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Listen to the Learner: A Grounded Theory Approach to Clinical Reasoning Remediation in Pediatric Residency
James Bowen1, Johnathan Mollman2, Lisa E Herrmann1
1Division of Pediatric Hospital Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio.
Objective:
Clinical reasoning (CR) skills are essential to physician practice, yet deficits are difficult to detect and support. Although remediation frameworks exist, little is known about how pediatric residency programs approach CR remediations or the barriers they face. This study aimed to develop an evidence-informed process for supporting CR deficits in pediatrics.
Methods:
Using a grounded theory approach and a pragmatism worldview, we conducted a secondary analysis of 20 semistructured interviews with pediatric residency program leaders, followed by 8 additional interviews with CR experts. Data from program leaders were recoded to generate a preliminary remediation process, which was refined through constant comparison with expert interviews to identify best practices and common challenges.
Results:
Analysis generated a multi-step model of CR support. Key steps include differentiating CR from deficits in other competencies, characterizing the specific CR microskills involved, and assessing for alternative factors such as mental health or burnout. Effective remediation requires identifying trusted, available supporters with CR expertise and tailoring support methods to specific deficits. Structural barriers unique to pediatrics, such as family-centered rounds limit opportunities for CR support in authentic environments. Experts identified best practices for residency leaders to use to ensure continued progress in and beyond residency.
Conclusions:
This study offers a pragmatic process for CR remediation that reflects both the contextual barriers of pediatric training and the expertise of leaders and educators. The model provides actionable guidance for programs seeking to improve CR support, even in resource-limited settings.
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