Model Of Clinical Reasoning Research Articles

A graphical model to make explicit pharmacist clinical reasoning during medication review

Pharmacists’ roles have evolved substantially from traditional drug compounding and dispensing to encompass patient-centred clinical services. Pharmacist clinical reasoning, though fundamental to these new roles, generally remains implicit and understudied, particularly compared with that of other healthcare professionals, such as physicians. However, teaching and supervising the clinical services provided by pharmacists require a thorough understanding of the reasoning process involved. Several models describing pharmacist clinical reasoning have been developed, but they lack unified mapping.Here, we used an instrumental case study approach to develop a model of pharmacist clinical reasoning during medication review. Our model is adapted from a previously published modelling-using-typified-objects model of physician clinical reasoning in all its cognitive complexity. Our pharmacist model, validated after iterative development and expert consultation, aligns components of pharmacist clinical reasoning with those of physician clinical reasoning. The clinical case contains drug-related problems of variable clinical relevance, as well as numerous key elements (e.g., laboratory results, vital signs) necessary for conducting a medication review. The case serves both as the foundation for model development and as an illustrative step-by-step example within this article.Our model delineates the subprocesses of pharmacist clinical reasoning during medication review, offering a flexible, multipath structure that underscores the dynamic, nonlinear nature of the reasoning. The model might be able to clarify implicit cognitive processes, thus furthering the overarching objective of promoting reflective skill development among learners rather than relying solely on tacit knowledge gained through practice experience.

Informing the clinical reasoning of advanced practice students with nursing theories

This article examines the integration of a Clinical Nurse Reasoning (CNR) model into advanced nursing practice training to develop the clinical reasoning skills of advanced practice nurses. The article explores the contribution of Callista Roy's conceptual model of adaptation and presents a global analysis of a complex care situation that justifies the introduction of an CNR model paired with nursing knowledge to ensure comprehensive, quality nursing care.

Beyond thinking fast and slow: Implications of a transtheoretical model of clinical reasoning and error on teaching, assessment, and research

From dual process to a family of theories known collectively as situativity, both micro and macro theories of cognition inform our current understanding of clinical reasoning (CR) and error. CR is a complex process that occurs in a complex environment, and a nuanced, expansive, integrated model of these theories is necessary to fully understand how CR is performed in the present day and in the future. In this perspective, we present these individual theories along with figures and descriptive cases for purposes of comparison before exploring the implications of a transtheoretical model of these theories for teaching, assessment, and research in CR and error.

Dual process models of clinical reasoning: The central role of knowledge in diagnostic expertise.

Research on diagnostic reasoning has been conducted for fifty years or more. There is growing consensus that there are two distinct processes involved in human diagnostic reasoning: System 1, a rapid retrieval of possible diagnostic hypotheses, largely automatic and based to a large part on experiential knowledge, and System 2, a slower, analytical, conscious application of formal knowledge to arrive at a diagnostic conclusion. However, within this broad framework, controversy and disagreement abound. In particular, many authors have suggested that the root cause of diagnostic errors is cognitive biases originating in System 1 and propose that educating learners about the types of cognitive biases and their impact on diagnosis would have a major influence on error reduction. In the present paper, we take issue with these claims. We reviewed the literature to examine the extent to which this theoretical model is supported by the evidence. We show that evidence derived from fundamental research in human cognition and studies in clinical medicine challenges the basic assumptions of this theory-that errors arise in System 1 processing as a consequence of cognitive biases, and are corrected by slow, deliberative analytical processing. We claim that, to the contrary, errors derive from both System 1 and System 2 reasoning, that they arise from lack of access to the appropriate knowledge, not from errors of processing, and that the two processes are not essential to the process of diagnostic reasoning. The two processing modes are better understood as a consequence of the nature of the knowledge retrieved, not as independent processes.

The Operators Model of Psychoanalytic Clinical Reasoning.

In this paper, the authors develop a model of psychoanalytic clinical reasoning as the inferential process by which analytic therapists are able to arrive at an understanding of the clinical material. Starting from Bion's theory of functions, the authors propose that a "function" can be thought of as a condition-action sequence that analytic therapists implicitly use to respond to certain configurations of elements in the material by executing conceptual or reflective operations. To investigate the main families of functions that are used by analytic therapists in everyday practice, the authors used an interpersonal process recall procedure based on supervision sessions from a theoretically heterogeneous group of participants. A consensual procedure was developed to identify operations, spell out the underlying functions, and group functions into families. Twelve families of functions were identified that appear to be used by analytic therapists regardless of their schools of thought. The authors call them the "operators" of psychoanalytic clinical reasoning. According to the operators model, the process of psychoanalytic clinical reasoning consists in the chaining together of operations using functions from different families. A specific collection of "clinical reasoning styles" seems to be interwoven in this process. Different avenues open up for research, clinical practice, and training.

Effects of an unfolding case study on clinical reasoning, self-directed learning, and team collaboration of undergraduate nursing students: A mixed methods study

BackgroundClinical reasoning is an essential nursing competency that students must develop to provide safe patient care. Developing and utilizing unfolding case studies, which present constantly changing patient conditions to improve students' clinical reasoning and to foster communication and self-reflection, can help to achieve that imperative. ObjectivesTo develop an unfolding case study and to test its effectiveness in improving clinical reasoning, team collaboration, and self-directed learning. DesignA mixed methods design. SettingOne university in Southern Taiwan. ParticipantsForty nursing students. MethodsAn unfolding case study was developed based on the clinical reasoning model and unfolding cases model. The Nurses Clinical Reasoning Scale, Self-Directed Learning Instrument, and Questionnaire of Group Responsibility and Cooperation in Learning Teams were used. Forty nursing students completed questionnaires and nine of them participated in focus group discussions. Wilcoxon signed-rank, Spearman correlation, regression, and inductive content analysis were used to analyze data. ResultsStudents' abilities in clinical reasoning, self-directed learning, and team collaboration were statistically significantly improved after implementation of the unfolding case study. Emergent themes included “patient-centered communication,” “group inspiration and learning,” “thinking critically and reflecting on oneself,” and “applying theoretical knowledge in care to meet patients' changing needs.” ConclusionsUnfolding case studies provide a safe environment in which nursing students may learn and apply knowledge to safe patient care.

ICF in Bachelor degree programs-the implementation of the ICF in the clinical reasoning process of physical therapists for neurological patients-optimizing the health curriculum for comprehensive patient care.

The International Classification of Function, Disability, and Health (ICF) is known to be a valuable classification model in interprofessional neurorehabilitation, as it can lead to more patient-centered and self-determined treatment. To acquire the competencies implementing the ICF in the field of neurorehabilitation, it is important to anchor essential skills in the basic training of healthcare professionals. The Institute of Physiotherapy at FH JOANNEUM in Graz/Austria developed a concept to help students learn the necessary skills for implementing the ICF in a structured way. In the area of neurorehabilitation, we linked the ICF model with the Clinical Reasoning Model (CR). Competences are acquired over six semesters. Besides the general topics relating to the ICF (such as history, intention, and language) and CR that are taught in the first year, we focus in the later semesters explicitly on transferring these skills to neurorehabilitation. Therefore, we use interprofessional group work and problem-based courses as essential didactic elements for this transfer of skills. This article aims to show how the ICF could be implemented in Bachelor's degree programs for physiotherapy as well as in other healthcare programs. The authors' experiences are described and some best practice examples when working with the ICF in this field are given.

A19Identification of clinical reasoning models commonly used in simulation-based education

Simulation can immerse learners in scenarios that mimic clinical situations, simultaneously mitigating safety risks and increasing standardization in healthcare education [1]. Through simulation, learners can get the chance to develop clinical reasoning with focused learning opportunities [2]. Clinical reasoning is multidimensional in nature, and underdeveloped clinical reasoning skills and the risk of cognitive overload can potentially threaten patient safety and delay care, so it is important to systematize, optimize and structure clinical reasoning for simulation-based education [3]. That can be achieved through using valid clinical reasoning models but with careful consideration to the contributing and influencing factors of case complexity, staff seniority, competence, scope of practice, specialty and subspecialty. A scoping review was undertaken to answer the questions: what are the best available valid and reliable clinical reasoning models for simulation-based education? We searched Medline, Scopus, Education Research Complete and Google Scholar to identify relevant recent primary research conducted on this topic from 2000 onwards. The search included MeSH topics of ‘Clinical reasoning’, ‘Simulation-based education’ and ‘Clinical Reasoning models’. The inclusion criteria were primary studies describing the clinical reasoning models developed for simulation-based courses. Two independent researchers agreed on the inclusion of the identified articles for full-text review. This review followed the review guidelines of Joanne Briggs Institute. Five valid and reliable models to structure the clinical reasoning process while attending simulation-based training were identified and are reported in Identified clinical reasoning models based on the scoping review There is an adequate number of clinical reasoning models to be used while taking part in simulation-based training; however, there is a significant basis to test the reliability and validity of these models against different competence and seniority levels, and applicability to other healthcare professions. The authors are presently working on the development of a new model using an innovative and rigorous approach. Authors confirm that all relevant ethical standards for research conduct and dissemination have been met. The submitting author confirms that relevant ethical approval was granted, if applicable.

Cognitive processes in pharmacists’ clinical decision-making

BackgroundPharmacists’ clinical decision-making is a core process in pharmaceutical care. However, the practical aspects and effective teaching methods of this process remain largely unexplored. ObjectiveTo examine the cognitive processes involved in pharmacists’ perceptions of how they make clinical decisions in pharmacy practice. MethodsSemi-structured, face-to-face interviews were conducted with pharmacists working in community, outpatient, and hospital care in the Netherlands between August and December 2021. Participants were explicitly asked for examples when asked how they make clinical decisions in practice and how they teach this to others. After transcribing audio-recorded interviews, an inductive thematic analysis was conducted to identify cognitive processes. A theoretical model of clinical decision-making was then used and adapted to structure the identified processes. ResultsIn total, 21 cognitive processes were identified from interviews with 16 pharmacists working in community (n = 5), outpatient (n = 2), and hospital care (n = 9). These cognitive processes were organized into 8 steps of the adapted theoretical model, i.e. problem and demand for care consideration, information collection, clinical reasoning, clinical judgment, shared decision-making, implementation, outcomes evaluation, and reflection. Pharmacists struggled to articulate their clinical decision-making and went back-and-forth in their explanations of this process. All pharmacists emphasized the importance of identifying the problem and described how they collect information through reviewing, gathering, recalling, and investigating. Clinical reasoning entailed various cognitive processes, of which comprehending the problem in the patient's context was deemed challenging at times. Pharmacists seemed least active in evaluating patient outcomes and reflecting on these outcomes. ConclusionsPharmacists use multiple cognitive processes when making clinical decisions in pharmacy practice, and their back-and-forth explanations emphasize its dynamic nature. This study adds to a greater understanding of how pharmacists make clinical decisions and to the development of a theoretical model that describes this process, which can be used in pharmacy practice and education.

Development of higher-order thinking skills in nursing students through online problem-based assessment.

The development of higher-order thinking skills (HOTS) in problem-based learning (PBL) is not confined to teaching and learning but extends to authentic assessment methods, similar to real-life situations. The assessments aligned to PBL attempt to eliminate the students' tendency towards memorisation. Rather, it instils and encourages their ability to analyse, interpret, synthesise, and evaluate knowledge and its sources. The study had two primary aims: (1) to describe undergraduate nursing students' experiences of an online problem-based assessment (PBA), and (2) to explore how online PBA assessment contributed to the development of undergraduate student nurses' HOTS. An urban-based South African higher education institution (HEI) in KwaZulu-Natal, Durban, South Africa. A descriptive, exploratory qualitative approach was used. The target population was 4th-year psychiatric nursing students (N = 39) studying for the degree of Bachelor of Nursing at the preselected university, utilising two focus groups (n = 5, n = 7). Data were analysed through content analysis using the clinical reasoning model as a framework. Three categories (trigger problem, re-visioning the cues, treatment direction) and seven sub-categories (trigger problem posing, early cue identification, cue interpretation and clustering, focussed cue investigation, information processing and interpretation, reprioritise hypotheses, and diverse intervention[s]) emerged. Psychiatry, Nursing and Midwifery practices require a practitioner skilled in HOTS to provide quality, efficient and cost-effective patient care. The findings in this study can benefit nursing education, particularly learning interruptions in HEIs.

Psychometric Evaluation of the Nurse Clinical Reasoning Scale (NCRS): A Validation Study Among Italian Nurses.

Background and Purpose: Clinical reasoning for nurses is considered a valuable component of clinical nursing competencies, but there are few tools to ascertain this. This study tested the Italian Nurses Clinical Reasoning Scale (I-NCRS) psychometric properties based on Levett-Jones' theoretical clinical reasoning model. Methods: Content, face, and construct characteristics were ascertained for their validity. The study had a two-phase design: (a) content and face validity and (b) construct validity. Results: Three factors emerged from the factorial analysis of our reference sample: nursing problems of health, nursing information of health, and nursing assessment of health. Conclusions: The scale represents a valuable tool for the self-assessment of the clinical reasoning skills of nurses. I-NCRS showed evidence of validity and reliability, being also useful for assessing clinical reasoning for educational and research purposes among Italian nurses.

Physiotherapists’ clinical reasoning in examination of clients with low back pain in direct access practice: a theory-driven qualitative content analysis

Aim The aim of this study was to gain deeper understanding of physiotherapists’ clinical reasoning in examination of clients with low back pain (LBP) in direct access (DA) practice. Method Data were collected through individual semi-structured thematic interviews of ten physiotherapists who described their clinical reasoning in one of their LBP clients in direct access practice. The interviews were recorded and transcribed verbatim and then examined using a theory-driven qualitative content analysis. Four clinical reasoning models, hypothetico-deductive, pattern recognition, narrative and systematic, were used as theoretical frameworks to analyse the descriptions of physiotherapists’ clinical reasoning in examination. Results In this study clinical reasoning in examination manifested as a process where physiotherapist proceeds from interview to clinical assessment and decision-making, simultaneously taking into consideration the DA setting and the specific role of the physiotherapist. As described by the physiotherapists working in DA practice clinical reasoning in examination presented by extracting facts from the interview in relation to symptoms or certain diagnosis, identifying and excluding red flags and identifying the factors that were important to consider in acute musculoskeletal pain in relation to individual client’s problem. Physiotherapists described having improved differential diagnostic skills, wider range of physical assessment techniques and more precise assessment. Based on the data, the physiotherapists presented to use either the hypothetico–deductive or the systematic clinical reasoning model when examining an LBP client in DA practice. Conclusions Clinical reasoning in examination with LBP clients in direct access practice started with anamnesis and proceeded by using either the hypothetico–deductive or the systematic clinical reasoning model.

The Outcome-Present State Test Model of Clinical Reasoning to Promote Critical Thinking in Psychiatric Nursing Practice among Nursing Students: A Mixed Research Study

In this interventional study, 19 students were taught critical thinking skills using the OPT clinical reasoning model during a psychiatry clinical practice. Work-learning forms were used in daily 1 h individual and group discussions with students. The critical thinking disposition scale was completed by every student before and after the intervention. Moreover, the students were asked to the complete reflection experience forms. The average critical thinking disposition pre-intervention score was 95.21, whereas the average post-intervention score was 97.05, indicating an increase of 1.84. There was a significant increase in the fourth dimension of open-mindedness (z = -2.80, p < 0.01). The learning experience has been likened to a process of clearing the fog, and it involves the use of limited known conditions, thinking outside the box, and adaptation to complex care issues. Using the OPT clinical reasoning model as a teaching strategy during a psychiatric nursing internship significantly improved the open-mindedness dimension among the students. The student reflective experience of talking to teachers as peers helped students identify clues and reframe problems related to clinical care. Additionally, the students reported that this led to more harmonious interactions with their teachers.

Context matters: toward a multilevel perspective on context in clinical reasoning and error.

Context in diagnosis and management of patients is a vexing phenomenon in medicine and health professions education that can lead to unwanted variation in clinical reasoning performance and even errors that cause patient harm. Studies have examined individual-, team-, andsystem-level contextual factors, but the ways in whichmultiple contextual factors can interact, how both distracting and enabling factors can impact performance and error, and the boundaries between context and content information are not well understood. In this paper, we use a theory-based approach to enhance our understanding ofcontext. We introduce a multilevel perspective on context that extends prior models of clinical reasoning and propose a micro-meso-macro framework to provide a more integrated understanding of how clinical reasoning is bothinfluenced by and emerges from multiple contextual factors. The multilevel approach can also be used to study other social phenomena in medicine such as professionalism, learning, burnout, and implicit bias. We call for a new paradigm in clinical reasoning research and education that uses multilevel theory and analysis to enhance clinical reasoning performance expertise and improve the quality of patient care.

Co-design: a guided reflective learning conversation model for simulation-based education

The critical care environment is stressful with complex clinical cases and high levels of workload [1]. Adequate exposure to various clinical experiences is essential to develop effective clinical reasoning skills [2]. Taking into consideration the risk of clinical practice mistakes and the importance of patient safety, simulation is an effective method to immerse learners in scenarios that mimic clinical situations with focused learning opportunities. Guided reflection through reflective learning conversations following simulation activities is recognized as an effective method to develop clinical reasoning skills [3]. We describe a co-design process to develop a simulation guided reflective learning conversation model to optimize the clinical reasoning skills for critical care nurses attending simulation-based activities. A co-design working group of 10 critical care nurses of varying levels of seniority, experience, nationality, and gender; two critical care doctors; three patient representatives; 2 researchers, and 5–6 critical care educators are working collaboratively to co-design the guided reflective learning conversation model, in which clinical reasoning can be optimized with consideration to a wide range of case complexity, subspecialty, and competence levels. The co-design working group is meeting online for 4–6 workshops of 4 hours. The co-design process is built on valid and reliable clinical reasoning and educational theoretical frameworks and models. The inputs to the process, exercises, and activities are taking place during the workshops and the outputs of the workshops are described to establish the co-design process. The final draft of the model will be validated and tested. The study sample will be grouped into experimental and control cohorts of critical care nurses who attend critical care simulation-based courses (N=300). Data will be collected through surveys, focus groups, and simulation-based objective assessment and observations. The study has received Institutional Review Board approval from the Hamad Medical Corporation Medical Research Centre (MRC-01-22-117) and the University of Hertfordshire (HSK/PGR/UH/04728). The first draft of the co-design model is presented in Simulation-Based Reflective Learning Conversation Model (SBRLCM) under development Clinical reasoning is multidimensional with difficulty to structure and evaluate during debriefing. Developing a guided reflective learning conversation model in which clinical reasoning skills are actively and effectively embedded, would therefore enable critical care nurses developing clinical reasoning skills to meet the special demands of critical care. 1. Vahedian-Azimi A, Hajiesmaeili M, Kangasniemi M, Fornés-Vives J, Hunsucker RL, Rahimibashar F, Pourhoseingholi MA, Farrokhvar L, Miller AC. Effects of stress on critical care nurses: a national cross-sectional study. Journal of intensive care medicine. 2019;34(4):311–22. 2. Kang H, Kang HY. The effects of simulation-based education on the clinical reasoning competence, clinical competence, and educational satisfaction. Journal of the Korea Academia-Industrial cooperation Society. 2020;21(8):107–14. 3. Decker S, Alinier G, Crawford SB, Gordon RM, Jenkins D, Wilson C. Healthcare Simulation Standards of Best Practice

Clinical Reasoning in Cardiology: Past, Present and Future.

Clinical reasoning was born 2,500 years ago with Hippocrates, having evolved over the centuries, becoming a mixture of art and science. Several personalities throughout history have contributed to improving diagnostic accuracy. Nonetheless, diagnostic error is still common and causes a severe impact on healthcare systems. To face this challenge, several clinical reasoning models have emerged to systematize the clinical thinking process. This paper describes the history of clinical reasoning and current diagnostic reasoning methods, proposes a new clinical reasoning model, called Integrative Reasoning, and brings perspectives about the future of clinical reasoning.

Adaptation of a clinical reasoning model for use in inflammatory conditions of the lactating breast: a retrospective mixed-methods study.

Background:Many potential factors associated with Inflammatory Conditions of the Lactating Breast (ICLB) have been reported in the literature, by lactating mothers and clinicians. Clinicians, including general practitioners, lactation consultants and physiotherapists, require a clinical reasoning model that summarises associated or linked factors, to aid in the assessment, treatment, and prevention of ICLB. Thus, we aimed to adapt the existing Breastfeeding Pain Reasoning Model (BPRM), for use in the management of ICLB, using prior research and clinical audit data to guide adaptation. The existing BPRM categorises contributing factors for breastfeeding nipple pain, rather than ICLB.Methods:Factors linked with ICLB were identified from prior research and considered for inclusion into the existing model. Clinical data from a retrospective audit of ICLB patient notes at a private physiotherapy practice were also examined. Any factors identified from prior research that could not be identified in the clinical notes were not considered for inclusion into the existing model. Additional factors from the clinical notes that appeared repeatedly were considered for inclusion into the adaptation of the BPRM. A draft adapted model was created comprising all eligible factors, considering their counts and percentages as calculated from the clinical data. The research team iteratively examined all factors for appropriate categorisation and modification within the adapted model.Results:Prior research and data from 160 clinical notes were used to identify factors for inclusion in the adapted model. A total of 57 factors, 13 pre-existing in the BPRM and 44 extra identified from the prior research or clinical audit, comprised the draft adapted model. Factor consolidation and terminology modification resulted in a total of 34 factors in the final proposed adapted ICLB model. The three main categories, CNS modulation, External influences and Local stimulation, from the existing model were maintained, with one minor terminology change to the former Local stimulation category, resulting in ‘Local influences’ category. Terminology for five subcategories were modified to better reflect the types of factors for ICLB. The most common factors in the adapted model, calculated from the clinical audit population of mothers with ICLB, were employment (85%), high socioeconomic status (81%), antibiotic use during breastfeeding (61%), history of an ICLB (56%), any breast pump use (45%), multiparity (43%), birth interventions (35%), decreased milk transfer (33%), breastfeeding behaviour and practices (33%), nipple pain (30%) and fit and hold (attachment and positioning) difficulty (28%).Conclusion:An ICLB-specific linked factors model is proposed in this paper. Clinicians treating mothers with ICLB can use this model to identify influencing and determining factors of ICLB clinical presentations and provide targeted education and effective treatment plans.

Approaches that promote clinical reasoning in clinical and simulation-based practice settings

Background: Clinical reasoning is described as a reflective process that enables health care practitioners to collect data, solve problems, and make decisions and judgments to enhance patient outcomes and patient safety 1. To avoid practice mistakes, healthcare professionals should possess or develop effective clinical reasoning skills. To develop effective clinical reasoning skills, enough exposure to various experiences is required. Practicing and developing clinical reasoning skills can be achieved in both clinical and simulated settings 2. Using structured clinical reasoning models could enhance effective clinical reasoning development 3. This review aims to explore the current clinical reasoning models. Methods: A scoping review was undertaken to answer the question; what are the best available clinical reasoning models to enhance clinical reasoning in clinical and simulated settings? The following sources were searched: Medline; Scopus; Education Research Complete, and Google Scholar to identify relevant recent primary research conducted on this topic published in 2000 onwards. The search included [MeSH] topics of; “Clinical reasoning” and “Clinical Reasoning Models”. The inclusion criteria were primary studies that described the use of clinical reasoning models in clinical and simulated settings. Two independent researchers agreed on the inclusion of the identified papers for full-text review. This review followed the review guidelines of the Joanne Briggs institute. Results: There are valid clinical reasoning models to be used for clinical and simulated settings which are; TANNER, DML, clinical Reasoning Model (CRM), Outcome-Present State Test (OPT), and Self-Regulated Learning (SRL) model (Table 1). However, the validity of these models needs to be tested considering different health care specialties, the scope of practice, complexity, and seniority levels. Conclusion: Considering the importance of clinical reasoning skills in health care practices, using structured models could enhance the clinical reasoning process, however, despite the availability of clinical reasoning models, additional validation for these models is still required.

Developing BENDi: A BayEsian Network DecIsion support tool for managing low back pain

Purpose: Artificial intelligence (AI) tools have the potential to address the complexity of clinical decision making and possibly limit the bias inherent in individual decision making. Poor outcomes for patients with low back pain are common and it continues to be burdensome condition for both patients and the NHS. There is a resultant imperative to ensure patients receive the right treatment at the right time. A decision support tool for LBP developed with a Delphi approach has been implemented with some success in the past, but could results be improved with AI techniques? This study proposes and pilots a method for building an AI clinical reasoning model using expert judgements from MSK practitioners.

Syncing Our Global Thinking: A Framework for Contextualized Clinical Reasoning

PurposeGlobally, health care practitioners (HCPs) practice in a variety of settings. To account for the diversity of these contexts, HCPs should utilize dynamic clinical reasoning skills to provide contextually responsive services that account for the complexities of patients, clinicians, and their surroundings. However, traditional models of clinical reasoning approach this skill in a reductionistic and segmented manner that ignores the impact of these diverse factors in health care provision. This makes it very difficult to reconcile these models with the realities of practice.MethodBy repositioning clinical reasoning as a unique and dynamic skill and identifying the shortcomings of traditional clinical reasoning models, we suggest a novel theoretical framework:contextualized clinical reasoning, which centralizes factors related to context and individual within its approach.ConclusionsIn order to practice clinical reasoning in an authentic manner that recognizes the impact of contextual and personal realities, we put forward thecontextualized clinical reasoningframework. This framework gives HCPs the tools needed to change the rhetoric on best practice and provide effective health care services that account for complexity and diversity of health care contexts globally.