PND130 - MEASURING WHAT MATTERS TO PEOPLE WITH MULTIPLE SCLEROSIS AND PREFERENCES FOR NOVEL METHODS TO ASSESS CLINICAL OUTCOMES

Abstract

Objectives: The objective of this study was to quantify preferences for disease monitoring aspects as well as for the apps/devices to measure those aspects. Method(s): Adults with MS aged between 21 and 60 years, willing to participate, and using any kind of smart devices completed an online survey. A self-explicated conjoint approach was adapted to elicit preferences and opinions of each individual. Participants were asked to rate different levels for different attributes pertaining to: (i) aspect of MS that could be monitored, and (ii) device options to monitor those aspects of MS. Preferences for each attribute were ranked by importance and part-worth utilities (i.e. preference score) for each attribute level of performance were generated, allowing for easy side-by-side comparison. Result(s): A total of 140 people with MS participated in the survey (France: 30, Germany: 30, US: 50, UK: 30). The part-worth utility/preference score was highest for Physical activity (0.1523), followed by brain/mental health (0.1472), and physical fatigue (0.1457) indicating that these were the most important areas of MS to monitor, while physical fatigue (0.0931) was the most important symptom to monitor. Monitoring results of medical tests (0.1054), medication intake and appointment monitoring (0.0864) are as important as monitoring physical activity (0.0923), physical fatigue (0.1021) and brain/mental health (0.0973). The preferred way of monitoring symptoms is generally to track activities that improve the symptoms and to track the time of day when symptoms are at their worst, which could help them manage their symptoms. Smartphone app or a wrist measuring device is preferred as the main option to monitor their disease. Conclusion(s): This study provides new insights into outcomes and symptoms that matter most to people with MS and novel ways to measure clinical outcomes using digital technologies.Copyright © 2018