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

Almomani, Emad, Alinier, Guillaume and Pattison, Natalie (2022) Approaches that promote clinical reasoning in clinical and simulation-based practice settings. Journal of Emergency Medicine, Trauma and Acute Care, 2022 (1). p. 66. ISSN 1999-7086

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Abstract

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

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