Clinical reasoning in general practice is increasingly challenging because of the rise in the number of patients with multimorbidity. This creates uncertainty because of unpredictable interactions between the symptoms from multiple medical problems and the patient's personality, psychosocial context and life history. Case analysis may then be more appropriately managed by systems thinking than by hypothetic‐deductive reasoning, the predominant paradigm in the current teaching of clinical reasoning. Application of “systems thinking” tools such as causal loop diagrams allows the patient's problems to be viewed holistically and facilitates understanding of the complex interactions. We will show how complexity levels can be graded in clinical reasoning and demonstrate where and how systems thinking can have added value by means of a case history.
Healthcare professionals' clinical practice is steeped in both compassion and technical aspects of care, yet data on how to improve the care of patients with multimorbidity is limited(1). Two of the cornerstones of modern clinical practice -evidence-based medicine and the teaching of consultation skills -lack utility in making decisions with and for patients who have multimorbidity, especially in time-pressurised, metrics-dominated clinical environments. We have developed a new model which supports the translation of population-based, evidence-based medicine and complex consultation models to simpler, natural conversations about care appropriate for and agreed with individual patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.