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Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

ABSTRACT: Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty.

SUBMITTER: Hege I

PROVIDER: S-EPMC5827186 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

Hege Inga I Kononowicz Andrzej A AA Berman Norman B NB Lenzer Benedikt B Kiesewetter Jan J

GMS journal for medical education 20180215 1

<b>Background:</b> Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key co ...[more]

PMID: 29497697

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Project description:BackgroundImproving clinical reasoning skills-the thought processes used by clinicians to formulate appropriate questions and diagnoses-is essential for reducing missed diagnostic opportunities. The electronic Clinical Reasoning Educational Simulation Tool (eCREST) was developed to improve the clinical reasoning of future physicians. A feasibility trial demonstrated acceptability and potential impacts; however, the processes by which students gathered data were unknown.ObjectiveThis study aims to identify the data gathering patterns of final year medical students while using eCREST and how eCREST influences the patterns.MethodsA mixed methods design was used. A trial of eCREST across 3 UK medical schools (N=148) measured the potential effects of eCREST on data gathering. A qualitative think-aloud and semistructured interview study with 16 medical students from one medical school identified 3 data gathering strategies: Thorough, Focused, and Succinct. Some had no strategy. Reanalysis of the trial data identified the prevalence of data gathering patterns and compared patterns between the intervention and control groups. Patterns were identified based on 2 variables that were measured in a patient case 1 month after the intervention: the proportion of Essential information students identified and the proportion of irrelevant information gathered (Relevant). Those who scored in the top 3 quartiles for Essential but in the lowest quartile for Relevant displayed a Thorough pattern. Those who scored in the top 3 quartiles for Relevant but in the lowest quartile for Essential displayed a Succinct pattern. Those who scored in the top 3 quartiles on both variables displayed a Focused pattern. Those whose scores were in the lowest quartile on both variables displayed a Nonspecific pattern.ResultsThe trial results indicated that students in the intervention group were more thorough than those in the control groups when gathering data. The qualitative data identified data gathering strategies and the mechanisms by which eCREST influenced data gathering. Students reported that eCREST promoted thoroughness by prompting them to continuously reflect and allowing them to practice managing uncertainty. However, some found eCREST to be less useful, and they randomly gathered information. Reanalysis of the trial data revealed that the intervention group was significantly more likely to display a Thorough data gathering pattern than controls (21/78, 27% vs 6/70, 9%) and less likely to display a Succinct pattern (13/78, 17% vs 20/70, 29%; χ23=9.9; P=.02). Other patterns were similar across groups.ConclusionsQualitative data suggested that students applied a range of data gathering strategies while using eCREST and that eCREST encouraged thoroughness by continuously prompting the students to reflect and manage their uncertainty. Trial data suggested that eCREST led students to demonstrate more Thorough data gathering patterns. Virtual patients that encourage thoroughness could help future physicians avoid missed diagnostic opportunities and enhance the delivery of clinical reasoning teaching.

Project description:BackgroundAlthough clinical teachers can often identify struggling learners readily and reliably, they can be reluctant to act upon their impressions, resulting in failure to fail. In the absence of a clear process for identifying and remediating struggling learners, clinical teachers can be put off by the prospect of navigating the politically and personally charged waters of remediation and potential failing of students.MethodsTo address this gap, we developed a problem-solving algorithm to support clinical teachers from the identification through the remediation of learners with clinical reasoning difficulties, which have significant implications for patient care. Based on this algorithm, a mobile application (Pdx) was developed and assessed in two emergency departments at a Canadian university, from 2015 to 2016, using interpretive description as our research design. Semi-structured interviews were conducted before and after a three-month trial with the application. Interviews were analysed both deductively, using pre-determined categories, and inductively, using emerging categories.ResultsTwelve clinical teachers were interviewed. Their experience with the application revealed their need to first validate their impressions of difficulties in learners and to find the right words to describe them before difficulties could be addressed. The application was unanimously considered helpful regarding both these aspects, while the mobile format appeared instrumental in allowing clinical teachers to quickly access targeted information during clinical supervision.ConclusionsThe value placed on verifying impressions and finding the right words to pinpoint difficulties should be further explored in endeavours that aim to address the failure to fail phenomenon. Moreover, just-in-time mobile solutions, which mirror habitual clinical practices, may be used profitably for knowledge transfer in medical education, as an alternative form of faculty development.

Dataset Information

Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

Publications

Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

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