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

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          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.

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          Most cited references33

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          Technology-enhanced simulation for health professions education: a systematic review and meta-analysis.

          Although technology-enhanced simulation has widespread appeal, its effectiveness remains uncertain. A comprehensive synthesis of evidence may inform the use of simulation in health professions education. To summarize the outcomes of technology-enhanced simulation training for health professions learners in comparison with no intervention. Systematic search of MEDLINE, EMBASE, CINAHL, ERIC, PsychINFO, Scopus, key journals, and previous review bibliographies through May 2011. Original research in any language evaluating simulation compared with no intervention for training practicing and student physicians, nurses, dentists, and other health care professionals. Reviewers working in duplicate evaluated quality and abstracted information on learners, instructional design (curricular integration, distributing training over multiple days, feedback, mastery learning, and repetitive practice), and outcomes. We coded skills (performance in a test setting) separately for time, process, and product measures, and similarly classified patient care behaviors. From a pool of 10,903 articles, we identified 609 eligible studies enrolling 35,226 trainees. Of these, 137 were randomized studies, 67 were nonrandomized studies with 2 or more groups, and 405 used a single-group pretest-posttest design. We pooled effect sizes using random effects. Heterogeneity was large (I(2)>50%) in all main analyses. In comparison with no intervention, pooled effect sizes were 1.20 (95% CI, 1.04-1.35) for knowledge outcomes (n = 118 studies), 1.14 (95% CI, 1.03-1.25) for time skills (n = 210), 1.09 (95% CI, 1.03-1.16) for process skills (n = 426), 1.18 (95% CI, 0.98-1.37) for product skills (n = 54), 0.79 (95% CI, 0.47-1.10) for time behaviors (n = 20), 0.81 (95% CI, 0.66-0.96) for other behaviors (n = 50), and 0.50 (95% CI, 0.34-0.66) for direct effects on patients (n = 32). Subgroup analyses revealed no consistent statistically significant interactions between simulation training and instructional design features or study quality. In comparison with no intervention, technology-enhanced simulation training in health professions education is consistently associated with large effects for outcomes of knowledge, skills, and behaviors and moderate effects for patient-related outcomes.
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            Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality.

            Better health care quality is a universal goal, yet measuring quality has proven to be difficult and problematic. A central problem has been isolating physician practices from other effects of the health care system. To validate clinical vignettes as a method for measuring the competence of physicians and the quality of their actual practice. Prospective trial conducted in 1997 comparing 3 methods for measuring the quality of care for 4 common outpatient conditions: (1) structured reports by standardized patients (SPs), trained actors who presented unannounced to physicians' clinics (the gold standard); (2) abstraction of medical records for those same visits; and (3) physicians' responses to clinical vignettes that exactly corresponded to the SPs' presentations. Setting Outpatient primary care clinics at 2 Veterans Affairs medical centers. Ninety-eight (97%) of 101 general internal medicine staff physicians, faculty, and second- and third-year residents consented to be randomized for the study. From this group, 10 physicians at each site were randomly selected for inclusion. A total of 160 quality scores (8 cases x 20 physicians) were generated for each method using identical explicit criteria based on national guidelines and local expert panels. Scores were defined as the percentage of process criteria correctly met and were compared among the 3 methods. The quality of care, as measured by all 3 methods, ranged from 76.2% (SPs) to 71.0% (vignettes) to 65.6% (chart abstraction). Measuring quality using vignettes consistently produced scores closer to the gold standard of SP scores than using chart abstraction. This pattern was robust when the scores were disaggregated by the 4 conditions (P<.001 to <.05), by case complexity (P<.001), by site (P<.001), and by level of physician training (P values from <.001 to <.05). The pattern persisted, although less dominantly, when we assessed the component domains of the clinical encounter--history, physical examination, diagnosis, and treatment. Vignettes were responsive to expected directions of variation in quality between sites and levels of training. The vignette responses did not appear to be sensitive to physicians' having seen an SP presenting with the same case. Our data indicate that quality of health care can be measured in an outpatient setting by using clinical vignettes. Vignettes appear to be a valid and comprehensive method that directly focuses on the process of care provided in actual clinical practice. Vignettes show promise as an inexpensive case-mix adjusted method for measuring the quality of care provided by a group of physicians.
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              The science on front-of-package food labels.

              The U.S. Food and Drug Administration and Institute of Medicine are currently investigating front-of-package (FOP) food labelling systems to provide science-based guidance to the food industry. The present paper reviews the literature on FOP labelling and supermarket shelf-labelling systems published or under review by February 2011 to inform current investigations and identify areas of future research. A structured search was undertaken of research studies on consumer use, understanding of, preference for, perception of and behaviours relating to FOP/shelf labelling published between January 2004 and February 2011. Twenty-eight studies from a structured search met inclusion criteria. Reviewed studies examined consumer preferences, understanding and use of different labelling systems as well as label impact on purchasing patterns and industry product reformulation. The findings indicate that the Multiple Traffic Light system has most consistently helped consumers identify healthier products; however, additional research on different labelling systems' abilities to influence consumer behaviour is needed.
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                Author and article information

                Contributors
                URI : http://frontiersin.org/people/u/32823
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                21 August 2017
                2017
                : 8
                : 430
                Affiliations
                [1] 1Division of Neurology, Department of Medicine, St. Michael’s Hospital, University of Toronto , Toronto, ON, Canada
                [2] 2Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich , Zurich, Switzerland
                [3] 3Outcomes Research and Decision Neuroscience Unit, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, University of Toronto , Toronto, ON, Canada
                [4] 4Neuroscience Area, Medical Department, Roche Farma , Madrid, Spain
                [5] 5Department of Neurology, Hospital General Universitario de Alicante , Alicante, Spain
                [6] 6Healthcare Analytics Research, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, University of Toronto , Toronto, ON, Canada
                [7] 7Neurology-Neuroimmunology Department, Neurorehabilitation Unit, Multiple Sclerosis Centre of Catalonia (Cemcat) , Barcelona, Spain
                Author notes

                Edited by: Ayrton R. Massaro, Hospital Sirio-Libanes, Brazil

                Reviewed by: Asif Doja, Children’s Hospital of Eastern Ontario, Canada; Robert Jerome Frysztak, Loyola University Chicago, United States

                *Correspondence: Gustavo Saposnik, saposnikg@ 123456smh.ca

                These authors have contributed equally to this work.

                Specialty section: This article was submitted to Neurology Education, a section of the journal Frontiers in Neurology

                Article
                10.3389/fneur.2017.00430
                5567059
                4451fb6e-2793-4661-9007-f379081b85ed
                Copyright © 2017 Saposnik, Maurino, Sempere, Terzaghi, Ruff, Mamdani, Tobler and Montalban.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 July 2017
                : 08 August 2017
                Page count
                Figures: 4, Tables: 2, Equations: 0, References: 38, Pages: 12, Words: 5499
                Categories
                Neuroscience
                Clinical Trial

                Neurology
                multiple sclerosis,disease-modifying therapy,neuroeconomics,decision making,risk aversion

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