Frontiers in Public Health (May 2023)

A novel approach for assessing bias during team-based clinical decision-making

  • Natalie Pool,
  • Megan Hebdon,
  • Esther de Groot,
  • Ryan Yee,
  • Kathryn Herrera-Theut,
  • Erika Yee,
  • Larry A. Allen,
  • Ayesha Hasan,
  • JoAnn Lindenfeld,
  • Elizabeth Calhoun,
  • Molly Carnes,
  • Nancy K. Sweitzer,
  • Khadijah Breathett

DOI
https://doi.org/10.3389/fpubh.2023.1014773
Journal volume & issue
Vol. 11

Abstract

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Many clinical processes include multidisciplinary group decision-making, yet few methods exist to evaluate the presence of implicit bias during this collective process. Implicit bias negatively impacts the equitable delivery of evidence-based interventions and ultimately patient outcomes. Since implicit bias can be difficult to assess, novel approaches are required to detect and analyze this elusive phenomenon. In this paper, we describe how the de Groot Critically Reflective Diagnoses Protocol (DCRDP) can be used as a data analysis tool to evaluate group dynamics as an essential foundation for exploring how interactions can bias collective clinical decision-making. The DCRDP includes 6 distinct criteria: challenging groupthink, critical opinion sharing, research utilization, openness to mistakes, asking and giving feedback, and experimentation. Based on the strength and frequency of codes in the form of exemplar quotes, each criterion was given a numerical score of 1–4 with 1 representing teams that are interactive, reflective, higher functioning, and more equitable. When applied as a coding scheme to transcripts of recorded decision-making meetings, the DCRDP was revealed as a practical tool for examining group decision-making bias. It can be adapted to a variety of clinical, educational, and other professional settings as an impetus for recognizing the presence of team-based bias, engaging in reflexivity, informing the design and testing of implementation strategies, and monitoring long-term outcomes to promote more equitable decision-making processes in healthcare.

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