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The main objectives of this study are:
i) To design an educational tool to train physicians in overcome cognitive factors associated with therapeutic inertia.
ii) To determine the feasibility and efficacy of an educational tool to overcome therapeutic inertia among neurologists caring for MS patients
iii) identify the best strategy to disseminate an educational program to train physicians taking into account regional and practice variations.
iv) To explore whether multiple sclerosis (MS) patients' risk category influence the incidence of therapeutic inertia in neurologists that may require a segmentation strategy in medical education.
v) To assess how participants handle uncertainty when making treatment decisions by measuring pupil variation from baseline (Canadian study).
vi) To evaluate the effect of the TLS on TI by assessing differences pupil variability between the intervention and control groups (Canadian study).
A multicenter, randomized, study including an educational intervention (applying the traffic light system) to overcome therapeutic inertia in MS care.
Full description
The goal of the present study is the application of an educational intervention (based on best clinical practices) to reduce therapeutic inertia targeting neurologists caring for MS patients. The investigators are also interested in evaluating whether an education intervention decreases TI by reducing arousal response (pupil dilation), a proxy measure of how physicians respond to uncertainty during treatment decisions.
A secondary goal is to improve physicians' tolerance to uncertainty, which has been directly related to therapeutic inertia in our previous studies. This proposal follows the results of our study that identified factors associated with management errors and therapeutic inertia by applying novel concepts and validated experiments from Behavioral economics/ Neuroeconomics.
Rationale for the current study:
Some strategies has been proposed to reduce the effects cognitive factors and biases on clinical decisions. A comprehensive narrative review comprising 41 studies on cognitive interventions to reduce misdiagnosis found three main effective strategies: increasing knowledge and expertise, improving clinical reasoning, and getting help from colleagues, experts and tools.18 First, reflective reasoning counteracts the impact of cognitive biases by improving diagnostic accuracy in second- (OR 2.03; 95%CI, 1.49-2.57) and first-year residents [OR (odds ratio) 2.31; 95% CI, 1.89-2.73].19 Second, the implementation of tools (e.g. cognitive checklist, calibration) may overcome overconfidence, the anchoring and framing effects (figure 5).20-22 Third, heuristics approaches (shortcuts to ignore less relevant information to overcome the complexity of some clinical situations) can improve decision making. As shown by Marewski and Gigerenzer, the identification of three rules (search for predictors to determine their individual importance, stop searching when relevant information was already obtained, and a criteria that specify how a decision is made) may facilitate prompt decisions and may help physicians to avoid errors in some clinical situations.
The inclusion of training in cognitive biases in graduate and postgraduate programs might foster medical education and thereby improve health care delivery.
In summary, a new arsenal of disease-modifying agents became available in the last few decades (and more will be approved in the next three years), but over half of neurologists caring for MS patients do not escalate therapy when indicated by clinical best practices. As such, physicians' decision-making process and access to new effective DMTs became the current bottleneck in MS care. Physicians' factors that are directly associated with therapeutic inertia in MS care. The investigators propose to creating and testing an intervention or tool to train physicians to overcome biases, implement more standardized therapeutic approaches, which will lead to reducing the incidence of TI and better MS outcomes.
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90 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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