complex decision-making scenarios. Analyses were conducted in 2013 with data reanalyzed in July 2022. By adapting the SCES framework for the unique features of academic health care, they developed and refined a coding method from videos and transcripts. To examine validity, they consider the content, response process, internal structure, relation to other variables, and consequences of the framework.

Having established an acceptable level of coding reliability for key variables for videos and transcripts, the authors demonstrate relation to other variables, specifically detailing how the coding scheme delineates 2 status characteristics-occupation and gender. The mean numbers of statement types by gender and occupation were largely as predicted. Directives, question directives, patient work, and knowledge claims were more likely to be coded during video than transcript coding, whereas questions, statements of fact, and compliance were more likely to be coded during transcript than video coding. However, the relative rates of each statement type by status remained largely consistent among the coding methods.

This study provides important insight into the mechanisms by which hierarchy impacts team decision making and develops the necessary framework and measurement tool to perform larger studies.