Publications by authors named "Pusic M"

Objective: To examine pediatrician diagnostic skill development of dermatology image-based cases via a web-based tool and to determine case-level variables that were associated with diagnostic error.

Study Design: This was a multicenter, prospective, cross-sectional study. A convenience sample of pediatric trainees and attendees were eligible for participation.

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Article Synopsis
  • Pediatric pneumonia diagnoses are tricky due to overlapping symptoms with other respiratory issues, subjective radiograph interpretations, and non-diagnostic lab results.
  • The study analyzed children aged 3 months to 16 years in Canadian EDs before COVID-19, focusing on how accurately physicians could classify pneumonia types using an expert panel for consensus diagnosis.
  • Findings showed a significant mismatch between physicians’ diagnoses and consensus results, with over-diagnosis of typical bacterial pneumonia and recommendations for specific clinical and lab indicators to better identify bacterial cases.
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Purpose: Competency-based time-variable (CBTV) graduate medical education (GME) has been implemented in Canada, Europe, and the United States, yet its perceived value has not been explored. Promotion in Place (PIP) is a CBTV GME program in which residents graduating early advance to attending status with "sheltered independence" until the standard graduation date. This study describes perceived value of CBTV GME and PIP at Mass General Brigham by capturing diverse stakeholder perspectives.

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A procedure is outlined for point and interval estimation of location parameters associated with polytomous items, or raters assessing studied subjects or cases, which follow the rating scale model. The method is developed within the framework of latent variable modeling, and is readily applied in empirical research using popular software. The approach permits testing the goodness of fit of this widely used model, which represents a rather parsimonious item response theory model as a means of description and explanation of an analyzed data set.

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Introduction: Increasingly, medical training aims to develop physicians who are competent collaborators. Although interprofessional interactions are inevitable elements of medical trainees' workplace learning experiences, the existing literature lacks a cohesive model to conceptualise the learning potential residing in these interactions.

Methods: We conducted a critical review of the health professions and related educational literatures to generate an empirically and theoretically informed description of medical trainees' workplace interactions with other health professionals, including learning mechanisms and outcomes.

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Introduction: Addressing systemic bias in medical school assessment is an urgent task for medical education. This paper outlines recommendations on topic areas for further research on systemic bias, developed from a workshop discussion at the 2023 annual meeting of the Society of Directors of Research in Medical Education.

Materials And Methods: During the workshop, directors engaged in small-group discussions on guidelines to address bias in assessment practices following a proposed categorization of 'Do's,' 'Don'ts,' and 'Don't knows' and listed their insights using anonymous sticky notes, which were shared and discussed with the larger group of participants.

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Objective: To examine the effectiveness of an education intervention for reducing physician diagnostic error in identifying pediatric burn and bruise injuries suspicious for abuse, and to determine case-specific variables associated with an increased risk of diagnostic error.

Study Design: This was a multicenter, prospective, cross-sectional study. A convenience sample of pediatricians and other front-line physicians who treat acutely injured children in the United States and Canada were eligible for participation.

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Background: Precision medicine, sometimes referred to as personalized medicine, is rapidly changing the possibilities for how people will engage health care in the near future. As technology to support precision medicine exponentially develops, there is an urgent need to proactively improve our understanding of precision medicine and pose important research questions (RQs) related to its inclusion in the education and training of future emergency physicians.

Methods: A seven-step process was employed to develop a research agenda exploring the intersection of precision and emergency medicine education/training.

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The use of the p-value in quantitative research, particularly its threshold of "P < 0.05" for determining "statistical significance," has long been a cornerstone of statistical analysis in research. However, this standard has been increasingly scrutinized for its potential to mislead findings, especially when the practical significance, the number of comparisons, or the suitability of statistical tests are not properly considered.

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Background: Currently, the Accreditation Council of Graduate Medical Education requires time-based pediatric experiences for emergency medicine (EM) residents in both pediatric emergency medicine (PEM) and critical care settings. The American Board of Emergency Medicine has published the Model of the Clinical Practice of Emergency Medicine, which is a list of content an EM resident should learn. However, this list is large and without prioritization and therefore can be difficult to incorporate into time-limited curricula.

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Purpose: Medical education should prepare learners for complex and evolving work, and should ideally include the Master Adaptive Learner (MAL) model-meta-learning skills for continuous self-regulated learning. This study aimed to measure obstetrics and gynecology (OB/GYN) residents' MAL attributes, assess associations with burnout and resilience, and explore learning task associations with MAL.

Method: OB/GYN residents were surveyed electronically at an in-training examination in January 2022.

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Changes in digital technology, increasing volume of data collection, and advances in methods have the potential to unleash the value of big data generated through the education of health professionals. Coupled with this potential are legitimate concerns about how data can be used or misused in ways that limit autonomy, equity, or harm stakeholders. This consensus statement is intended to address these issues by foregrounding the ethical imperatives for engaging with big data as well as the potential risks and challenges.

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Problem: Competency-based medical education is increasingly regarded as a preferred framework for physician training, but implementation is limited. U.S.

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Article Synopsis
  • Between 0.25% and 3% of admissions to specialized care units like NICU, PICU, and PCICU require CPR, with most events occurring in infants under 1 year old, highlighting the need for optimized CPR approaches for this age group.
  • Current resuscitation practices differ for newborns (following neonatal guidelines) and older infants and children (following pediatric guidelines), yet there are no clear recommendations for transitioning between these two protocols.
  • The report reviews current guidelines, explores their application in hospitalized infants, and points out the absence of strong data to definitively dictate when to switch from neonatal to pediatric guidelines, leaving the choice to individual healthcare teams and institutions.
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Learning curves can be used to design, implement, and evaluate educational interventions. Attention to key aspects of the method can improve the fidelity of this representation of learning as well as its suitability for education and research purposes. This paper addresses when to use a learning curve, which graphical properties to consider, how to use learning curves quantitatively, and how to use observed thresholds to communicate meaning.

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Coaching is proposed as a means of improving the learning culture of medicine. By fostering trusting teacher-learner relationships, learners are encouraged to embrace feedback and make the most of failure. This paper posits that a cultural shift is necessary to fully harness the potential of coaching in graduate medical education.

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Background: Despite the constant presence of change and innovation in health professions education (HPE), there has been relatively little theoretical modelling of such change, the experiences of change, the ideology associated with change or the unexpected consequences of change. In this paper, the authors explore theoretical approaches to the adoption of innovations in HPE as a way of mapping a broader theoretical landscape of change.

Method: The authors, HPE researchers with an interest in technology adoption and systemic change, present a narrative review of the literature based on a series of thought experiments regarding how communities and individuals respond to the introduction of new ideas or methods.

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  • Researchers developed a statistical model to analyze how pathologists and residents rate prostate cancer images, focusing on their ability to distinguish cases near the diagnostic borderlines.
  • A study involving 36 physicians rated cases using the International Society of Urological Pathologists (ISUP) scale, revealing that expert raters effectively categorized samples across five severity levels.
  • The proposed method could be applied to other clinical scenarios where healthcare providers need to make ordinal assessments on varying medical conditions.
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Objective: We developed a web-based tool to measure the amount and rate of skill acquisition in pediatric interproximal caries diagnosis among pre- and postdoctoral dental students and identified variables predictive for greater image interpretation difficulty.

Study Design: In this multicenter prospective cohort study, a convenience sample of pre- and postdoctoral dental students participated in computer-assisted learning in the interpretation of bitewing radiographs of 193 children. Participants were asked to identify the presence or absence of interproximal caries and, where applicable, locate the lesions.

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  • The note discusses how to evaluate location parameters for items with multiple response options, useful in various fields like education and marketing.
  • It presents a point and interval estimation method within the context of latent variable modeling.
  • The method is easy to apply in real studies and can be executed using common software, with examples provided from empirical data.
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Competency-based medical education (CBME) requires a criterion-referenced approach to assessment. However, despite best efforts to advance CBME, there remains an implicit, and at times, explicit, demand for norm-referencing, particularly at the junction of undergraduate medical education (UME) and graduate medical education (GME). In this manuscript, the authors perform a root cause analysis to determine the underlying reasons for continued norm-referencing in the context of the movement toward CBME.

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The use of Artificial Intelligence (AI) in medical education has the potential to facilitate complicated tasks and improve efficiency. For example, AI could help automate assessment of written responses, or provide feedback on medical image interpretations with excellent reliability. While applications of AI in learning, instruction, and assessment are growing, further exploration is still required.

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The information systems designed to support clinical care have evolved separately from those that support health professions education. This has resulted in a considerable digital divide between patient care and education, one that poorly serves practitioners and organizations, even as learning becomes ever more important to both. In this perspective, we advocate for the enhancement of existing health information systems so that they intentionally facilitate learning.

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