This US multicenter, prospective cohort study aims to evaluate how MSCopilot can be seamlessly integrated into the current care pathway and identify potential optimizations to enhance its impact on both MS patients and clinicians, facilitating broader implementation. Specifically, the study will assess: * The overall integration of MSCopilot into routine clinical practice, * Patients' ability to use MSCopilot at home without supervision, * The need for patient support when using MSCopilot at home, * User behavior based on usage analytics data from the MSCopilot mobile app and dashboard, * Patient adherence to MSCopilot use in routine clinical practice, * The adequacy of the onboarding/training process for HCPs, * The effectiveness of HCPs onboarding/training in ensuring successful patient onboarding, * The variances in user behavior and adherence to MSCopilot use according to socio-demographic factors and EDSS scores
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
60
MSCopilot Flower includes active tests for walking, cognition, dexterity and vision, and e-questionnaires related to fatigue and Anxiety
Jenny Feng
New Orleans, Louisiana, United States
Robert Naismith
St Louis, Missouri, United States
Gabriel Pardo
Oklahoma City, Oklahoma, United States
Leorah Freeman
Austin, Texas, United States
To assess the ease of integrating the MSCopilot dashboard into clinical workflows for neurologists and the ease of use at home for patients with multiple sclerosis.
Descriptive analysis and acceptance criteria of a minimum score of \>2/4 on neurologists' questionnaires regarding the ease of integrating the MSCopilot dashboard into clinical workflows Descriptive analysis and acceptance criteria of a minimum score of \>2/4 on patients' questionnaires regarding the ease of use of MSCopilot at home
Time frame: For neurologists: Day 180 (+/- 30 days) and for patients: Day 1, Day 90 and Day 180 (+/- 30 days)
To assess the integration of MSCopilot dashboard and application into routine clinical practice as well as perceived value for both HCPs and patients.
Descriptive analysis of neurologists' questionnaires, to be completed after each investigator's last visit, regarding the Health Care Profesionnals (HCPs) dashboard Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item, of neurologists' questionnaires after the last visit on the HCPs dashboard Descriptive analysis of patients' questionnaires after the last visit regarding MSCopilot app and dashboard use by the HCPs. Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item in patients' questionnaires, to be completed after the follow-up visit, regarding MSCopilot application and dashboard use by HCPs
Time frame: At Day 180 ± 30days
To assess patients' ability to use MSCopilot at home without supervision.
Descriptive analysis of patient questionnaires Acceptance criteria of a minimum of \>2/4 for each item, of patient questionnaires
Time frame: Day 1 (+/- 30 days)
To assess patients' ability to use MSCopilot at home without supervision.
Descriptive analysis of patient questionnaires at mid-study Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item, of patient questionnaires at mid-study
Time frame: Day 90 (+/-30 days)
To assess the need for patient support when using MSCopilot at home
Descriptive analysis of nurses or medical assistants' questionnaires (if applicable) Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item, of nurses or medical assistants' questionnaires (if applicable)
Time frame: Day 180 (+/-30 days)
To assess patient adherence to MSCopilot use in routine clinical practice.
Descriptive analysis of the mobile application's adherence data, including: Number of performed tests, Number of performed sessions, Number of completed questionnaires.
Time frame: Day 1 to Day 180 (+/-30 days)
To assess user behavior based on usage analytics data from the MSCopilot mobile app and the dashboard.
Quantitative analysis of real-world utilization patterns of the MSCopilot mobile app through analytics data Quantitative analysis of real-world utilization patterns of the HCPs dashboard through analytics data
Time frame: Day 1 to Day 180 (+/-30 days)
To assess the effectiveness of HCPs onboarding/training in ensuring successful patient onboarding.
Descriptive analysis of HCPs (neurologists) questionnaires Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item, of HCPs (neurologists) questionnaires
Time frame: At the end of inclusion period (90 days)
To assess the effectiveness of HCPs onboarding/training in ensuring successful patient onboarding.
Descriptive analysis of patient questionnaires Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item, of patient questionnaires
Time frame: After patient inclusion visit (90 days)
To assess the adequacy of the onboarding/training process for HCPs, including neurologists, nurses, and medical assistants, focusing on clarity, satisfaction, and confidence in using MSCopilot
Descriptive analysis of HCPs questionnaires post-onboarding/training session Descriptive analysis and acceptance criteria of a minimum score of \>2/4 for each item in HCPs questionnaires post-onboarding/training
Time frame: After onboarding/training session (Day 0)
To assess the variances in user behavior and adherence to MSCopilot use according to socio-demographic factors and EDSS scores.
Descriptive analysis of how socio-demographic factors and EDSS scores affect patient behavior and adherence to MSCopilot mobile application.
Time frame: Day 1 to Day 180 (+/-30 days)
To assess the variances in user behavior and adherence to MSCopilot use according to socio-demographic factors and EDSS scores.
Descriptive analysis of how HCPs socio-demographic factors affect their behavior toward MSCopilot dashboard.
Time frame: Day 1 to Day 180 (+/-30 days)
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