Medical Education for Better Multiple Sclerosis Outcomes

Not Applicable

Completed

• Conditions: Multiple Sclerosis
• Interventions: Behavioral: Educational intervention applying the traffic light system (TLS)

• Registration Number: NCT03134794
• Lead Sponsor: Unity Health Toronto

Brief Summary

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.

Detailed 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:

* Physicians have limited education in risk management and formal training in decision making.

* Only a small proportion of MS patients are being treated according to the best clinical practice guidelines. Physicians (cognitive biases affecting decision making) and health system (e.g. access to an infusion center) factors are the most responsible causes of practice gaps in MS care (Blum).

* In a previous study (JURaSSiC), physicians have shown poor estimation of the prognosis of stroke patients. As this not unique to a single neurological condition and directly affects the recognition of patients who would benefit from escalating therapies.

* Therapeutic inertia (TI) is a common phenomenon in medicine defined as lack of treatment escalation when recommended according to the best practice guidelines. This phenomenon lead to poorer patients outcomes, greater disability, and diminished quality of life.

* In a recent study conducted by our group including 136 neurologists and MS experts, the investigators found TI was present in nearly 7 out of 10 (68.8%) of participants. Similar results were observed for criteria of disease progression. Aversion to ambiguity (situation when risk are unknown) and low tolerance to uncertainty were the stronger predictors of TI among neurologists caring for MS patients.

* Although risk prognostic tools (e.g. EMA, modified Rio, clinical+radiological progression) are available to assist physicians in stratifying patients, it is not known whether or not neurologists use a systematic approach to improve the therapeutic decisions in MS care.

* There is a limited understanding on how to ameliorate the physicians' factors (e.g. low tolerance to uncertainty, aversion to ambiguity, etc) associated with TI, which leads to worse clinical outcomes and poor quality of life.

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.

Study Timeline

• Study First Submitted: 2017-03-05
• Study Start: 2017-03-22
• Study First Submitted QC: 2017-04-26
• Study First Posted: 2017-05-01
• Primary Completion: 2018-10-30
• Study Completion: 2018-10-30
• Status Verified: 2020-10
• Last Update Submitted: 2020-10-16
• Last Update Posted: 2020-10-19

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 90

Inclusion Criteria

1. Practicing neurologists and MS specialists caring for patients with MS
2. Clinical setting: academic or community institutions
3. Certified physicians in their specialty
4. Online consent to participate in the study

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Exclusion Criteria

Not provided

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Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Educational Intervention	Educational intervention applying the traffic light system (TLS)	Education intervention using the TLS. The active group will received an educational intervention applying proven concepts in medical education (cognitive reflection/checklist, traffic light system (TLS). Previous research showed that TL food labels prompted individuals to consider their health and to make healthier choices. A color-coded system influences the valuation process in favor of healthier choices by interfering with automatic decisions and triggering the re-evaluation process (Ena, Krajbich et al Judgement and DM 2016). The TLS is being implemented to facilitate the identification of patients at risk of developing a clinical and radiological progression that could result in escalation of therapy.

Primary Outcome Measures

Name	Time	Method
The proportion of participants who exhibit therapeutic inertia	At the completion of the study, an estimated total of 60 minutes	defined as lack of treatment escalation when the goals of care are unmet based on best practice guidelines.; We will compare the total number of responses between groups post-intervention (total number of responses that met the TI criteria over total number of questions answered per participant.
Feasibility of the educational intervention	At the completion of the study, an estimated total of 60 minutes	defined as the proportion of participants in the educational intervention who selected the 'red" traffic light for high risk cases. It is expected a 70% or higher proportion of correct responses
Pupil dilation from baseline (Primary outcome of the study conducted in Canada)	Up to 60 min	Pupil time-series were z-scored within each participant, to allow comparison of pupil dilation between and within simulated case-scenarios, critical time-periods, and participants. Pupil data will be analyzed as a continuous (mean maximum peak minus mean baseline and mean pupil size minus mean baseline) and dichotomized to reflect phasic and tonic arousal responses (mean maximum-peak minus mean-baseline greater than or equal to 0.1 z-scored difference as a high arousal vs. below 0.1 z-scored difference -low arousal response).

Secondary Outcome Measures

Name	Time	Method
Scale (based on the experiment on ambiguity aversion)	At the completion of the study, approximately 60 minutes	association between ambiguity and risk aversion (independent variables) with therapeutic decisions. Ambiguity aversion is defined as a preference for known risks over unknown risks. This can be elicited through the experiments in the health and financial domains.
Efficacy of the educational intervention	At the completion of the study, approximately 60 minutes	Difference in the proportion of participants with decision fatigue between groups (measured as the difference between proportion of cases with therapeutic inertia post-intervention minus proportion of cases with therapeutic inertia pre-intervention).
Scale (physician reaction to uncertainty)	At the completion of the study, approximately 60 minutes	Using the 'physicians reaction to uncertainty" instrument as a continuous variable and median split.

Trial Locations

Locations (4)

St Michael's Hospital; 🇨🇦 Toronto, Ontario, Canada

Espacio GV30; 🇪🇸 Madrid, Spain

INEBA; 🇦🇷 Buenos Aires, Ciudad De Buenos Aires, Argentina

Clinica Las Condes; 🇨🇱 Santiago, Chile