Using Relational Reasoning Strategies to Help Improve Clinical Reasoning Practice

A comprehensive approach to identify challenges for clinical reasoning development in undergraduate dental students and their potential solutions

INTRODUCTION

Clinical reasoning is a core competence in health professions that impacts the ability to solve patients' health problems. Due to its relevance, it is necessary to identify difficulties arising from different sources that affect clinical reasoning development in students. The aim of this study was to explore a comprehensive approach to identify challenges for clinical reasoning development in undergraduate dental students and their potential solutions.

METHODS

Mixed methods were used in four stages: (1) students and clinical teachers focus groups to identify challenges to clinical reasoning development; (2) literature review to explore potential solutions for these challenges; (3) Delphi technique for teacher consensus on pertinence and feasibility of solutions (1-5 scale); and (4) teachers' self-perception of their ability to implement the solutions.

RESULTS

Three categories and seven subcategories of challenges were identified: (I) educational context factors influencing the clinical reasoning process; (II) teacher's role in clinical reasoning development; and (III) student factors influencing the clinical reasoning process. From 134 publications identified, 53 were selected for review, resulting in 10 potential solutions. Through two Delphi rounds, teachers rated the potential solutions very highly in terms of relevance (4.50-4.85) and feasibility (3.50-4.29). Finally, a prioritisation ranking of these solutions was generated using their scores for relevance, feasibility, and teachers' self-perception of their ability to implement them.

CONCLUSIONS

The present comprehensive approach identified challenges for clinical reasoning development in dental students and their potential solutions, perceived as relevant and feasible by teachers, requiring further research and follow-up actions to address them.

Reasoning like a doctor or like a nurse? A systematic integrative review

When physicians and nurses are looking at the same patient, they may not see the same picture. If assuming that the clinical reasoning of both professions is alike and ignoring possible differences, aspects essential for care can be overlooked. Understanding the multifaceted concept of clinical reasoning of both professions may provide insight into the nature and purpose of their practices and benefit patient care, education and research. We aimed to identify, compare and contrast the documented features of clinical reasoning of physicians and nurses through the lens of layered analysis and to conduct a simultaneous concept analysis. The protocol of this systematic integrative review was published doi: 10.1136/bmjopen-2021-049862. A comprehensive search was performed in four databases (PubMed, CINAHL, Psychinfo, and Web of Science) from 30th March 2020 to 27th May 2020. A total of 69 Empirical and theoretical journal articles about clinical reasoning of practitioners were included: 27 nursing, 37 medical, and five combining both perspectives. Two reviewers screened the identified papers for eligibility and assessed the quality of the methodologically diverse articles. We used an onion model, based on three layers: Philosophy, Principles, and Techniques to extract and organize the data. Commonalities and differences were identified on professional paradigms, theories, intentions, content, antecedents, attributes, outcomes, and contextual factors. The detected philosophical differences were located on a care-cure and subjective-objective continuum. We observed four principle contrasts: a broad or narrow focus, consideration of the patient as such or of the patient and his relatives, hypotheses to explain or to understand, and argumentation based on causality or association. In the technical layer a difference in the professional concepts of diagnosis and the degree of patient involvement in the reasoning process were perceived. Clinical reasoning can be analysed by breaking it down into layers, and the onion model resulted in detailed features. Subsequently insight was obtained in the differences between nursing and medical reasoning. The origin of these differences is in the philosophical layer (professional paradigms, intentions). This review can be used as a first step toward gaining a better understanding and collaboration in patient care, education and research across the nursing and medical professions.

Intensive Care Unit Decision-Making in Uncertain and Stressful Conditions Part 2: Cognitive Errors, Debiasing Strategies, and Enhancing Critical Thinking

Diagnostic errors are considered a blind spot of health care delivery and occur in up to 15% of patient cases. Cognitive failures are a leading cause of diagnostic error and often occur as a result of overreliance on system 1 thinking. This narrative review describes why diagnostic errors occur by shedding additional light on systems 1 and 2 forms of thinking, reviews literature on debiasing strategies in medicine, and provides a framework for teaching critical thinking in the intensive care unit as a strategy to promote learner development and minimize cognitive failures.

The Complexity of the Retropubic Midurethral Sling: A Cognitive Task Analysis

OBJECTIVE

The primary aim of this study was to use cognitive task analysis to expand the retropubic midurethral sling into smaller steps, reflecting a surgeon's internal thought processes during the surgery.

METHODS

Two surgeons and a cognitive psychologist collaborated with expert urogynecologic surgeons in structured discussions and semistructured interviews, iteratively creating a list of clinical steps for the midurethral sling. They primarily considered 2 questions: (1) what action does the expert perform for this step, and (2) what information does the expert need to complete the step? We defined each additional piece of detail within a step as a microstep. The cognitive task analysis list was further reviewed by 4 external expert urogynecologic surgeons to obtain further detail. The process was repeated for every step until the maximum level of detail was reached. We used multiple methods to explore the relationship between microsteps and the cognitive load associated with various portions of the surgery.

RESULTS

Cognitive task analysis expanded the midurethral sling from 23 to 197 microsteps. Steps with the greatest number of microsteps included retropubic advancement with the trocar (19 microsteps) and ventral advancement of the trocar through the skin (17 microsteps).

CONCLUSIONS

The retropubic midurethral sling is a complex surgery with multiple microsteps embedded within in each step. Identification of these steps can lead to strategies to minimize cognitive load encouraging both efficacy and safety. Surgical training interventions and competency assessment can be developed based on this content.

Controversies in diagnosis: contemporary debates in the diagnostic safety literature

Since the 2015 publication of the National Academy of Medicine's (NAM) Improving Diagnosis in Health Care (Improving Diagnosis in Health Care. In: Balogh EP, Miller BT, Ball JR, editors. Improving Diagnosis in Health Care. Washington (DC): National Academies Press, 2015.), literature in diagnostic safety has grown rapidly. This update was presented at the annual international meeting of the Society to Improve Diagnosis in Medicine (SIDM). We focused our literature search on articles published between 2016 and 2018 using keywords in Pubmed and the Agency for Healthcare Research and Quality (AHRQ)'s Patient Safety Network's running bibliography of diagnostic error literature (Diagnostic Errors Patient Safety Network: Agency for Healthcare Research and Quality; Available from: https://psnet.ahrq.gov/search?topic=Diagnostic-Errors&f_topicIDs=407). Three key topics emerged from our review of recent abstracts in diagnostic safety. First, definitions of diagnostic error and related concepts are evolving since the NAM's report. Second, medical educators are grappling with new approaches to teaching clinical reasoning and diagnosis. Finally, the potential of artificial intelligence (AI) to advance diagnostic excellence is coming to fruition. Here we present contemporary debates around these three topics in a pro/con format.

"Starting from a higher place": linking Habermas to teaching and learning clinical reasoning in the emergency medicine context

Teaching clinical reasoning in emergency medicine requires educators to foster diagnostic accuracy and judicious decision-making amidst chaotic ambient factors including clinician fatigue, high cognitive load, and diverse patient expectations. The current study applies the early work of Jurgen Habermas and his knowledge-constitutive interests as a lens to explore an educational approach where physician-educators were asked to make their expert reasoning visible to emergency medicine trainees, to more deliberately make visible and accessible the context-specific thinking that emergency physicians routinely use. An action research methodology was used. The 'making thinking visible' teaching approach was introduced to five emergency medicine educators working in large public hospital emergency departments. Participants were asked to trial this teaching method and document its impact on student learning over two reporting cycles. Based on written reports of trialing the teaching approach, participants identified a need to change from: (1) introducing thinking structures to cultivating enquiry; and, (2) providing explanations based on cognitive thinking routines towards encouraging the learner to see the relevance of the clinical context. Educators described how they developed a more diagnostic and reflexive approach to learners, recognized the need to cultivate independent thinking, and valued the opportunity to reflect on their usual teaching. Teaching clinical reasoning using the 'making thinking visible' approach prompted educators to decrease the emphasis on providing technical information to assisting learners to understand the purposes and meanings behind clinical reasoning in emergency medicine. The knowledge-constitutive interests work of Jurgen Habermas was found to provide a robust framework supporting this emancipatory teaching approach.

The neurocognitive gains of diagnostic reasoning training using simulated interactive veterinary cases

The present longitudinal study ascertained training-associated transformations in the neural underpinnings of diagnostic reasoning, using a simulation game named “Equine Virtual Farm” (EVF). Twenty participants underwent structural, EVF/task-based and resting-state MRI and diffusion tensor imaging (DTI) before and after completing their training on diagnosing simulated veterinary cases. Comparing playing veterinarian versus seeing a colorful image across training sessions revealed the transition of brain activity from scientific creativity regions pre-training (left middle frontal and temporal gyrus) to insight problem-solving regions post-training (right cerebellum, middle cingulate and medial superior gyrus and left postcentral gyrus). Further, applying linear mixed-effects modelling on graph centrality metrics revealed the central roles of the creative semantic (inferior frontal, middle frontal and angular gyrus and parahippocampus) and reward systems (orbital gyrus, nucleus accumbens and putamen) in driving pre-training diagnostic reasoning; whereas, regions implicated in inductive reasoning (superior temporal and medial postcentral gyrus and parahippocampus) were the main post-training hubs. Lastly, resting-state and DTI analysis revealed post-training effects within the occipitotemporal semantic processing region. Altogether, these results suggest that simulation-based training transforms diagnostic reasoning in novices from regions implicated in creative semantic processing to regions implicated in improvised rule-based problem-solving.

Dynamic Measurement in Health Professions Education: Rationale, Application, and Possibilities

Dynamic measurement modeling (DMM) is a psychometric paradigm that uses longitudinal data to estimate individual students' growth in measured skills over the course of an educational program (i.e., growth scores). DMM represents a more formal way of assessing learning progress across the health professions education continuum. In this article, the authors provide justification for this approach in health professions education and demonstrate its proof-of-concept use with three time points of United States Medical Licensing Examination Step exams to generate growth scores for 454 current and recent medical learners. The authors demonstrate that learners vary substantially on their growth scores, and those growth scores exhibit psychometric reliability. In addition, growth scores significantly and positively correlated with indicators of medical learner readiness (e.g., undergraduate grade point average and Medical College Admission Test scores). These growth scores were also capable of significantly and positively correlating with future ratings of clinical competencies during internship as assessed through a survey sent to their program directors at the end of the first postgraduate year (e.g., patient care, interpersonal skills). These preliminary findings of reliability and validity for DMM growth scores provide initial evidence for further investigation into the suitability of a dynamic measurement paradigm in health professions education.

Clinical Reasoning and Knowledge Organization: Bridging the Gap Between Medical Education and Neurocognitive Science

PURPOSE

The purpose of this pilot study was 2-fold. The first was to investigate the conceptual relationship between previously validated methodologies. The second was to establish a linkage between medical education research and current neurocognitive science that accounts for knowledge organization during the clinical reasoning process.

METHODS

Transcripts of Think Aloud interviews conducted after an objective structured clinical examination (n = 12) were coded and analyzed into 3 clinical reasoning competencies (semantic, diagnostic, and knowledge network organization). Correlational analyses were conducted to establish relationships between the 2 methodologies. Analyses of variance examined group differences.

RESULTS

Significant correlations with large effect sizes were found between semantic, diagnostic, and knowledge network organization variables. Analysis of variance results approach significant difference in the knowledge network organization between weak versus strong diagnosticians.

CONCLUSIONS

Knowledge network organization measurement can be used to discern differences in clinical reasoning and may offer explanations for the variation in health professionals' diagnostic performance.