Overcoming Therapeutic Inertia in Multiple Sclerosis Care: A Pilot Randomized Trial Applying the Traffic Light System in Medical Education

Abstract

Background: Physicians often do not initiate or intensify treatments when clearly warranted, a phenomenon known as therapeutic inertia (TI). Limited information is available on educational interventions to ameliorate knowledge-to-action gaps in TI.

Objectives: To evaluate the feasibility and efficacy of an educational intervention compared to usual care among practicing neurologists caring for patients with multiple sclerosis (MS).

Methods: We conducted a pilot double-blind, parallel-group, randomized clinical trial. Inclusion criteria included neurologists who are actively involved in managing MS patients. Participants were exposed to 20 simulated case-scenarios (10 cases at baseline, and 10 cases post-randomization to usual care vs. educational intervention) of relapsing-remitting MS with moderate or high risk of disease progression. The educational intervention employed a traffic light system (TLS) to facilitate decisions, allowing participants to easily recognize high-risk scenarios requiring treatment escalation. We also measured differences between blocks to invoke decision fatigue. The control group responded as they would do in their usual clinical practice not exposed to the educational intervention. The primary feasibility outcome was the proportion of participants who completed the study and the proportion of participants who correctly identified a high-risk case-scenario with the "red traffic light." Secondary outcomes included decision fatigue (defined as an increment of TI in the second block of case-scenarios compared to the first block) and the efficacy of the educational intervention measured as a reduction in TI for MS treatment.

Results: Of 30 neurologists invited to be part of the study, the participation rate was 83.3% (n = 25). Of the 25 participants, 14 were randomly assigned to the control group and 11 to the intervention group. TI was present in 72.0% of participants in at least one case scenario. For the primary feasibility outcome, the completion rate of the study was 100% (25/25 participants). Overall, 77.4% of participants correctly identified the "red traffic light" for clinical-scenarios with high risk of disease progression. Similarly, 86.4% of participants correctly identified the "yellow traffic light" for cases that would require a reassessment within 6-12 months. For the secondary fatigue outcome, within-group analysis showed a significant increased prevalence of TI in the second block of case-scenarios (decision fatigue) among participants randomized to the control group (TI pre-intervention 57.1% vs. TI post-intervention 71.4%; p = 0.015), but not in the active group (TI pre-intervention 54.6% vs. TI post-intervention 63.6%; p = 0.14). For the efficacy outcome, we found a non-significant reduction in TI for the targeted intervention compared to controls (22.6 vs. 33.9% post-intervention; OR 0.57; 95% CI 0.26-1.22).

Conclusion: An educational intervention applying the TLS is feasible and shows some promising results in the identification of high-risk scenarios to reduce decision fatigue and TI. Larger studies are needed to determine the efficacy of the proposed educational intervention.

Clinical trial registration: www.ClinicalTrials.gov, identifier NCT03134794.

Keywords: decision making; disease-modifying therapy; multiple sclerosis; neuroeconomics; risk aversion.

Figures

Figure 1

CONSORT flow diagram.

Figure 2

Description of the educational intervention according to the GREET guidelines.

Figure 2

Description of the educational intervention according to the GREET guidelines.

Figure 2

Description of the educational intervention according to the GREET guidelines.

Figure 3

Educational intervention: the traffic light system may facilitate therapeutic decisions in multiple sclerosis care. Participants viewed the two informative panels (A,B) and a third panel providing an example (C).

Figure 3

Educational intervention: the traffic light system may facilitate therapeutic decisions in multiple sclerosis care. Participants viewed the two informative panels (A,B) and a third panel providing an example (C).

Figure 4

Prevalence of therapeutic inertia (TI) for the targeted intervention accounting for each individual response in the active and control groups. Lower numbers represent lower TI (more optimal therapeutic decisions). *p = 0.74, **p = 0.12. Note the lower trend in the prevalence of TI in the intervention group compared to the control group (22.6 vs. 33.9%; OR 0.57; 95% CI 0.26–1.22).