Clinical Reasoning In Medicine Research Articles

Exploring the interplay of clinical reasoning and artificial intelligence in psychiatry: Current insights and future directions

For many years, it has been widely accepted in the psychiatric field that clinical practice cannot be reduced to finely tuned statistical prediction systems utilizing diverse clinical data. Psychiatrist clinicians are recognized for their unique and irreplaceable roles. In this brief historical overview, viewed through the lens of artificial intelligence (AI), we propose that comprehending the reasoning behind AI can enhance our understanding of clinical reasoning. Our objective is to systematically identify the factors that shape clinical reasoning in medicine, based on six factors that were historically considered beyond the reach of statistical methods: open-endedness, unanalyzed stimulus-equivalences, empty cells, theory mediation, insufficient time, and highly configured functions. Nevertheless, a pertinent consideration in the age of AI is whether these once-considered insurmountable specific factors of psychiatric clinicians are now subject to scrutiny or not. Through example in AI, we demonstrate that a deeper understanding of these factors not only sheds light on clinical decision-making and its heuristic processes but also underscores the significance of collaboration between AI experts and healthcare professionals. This comparison between AI and clinical reasoning contributes to a better grasp of the current challenges AI faces in the realm of clinical medicine.

Clinical reasoning in medicine I: A historical journey

Medical error is a public health problem, that may be related to failures in a doctor’s decisionmaking about a patient’s diagnosis, treatment, or prognosis, that is, in medical reasoning. Despite its importance, the understanding of clinical reasoning has been heterogeneous, with the use of multiple definitions and theoretical models, which focus on different aspects of the processing that physicians elaborate about taking care of a patient. This conceptual diversity can be explained by the influence of the historical context. How physicians think can be seen from magical thinking in Antiquity, through Renaissance rationalism and the modern scientific approach, to current models of dual thinking and probability estimation. What seems to be constant is that it has an explanatory mission of knowing what happens to the patient, although the ultimate goal is more to understand the patient’s experience. In this narrative review, this evolution is presented with a timeline, which summarizes the ways of conceiving reasoning in medicine according to the historical context.

Books: The Hands-on Guide to Clinical Reasoning in Medicine: Developing Clinical Reasoning.

Mujammil Irfan Wiley-Blackwell, 2019, PB, 368pp, £29.19, 978-1119244035 The Hands-on Guide to Clinical Reasoning in Medicine aims to provide a practical approach to undertake clinical reasoning for medical students in their training years, newly qualified doctors, and advanced nurse practitioners. The book is written in an informal, conversational style with a friendly and coaching feel. To engage fully …

Efficient clinical reasoning: Knowing when to start and when to stop

Purpose: While clinical reasoning in medicine traditionally values the ultimate goal of providing an accurate diagnosis of disease, insufficient emphasis has been placed on how students' decisions may affect their diagnostic efficiency. This study adds new empirical evidence about what makes students efficient problem-solvers in clinical reasoning. Methods: Seventy-five medical students participated in this study in 2015. The authors compared the differences in clinical reasoning behaviors between high- and low-performing students before they proposed any diagnostic hypothesis. The authors used the Cox proportional-hazards model to explore how certain characteristics of students and essential features of reasoning processes affect the life span of incorrect hypotheses. Results: High-performing students were more prepared than low performers to propose their first hypothesis. The more laboratory tests and hypotheses the medical students had, the longer it took for them to confirm a correct diagnosis. Male students tended to finalize the correct diagnosis earlier than females. There are no differences between the easy and the difficult cases in the aforementioned patterns. Conclusion: This study helps shift the emphasis away from a solitary focus on accuracy to one that considers the importance of diagnostic efficiency. The authors discussed two main take-home messages for physicians.

A qualitative study of experienced clinical teachers’ conceptualisation of clinical reasoning in medicine: Implications for medical education

Introduction: Clinical reasoning is an essential part of medical practice. Training medical students to reason competently is, therefore, an essential skill for clinical teachers. Ongoing debate over what clinical reasoning entails and difficulty explicitly teaching and assessing. it makes this a challenging task. This study explored clinical teachers’ understanding of the concept of clinical reasoning. Methods: Nine experienced clinical teachers participated in semi-structured interviews about clinical reasoning, exploring concepts, experiences, teaching and assessment. Interviews were transcribed and analysed thematically. Results: Ten key themes were identified in relation to participants’ understanding of clinical reasoning. These include the findings that clinical reasoning is: essential to medical practice, goal oriented, an applied cognitive process and an unconscious process. Clinical reasoning has several requirements, including knowledge, communication skills, experience and reflection. Participants reported that clinical reasoning is difficult, perhaps impossible, to teach. Conclusions: In this qualitative study, clinical teachers concurred with many of the characteristics of clinical reasoning as it is understood in the literature, but they also challenged assumptions made in medical education research regarding the conceptualisation of clinical reasoning. This has implications for teaching, assessment, student selection and professional development.

Clinical Reasoning in Medicine: A Concept Analysis

Background: Clinical reasoning plays an important role in the ability of physicians to make diagnoses and decisions. It is considered the physician’s most critical competence, but it is an ambiguous concept in medicine that needs a clear analysis and definition. Our aim was to clarify the concept of clinical reasoning in medicine by identifying its components and to differentiate it from other similar concepts. It is necessary to have an operational definition of clinical reasoning, and its components must be precisely defined in order to design successful interventions and use it easily in future research. Methods: McKenna’s nine-step model was applied to facilitate the clarification of the concept of clinical reasoning. The literature for this concept analysis was retrieved from several databases, including Scopus, Elsevier, PubMed, ISI, ISC, Medline, and Google Scholar, for the years 1995– 2016 (until September 2016). An extensive search of the literature was conducted using the electronic database. Accordingly, 17 articles and one book were selected for the review. We applied McKenna’s method of concept analysis in studying clinical reasoning, so that definitional attributes, antecedents, and consequences of this concept were extracted. Results: Clinical reasoning has nine major attributes in medicine. These attributes include: (1) clinical reasoning as a cognitive process; (2) knowledge acquisition and application of different types of knowledge; (3) thinking as a part of the clinical reasoning process; (4) patient inputs; (5) contextdependent and domain-specific processes; (6) iterative and complex processes; (7) multi-modal cognitive processes; (8) professional principles; and (9) health system mandates. These attributes are influenced by the antecedents of workplace context, practice frames of reference, practice models of the practitioner, and clinical skills. The consequences of clinical reasoning are the metacognitive improvement of reasoning and tacit knowledge production. Conclusion: The present concept analysis tries to clarify the concept of clinical reasoning in medicine and reduces the ambiguity of this concept to design successful interventions and use it easily in future research. Keywords: CLINICAL REASONING, MEDICINE, CONCEPT ANALYSIS, MCKENNA’S MODEL

Transforming Medical Assessment: Integrating Uncertainty Into the Evaluation of Clinical Reasoning in Medical Education.

In an age where practicing physicians have access to an overwhelming volume of clinical information and are faced with increasingly complex medical decisions, the ability to execute sound clinical reasoning is essential to optimal patient care. The authors propose two concepts that are philosophically paramount to the future assessment of clinical reasoning in medicine: assessment in the context of "uncertainty" (when, despite all of the information that is available, there is still significant doubt as to the best diagnosis, investigation, or treatment), and acknowledging that it is entirely possible (and reasonable) to have more than "one correct answer." The purpose of this article is to highlight key elements related to these two core concepts and discuss genuine barriers that currently exist on the pathway to creating such assessments. These include acknowledging situations of uncertainty, creating clear frameworks that define progressive levels of clinical reasoning skills, providing validity evidence to increase the defensibility of such assessments, considering the comparative feasibility with other forms of assessment, and developing strategies to evaluate the impact of these assessment methods on future learning and practice. The authors recommend that concerted efforts be directed toward these key areas to help advance the field of clinical reasoning assessment, improve the clinical care decisions made by current and future physicians, and have positive outcomes for patients. It is anticipated that these and subsequent efforts will aid in reaching the goal of making future assessment in medical education more representative of current-day clinical reasoning and decision making.

An analysis of clinical reasoning through a recent and comprehensive approach: the dual-process theory

Context. Clinical reasoning plays a major role in the ability of doctors to make diagnoses and decisions. It is considered as the physician's most critical competence, and has been widely studied by physicians, educationalists, psychologists and sociologists. Since the 1970s, many theories about clinical reasoning in medicine have been put forward.Purpose. This paper aims at exploring a comprehensive approach: the “dual-process theory”, a model developed by cognitive psychologists over the last few years.Discussion. After 40 years of sometimes contradictory studies on clinical reasoning, the dual-process theory gives us many answers on how doctors think while making diagnoses and decisions. It highlights the importance of physicians’ intuition and the high level of interaction between analytical and non-analytical processes. However, it has not received much attention in the medical education literature. The implications of dual-process models of reasoning in terms of medical education will be discussed.

University of Nevada School of Medicine

University of Nevada School of Medicine

Clinical reasoning in medicine and nursing: Decision making versus problem solving

The clinical reasoning process includes two broad components: (a) problem solving (searching for the one “right”; answer) and (b) decision making (selecting from several possibilities). Each component requires considerable knowledge and skill; decision making also requires that the values assigned to each potential outcome be ascertained and used. We present a framework for the clinical encounter, with particular emphasis on treatment selection. We then note evidence, including three studies conducted by our research group, to support the view that clinical problem solving is based primarily on pattern recognition following data gathering, rather than on a deterministic rule‐based approach. We suggest that a pattern recognition approach, which stresses the importance of a knowledge base as opposed to a set of learned skills, implies a strong potential role for the computer in both medical practice and medical education.

Clinical Reasoning in Medicine Compared With Clinical Reasoning in Occupational Therapy

This article highlights some observations made in the American Occupational Therapy Association/American Occupational Therapy Foundation Clinical Reasoning Study, an ethnographic study of 14 occupational therapists working in a large teaching hospital. Concepts and premises that frequently appear in the clinical reasoning in medicine literature are discussed and compared and contrasted to observations and interpretations made of the practice and reasoning strategies of the occupational therapists who were participants in the Clinical Reasoning Study. It is postulated that similarities in the reasoning strategies of the members of the two professions are a result of use of the scientific model that calls for hypothetical reasoning. Differences, it is proposed, are accounted for by the difference in the particular focus, goals, and tasks of the two professions and the nature of the practice in those arenas. Five hypotheses are proposed as questions for further research in clinical reasoning in occupational therapy.