Trainee selection of tasks in postgraduate medical education: Is there a role for 'cherry-picking' to optimise learning?

PURPOSE: Learning is optimised when postgraduate trainees engage in clinical tasks in their zone of proximal development (ZPD). However, workplace learning environments impose additional non-learning goals and additional tasks that may lead to trainees engaging in tasks that do not fall within their ZPD. We do not fully understand how trainees select clinical tasks in the workplace learning environment. If we knew the goals and factors they consider when selecting a task, we could better equip trainees with strategies to select tasks that maximise learning. We explored how postgraduate trainees select clinical tasks using echocardiography interpretation as a model. METHODS: Canadian General Cardiology residents and Echocardiography fellows were invited to participate in semi-structured interviews. Aligning with a theory-informed study, two independent researchers used a deductive, directed content analysis approach to identify codes and themes. RESULTS: Eleven trainees from seven Canadian universities participated (PGY4 = 4, PGY5 = 3, PGY6 = 1 and echocardiography fellows = 3). Goals included learning content, fulfilling assessment criteria and contributing to clinical demands. Trainees switched between goals throughout the day, as it was too effortful for them to engage in tasks within their ZPD at all times. When trainees had sufficient mental effort available, they selected higher complexity tasks that could advance learning content. When available mental effort was low, trainees selected less complex tasks that fulfilled numerically based assessment goals or contributed to clinical demands. Trainees predominantly used perceived complexity of the echocardiogram as a factor to select tasks to achieve their desired goals. CONCLUSION: Postgraduate trainees select tasks within their ZPD that enable them to maximise learning when they perceive to have sufficient mental effort available and workplace affordances are adequate. These findings can inform individual and systemic strategies to maximise learning when selecting tasks.

Developing and authenticating an electronic health record-based report card for assessing residents' clinical performance.

Purpose: The electronic health record (EHR) is frequently identified as a source of assessment data regarding residents' clinical performance. To better understand how to harness EHR data for education purposes, the authors developed and authenticated a prototype resident report card. This report card used EHR data exclusively and was authenticated with various stakeholders to understand individuals' reactions to and interpretations of EHR data when presented in this way. Methods: Using principles derived from participatory action research and participatory evaluation, this study brought together residents, faculty, a program director, and medical education researchers (n = 19) to develop and authenticate a prototype report card for residents. From February to September 2019, participants were invited to take part in a semistructured interview that explored their reactions to the prototype and provided insights about how they interpreted the EHR data. Results: Our results highlighted three themes: data representation, data value, and data literacy. Participants varied in terms of the best way to present the various EHR metrics and felt pertinent contextual information should be included. All participants agreed that the EHR data presented were valuable, but most had concerns about using it for assessment. Finally, participants had difficulties interpreting the data, suggesting that these data could be presented more intuitively and that residents and faculty may require additional training to fully appreciate these EHR data. Conclusions: This work demonstrated how EHR data could be used to assess residents' clinical performance, but it also identified areas that warrant further consideration, especially pertaining to data representation and subsequent interpretation. Providing residents and faculty with EHR data in a resident report card was viewed as most valuable when used to guide feedback and coaching conversations.

Facilitating Residents' Understanding of Electronic Health Record Report Card Data Using Faculty Feedback and Coaching.

PURPOSE: Feedback continues to present a challenge for competency-based medical education. Clear, consistent, and credible feedback is vital to supporting one's ongoing development, yet it can be difficult to gather clinical performance data about residents. This study sought to determine whether providing residents with electronic health record (EHR)-based report cards, as well as an opportunity to discuss these data with faculty trained using the R2C2 model, can help residents understand and interpret their clinical performance metrics. METHOD: Using action research methodology, the author team collected EHR data from July 2017 to February 2020, for all residents (n = 21) in one 5-year Emergency Medicine program and created personalized report cards for each resident. During October 6-17, 2020, 8 out of 17 eligible residents agreed to have their feedback conversations recorded and participate in a subsequent interview with a nonphysician member of the research team. Data were analyzed using thematic analysis, and the authors used inductive analysis to identify themes in the data. RESULTS: In analyzing both the feedback conversations as well as the individual interviews with faculty and residents, the authors identified 2 main themes: (1) Reactions and responses to receiving personalized EHR data and (2) The value of EHR data for assessment and feedback purposes. All participants believed that EHR data metrics are useful for prompting self-reflection, and many pointed to their utility in providing suggestions for actionable changes in their clinical practice. For faculty, having a tool through which underperforming residents can be shown "objective" data about their clinical performance helps underscore the need for improvement, particularly when residents are resistant. CONCLUSIONS: The EHR is a valuable source of educational data, and this study demonstrates one of the many thoughtful ways it can be used for assessment and feedback purposes.

A scoping review of approaches for measuring 'interdependent' collaborative performances.

INTRODUCTION: Individual assessment disregards the team aspect of clinical work. Team assessment collapses the individual into the group. Neither is sufficient for medical education, where measures need to attend to the individual while also accounting for interactions with others. Valid and reliable measures of interdependence are critical within medical education given the collaborative manner in which patient care is provided. Medical education currently lacks a consistent approach to measuring the performance between individuals working together as part of larger healthcare team. This review's objective was to identify existing approaches to measuring this interdependence. METHODS: Following Arksey & O'Malley's methodology, we conducted a scoping review in 2018 and updated it to 2020. A search strategy involving five databases located >12 000 citations. At least two reviewers independently screened titles and abstracts, screened full texts (n = 161) and performed data extraction on twenty-seven included articles. Interviews were also conducted with key informants to check if any literature was missing and assess that our interpretations made sense. RESULTS: Eighteen of the twenty-seven articles were empirical; nine conceptual with an empirical illustration. Eighteen were quantitative; nine used mixed methods. The articles spanned five disciplines and various application contexts, from online learning to sports performance. Only two of the included articles were from the field of Medical Education. The articles conceptualised interdependence of a group, using theoretical constructs such as collaboration synergy; of a network, using constructs such as degree centrality; and of a dyad, using constructs such as synchrony. Both descriptive (eg social network analysis) and inferential (eg multi-level modelling) approaches were described. CONCLUSION: Efforts to measure interdependence are scarce and scattered across disciplines. Multiple theoretical concepts and inconsistent terminology may be limiting programmatic work. This review motivates the need for further study of measurement techniques, particularly those combining multiple approaches, to capture interdependence in medical education.