Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice

A scoping review assessing the usability of digital health technologies targeting people with multiple sclerosis

Digital health technologies (DHTs) have become progressively more integrated into the healthcare of people with multiple sclerosis (MS). To ensure that DHTs meet end-users' needs, it is essential to assess their usability. The objective of this study was to determine how DHTs targeting people with MS incorporate usability characteristics into their design and/or evaluation. We conducted a scoping review of DHT studies in MS published from 2010 to the present using PubMed, Web of Science, OVID Medline, CINAHL, Embase, and medRxiv. Covidence was used to facilitate the review. We included articles that focused on people with MS and/or their caregivers, studied DHTs (including mhealth, telehealth, and wearables), and employed quantitative, qualitative, or mixed methods designs. Thirty-two studies that assessed usability were included, which represents a minority of studies (26%) that assessed DHTs in MS. The most common DHT was mobile applications (n = 23, 70%). Overall, studies were highly heterogeneous with respect to what usability principles were considered and how usability was assessed. These findings suggest that there is a major gap in the application of standardized usability assessments to DHTs in MS. Improvements in the standardization of usability assessments will have implications for the future of digital health care for people with MS.

Data on Ocrelizumab Treatment Collected by MS Patients in Germany Using Brisa App

BACKGROUND

With a rising number of multiple sclerosis (MS) cases and increasing pressure on health systems, digital companion apps like Brisa, designed specifically for people with MS, can play an important role in the patient journey. These apps enable the collection of real-time longitudinal data that are critical to our understanding of the pathophysiology and progression of MS.

METHODS

This retrospective, descriptive analysis consists of data from Brisa users who registered between 6 August 2021 and 8 September 2022. Of the unique users, 37.7% (n = 1593) fulfilled the inclusion criteria including information about medication and demographics and tracked one or more symptoms and/or patient-reported outcomes. Users were classified as moderate-efficacy treatment users, high-efficacy treatment users and ocrelizumab users, and the reporting frequency and scores of symptoms and patient-reported outcomes were analyzed.

RESULTS

The largest cohort of Brisa users (405) reported treatment with ocrelizumab and were mostly diagnosed 2-5 years before the survey. The most reported MS symptoms were similar between OUs (ocrelizumab users), HETUs (high-efficacy treatment users) and METUs (moderate-efficacy treatment users). OUs on average reported symptoms and answered questionnaires more frequently. Baseline scores between HETUs and OUs were similar, whereas baseline scores of METUs were slightly lower in comparison. In a further analysis of OUs, disability scores increased with age; users aged 26-45 years had higher pain scores than 18-25-year-olds. No significant differences were found in quality of life, bowel control and vision between age groups.

CONCLUSION

These findings show that the characteristics of the Brisa cohort are similar to the results of other studies and registries and can provide a representative overview of everyday disease management. Thereby, these results can bridge the gap between clinical research and real patient experience, but they also raise new questions, such as how often the hard-and-early therapy approach is already used and whether baseline characteristics and reasons for choosing a particular treatment contribute to the different outcomes over time. Answering these questions requires further research and analysis.

A collaborative approach to designing an online nutrition education program for people with multiple sclerosis

PURPOSE

People with multiple sclerosis (pwMS) want disease-specific dietary advice to reduce the confusion around diet. This study used co-design principles to develop an online nutrition education program for pwMS.

METHODS

Mixed-methods (multiphase sequential design). Phase 1: online survey (n = 114 pwMS) to explore preferred content and characteristics of a nutrition program and develop a draft program. Phase 2: feedback on the draft program from stakeholders (two meetings; n = 10 pwMS and multiple sclerosis (MS) health professionals) and pwMS (two workshops; n = 6) to produce a full program prototype. Phase 3: cognitive interviews (n = 8 pwMS plus 1 spouse) to explore acceptability and ease of comprehension of one module of the program, analysed using deductive content analysis.

RESULTS

Preferred topics were included in the program, which were further developed with consumer feedback. Cognitive interviews produced four themes: (1) positive and targeted messaging to motivate behaviour change; (2) "not enough evidence" is not good enough; (3) expert advice builds in credibility; and (4) engaging and appropriate online design elements are crucial.

CONCLUSIONS

Positive language appears to improve motivation to make healthy dietary changes and engagement with evidence-based nutrition resources. To ensure acceptability, health professionals can use co-design to engage consumers when developing resources for pwMS.IMPLICATIONS FOR REHABILITATIONCo-designed nutrition education programs can help people achieve high-quality diets in line with recommendations, but very few programs exist for people with multiple sclerosis (MS), and none were co-designedThe participatory research in this study was instrumental in ensuring that important information regarding program acceptability was identifiedCo-design can ensure that the language is appropriate for the target audience, and positive language appeared to improve motivation in people with MS to engage with the online nutrition education programWhere practical and feasible, health professionals should collaborate with MS consumers when developing resources, and use positive, empowering language.

Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments

The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.

Building digital patient pathways for the management and treatment of multiple sclerosis

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.

Opinions, satisfaction and expectations of individuals with multiple sclerosis about telerehabilitation services

OBJECTIVE

The opinions, satisfaction, and expectations of telemedicine can provide essential data for remote health services in individuals with Multiple Sclerosis (MS). The study aimed to demonstrate the views (barriers-benefits), satisfaction, and expectations of individuals with MS about telerehabilitation services.

METHODS

A prospective cross-sectional was conducted with 82 individuals with MS who received telerehabilitation services for at least one year. The participants have completed SymptoMScreen, Beck Depression Inventory (BDI), Telehealth Usability Questionnaire (TUQ), Telemedicine Satisfaction Questionnaire (TSQ), Telehealth Barriers Questionnaire (TBaQ and Telehealth Benefits Questionnaire (TBeQ).

RESULTS

As the age of individuals with MS increased, TUQ (r: -0.517, p < 0.001) and TBeQ (r: -0.383, p < 0.001) decreased, while TSQ (r: 0.405, p < 0.001) and TBaQ (r: 0.390, p < 0.001) increased. SymptoMScreen score (r: -0.288, p < 0.05) was weakly associated with TUQ. In addition, TUQ, TSQ, TBeQ, and TBaQ were strongly correlated (p < 0.001).

CONCLUSION

In order to improve usability and satisfaction in telerehabilitation services, the age, symptom severity, and education levels of individuals with MS should be considered. Telehealth methods with high usability should be preferred to increase patient satisfaction.

Management of multiple sclerosis fatigue in the digital age: from assessment to treatment

Fatigue is one of the most disabling symptoms of Multiple Sclerosis (MS), affecting more than 80% of patients over the disease course. Nevertheless, it has a multi-faceted and complex nature, making its diagnosis, evaluation, and treatment extremely challenging in clinical practice. In the last years, digital supporting tools have emerged to support the care of people with MS. These include not only smartphone or table-based apps, but also wearable devices or novel techniques such as virtual reality. Furthermore, an additional effective and cost-efficient tool for the therapeutic management of people with fatigue is becoming increasingly available. Virtual reality and e-Health are viable and modern tools to both assess and treat fatigue, with a variety of applications and adaptability to patient needs and disability levels. Most importantly, they can be employed in the patient's home setting and can not only bridge clinic visits but also be complementary to the monitoring and treatment means for those MS patients who live far away from healthcare structures. In this narrative review, we discuss the current knowledge and future perspectives in the digital management of fatigue in MS. These may also serve as sources for research of novel digital biomarkers in the identification of disease activity and progression.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs. A systematic review of mobile app interventions for three major CNSDs, i.e., Parkinson's disease (PD), multiple sclerosis (MS), and stroke, which impose significant burden on people and health care systems around the globe, is presented. A literature search in the bibliographic databases of PubMed and Scopus was performed. Identified studies were assessed in terms of quality, and synthesized according to target disease, mobile app characteristics, study design and outcomes. Overall, 21 studies were included in the review. A total of 3 studies targeted PD (14%), 4 studies targeted MS (19%), and 14 studies targeted stroke (67%). Most studies presented a weak-to-moderate methodological quality. Study samples were small, with 15 studies (71%) including less than 50 participants, and only 4 studies (19%) reporting a study duration of 6 months or more. The majority of the mobile apps focused on exercise and physical rehabilitation. In total, 16 studies (76%) reported positive outcomes related to physical activity and motor function, cognition, quality of life, and education, whereas 5 studies (24%) clearly reported no difference compared to usual care. Mobile app interventions are promising to improve outcomes concerning patient's physical activity, motor ability, cognition, quality of life and education for patients with PD, MS, and Stroke. However, rigorous studies are required to demonstrate robust evidence of their clinical effectiveness.

Correlation and differences of patient-reported outcomes vs. Likert-Rating of MS symptoms in a real-world cohort using a digital patient app

Background

Multiple Sclerosis (MS) is a chronic and progressive neurological autoimmune disease currently affecting 250,000 individuals in Germany. Patients suffering from the disease can be severely impaired in their day-to-day activities. BRISA is a digital app specifically designed to help MS patients monitor their disease by regularly tracking symptoms. Lengthy and time-consuming questionnaires for patient-reported outcomes (PRO) are the standard method to assess the patients' current condition. Here, we examine whether simplified versions of these questionnaires can provide comparable information regarding individual symptom presentations in BRISA users.

Methods

828 users were included in the analysis. Patients who provided onboarding information and answered at least one questionnaire and the corresponding simplified smiley symptoms assessment were included. Correlation of questionnaire and symptom scores was calculated using Pearson's correlation.

Results

Our analysis cohort predominantly consisted of female, 26-55-year-olds. Relapsing-remitting MS (RRMS) was the most common MS type recorded. Most patients were diagnosed 2-5 years ago. Questionnaires regarding fatigue and vision impairment were among the most answered, those regarding bowel movement and sexual satisfaction received fewest responses. Overall, the scores from questionnaires and symptoms correlated positively. Scoring correlation could also be shown across the subgroups divided by gender, age groups, type of MS, and time since diagnosis of the disease.

Conclusion

Scores recorded from traditional PRO questionnaires can be reflected more easily as a trend in a simplified scale using smileys. Nevertheless, traditional questionnaires are needed to also maintain a more objective assessment. In conclusion, the patient will benefit most from an adaptive combination of regular traditional PRO questionnaire assessments and simplified symptom recording.

Development and usability testing of your MS questionnaire: A patient-based digital tool to monitor symptoms of multiple sclerosis

Objectives

We describe the development of Your Multiple Sclerosis Questionnaire and present the real-world usability testing results of Your Multiple Sclerosis Questionnaire.

Methods

The Your Multiple Sclerosis Questionnaire tool was developed in four stages to collect feedback from people living with MS (plwMS), patient organizations, and clinicians on content, format, and applicability. To assess its usability, 13 clinicians across 7 countries completed an online survey after using the tool with plwMS in a total of 261 consultations from September, 2020 to July, 2021.

Results

The initial Your Multiple Sclerosis Questionnaire version was based on findings from previous research developing MSProDiscuss™, a clinician-completed tool. Subsequently, insights from plwMS obtained during cognitive debriefing, patient councils and advisory boards led to changes including the addition of mood and sexual problems and the definition of relapse. All 13 clinicians completed the individual survey, whereas 10 clinicians completed the final survey. Clinicians "strongly agreed" or "agreed" that Your Multiple Sclerosis Questionnaire was easy to use and understand (98.5%; 257/261 patient consultations). The clinicians were willing to use the tool again with the same patient (98.1%; 256/261 patient consultations). All clinicians who completed the final survey (100%; 10/10) reported the tool to have a positive influence on their clinical practice, helped patients engage with their MS, facilitated discussion with patients, and complemented neurological assessment.

Conclusion

Your Multiple Sclerosis Questionnaire benefits both plwMS and clinicians by facilitating a structured discussion and engaging the plwMS to self-monitor and self-manage. Your Multiple Sclerosis Questionnaire is compatible with telemedicine practice and integration of the tool into electronic health records would enable tracking of the disease evolution and individual monitoring of MS symptoms over time.

Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis

Background

Consumer-grade fitness trackers offer exciting opportunities to study persons with chronic diseases in greater detail and in their daily-life environment. However, attempts to bring fitness tracker measurement campaigns from tightly controlled clinical environments to home settings are often challenged by deteriorating study compliance or by organizational and resource limitations.

Objectives

By revisiting the study design and patient-reported experiences of a partly remote study with fitness trackers (BarKA-MS study), we aimed to qualitatively explore the relationship between overall study compliance and scalability. On that account, we aimed to derive lessons learned on strengths, weaknesses, and technical challenges for the conduct of future studies.

Methods

The two-phased BarKA-MS study employed Fitbit Inspire HR and electronic surveys to monitor physical activity in 45 people with multiple sclerosis in a rehabilitation setting and in their natural surroundings at home for up to 8 weeks. We examined and quantified the recruitment and compliance in terms of questionnaire completion and device wear time. Furthermore, we qualitatively evaluated experiences with devices according to participants' survey-collected reports. Finally, we reviewed the BarKA-MS study conduct characteristics for its scalability according to the Intervention Scalability Assessment Tool checklist.

Results

Weekly electronic surveys completion reached 96%. On average, the Fitbit data revealed 99% and 97% valid wear days at the rehabilitation clinic and in the home setting, respectively. Positive experiences with the device were predominant: only 17% of the feedbacks had a negative connotation, mostly pertaining to perceived measurement inaccuracies. Twenty-five major topics and study characteristics relating to compliance were identified. They broadly fell into the three categories: "effectiveness of support measures", "recruitment and compliance barriers", and "technical challenges". The scalability assessment revealed that the highly individualized support measures, which contributed greatly to the high study compliance, may face substantial scalability challenges due to the strong human involvement and limited potential for standardization.

Conclusion

The personal interactions and highly individualized participant support positively influenced study compliance and retention. But the major human involvement in these support actions will pose scalability challenges due to resource limitations. Study conductors should anticipate this potential compliance-scalability trade-off already in the design phase.

A Comprehensive Literature Search of Digital Health Technology Use in Neurological Conditions: Review of Digital Tools to Promote Self-management and Support

BACKGROUND

The use of digital health technology to promote and deliver postdiagnostic care in neurological conditions is becoming increasingly common. However, the range of digital tools available across different neurological conditions and how they facilitate self-management are unclear.

OBJECTIVE

This review aims to identify digital tools that promote self-management in neurological conditions and to investigate their underlying functionality and salient clinical outcomes.

METHODS

We conducted a search of 6 databases (ie, CINAHL, EMBASE, MEDLINE, PsycINFO, Web of Science, and the Cochrane Review) using free text and equivalent database-controlled vocabulary terms.

RESULTS

We identified 27 published articles reporting 17 self-management digital tools. Multiple sclerosis (MS) had the highest number of digital tools followed by epilepsy, stroke, and headache and migraine with a similar number, and then pain. The majority were aimed at patients with a minority for carers. There were 5 broad categories of functionality promoting self-management: (1) knowledge and understanding; (2) behavior modification; (3) self-management support; (4) facilitating communication; and (5) recording condition characteristics. Salient clinical outcomes included improvements in self-management, self-efficacy, coping, depression, and fatigue.

CONCLUSIONS

There now exist numerous digital tools to support user self-management, yet relatively few are described in the literature. More research is needed to investigate their use, effectiveness, and sustainability, as well as how this interacts with increasing disability, and their integration within formal neurological care environments.

Demographic Patterns of MS Patients Using BRISA: An MS-Specific App in Germany

Background: Multiple sclerosis (MS) is a chronic, progressive neurological autoimmune disease impacting quality of life. BRISA is an app designed to help MS patients in Germany track their disease course by symptom-monitoring. This study aimed to understand demographic and health-related characteristics of BRISA users. Methods: Demographic data provided by 2095 users were analyzed to describe characteristics such as sex, age, type of MS, and medication. The distribution of tracked symptoms based on age and time since diagnosis were studied. Furthermore, the covariance of specific symptom pairs was analyzed. Results: BRISA users are predominantly female and between 26 and 55 years old. Relapsing–remitting MS was the most prevalent form of MS. First-line category 1 drugs were most frequently used, followed by high-efficacy category 3 drugs (e.g., monoclonal antibodies). The relative frequencies of use of category 1 and category 2 drugs (e.g., spingosine-1-phosphate-receptor modulators) significantly altered with time since diagnosis. Fatigue, concentration disorders, tingling, forgetfulness, and pain were the top five symptoms affecting users. Conclusion: The results highlight the diversity among MS patients and the need for extensive cohort characterization in the real-world scenario. In-depth analysis could help in identifying novel insights that could aid in disease management.

The AIMS home-video method: parental experiences and appraisal for use in neonatal follow-up clinics

Background

In The Netherlands, prematurely born infants and their parents are offered regular developmental check-ups in a hospital setting. In line with providing healthcare at distance, the use of video footage showing the infant’s behavior and movements, taken by parents at home and assessed by professionals online, might be a fruitful future practice. The focus of this study was to gain insight into parental experiences with the Alberta Infant Motor Scale home-video method and their appraisal of its applicability for use in an outpatient neonatal follow-up clinic.

Method

A qualitative descriptive study among parents of healthy extremely or very premature infants (GA 26.2–31.5 weeks) participating in a longitudinal study of motor development between 3–18 months corrected age. Ten semi-structured interviews were conducted and transcribed verbatim. Data was analyzed independently. Inductive content analysis was performed following the process of the AIMS home-video method.

Results

Parents appraised the AIMS home-video method as manageable and fun to do. Instructions, instruction film, and checklists were clear. Transferring the video footage from their phone to their computer and uploading it to the web portal was sometimes time-consuming. Parents gained a better awareness of their infant’s motor development and found the provided feedback a confirmation of what they already thought about their infant’s development and was reassuring that their child was doing well. First-time parents seemed more uncertain and had a greater need for information about (motor) development, but on the other hand, also had confidence in their child.

All parents thought that home-videos can be an addition to follow-up visits, but cannot replace (all) visits. It may be an opportunity to reduce the frequency of hospital visits, while still having their infant monitored.

Conclusion

Parents appraised the AIMS home-video method positively and are of the opinion that home-videos can be of added value in monitoring infants at risk in neonatal follow-up additional to hospital visits. In future research a user-friendly application and/or platform to exchange video footage safely between parents and professionals should be developed with all possible stakeholders involved and implementation should be explored.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03398-9.

Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data

One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensive gait analysis, such as the Dresden protocol for multidimensional walking assessment, covers several facets of walking impairment including a 2-min walk test, in which the distance taken by the patient in two minutes is measured by an odometer. Using this approach, it is questionable how precise the measuring methods are at recording the distance traveled. In this project, we investigate whether the current measurement can be replaced by a digital measurement method based on accelerometers (six Opal sensors from the Mobility Lab system) that are attached to the patient’s body. We developed two algorithms using these data and compared the validity of these approaches using the results from 2-min walk tests from 562 pwMS that were collected with a gold-standard odometer. In 48.4% of pwMS, we detected an average relative measurement error of less than 5%, while results from 25.8% of the pwMS showed a relative measurement error of up to 10%. The algorithm had difficulties correctly calculating the walking distances in another 25.8% of pwMS; these results showed a measurement error of more than 20%. A main reason for this moderate performance was the variety of pathologically altered gait patterns in pwMS that may complicate the step detection. Overall, both algorithms achieved favorable levels of agreement (r = 0.884 and r = 0.980) with the odometer. Finally, we present suggestions for improvement of the measurement system to be implemented in the future.

The sympathies of the body: functional organization and neuronal differentiation in the peripheral sympathetic nervous system

During the last 30 years, our understanding of the development and diversification of postganglionic sympathetic neurons has dramatically increased. In parallel, the list of target structures has been critically extended from the cardiovascular system and selected glandular structures to metabolically relevant tissues such as white and brown adipose tissue, lymphoid tissues, bone, and bone marrow. A critical question now emerges for the integration of the diverse sympathetic neuron classes into neural circuits specific for these different target tissues to achieve the homeostatic regulation of the physiological ends affected.

Multiple Sclerosis Progression Discussion Tool Usability and Usefulness in Clinical Practice: Cross-sectional, Web-Based Survey

Background

A digital tool, Multiple Sclerosis Progression Discussion Tool (MSProDiscuss), was developed to facilitate discussions between health care professionals (HCPs) and patients in evaluating early, subtle signs of multiple sclerosis (MS) disease progression.

Objective

The aim of this study is to report the findings on the usability and usefulness of MSProDiscuss in a real-world clinical setting.

Methods

In this cross-sectional, web-based survey, HCPs across 34 countries completed an initial individual questionnaire (comprising 7 questions on comprehensibility, usability, and usefulness after using MSProDiscuss during each patient consultation) and a final questionnaire (comprising 13 questions on comprehensibility, usability, usefulness, and integration and adoption into clinical practice to capture the HCPs’ overall experience of using the tool). The responses were provided on a 5-point Likert scale. All analyses were descriptive, and no statistical comparisons were made.

Results

In total, 301 HCPs tested the tool in 6974 people with MS, of whom 77% (5370/6974) had relapsing-remitting MS, including those suspected to be transitioning to secondary progressive MS. The time taken to complete MSProDiscuss was reported to be in the range of 1 to 4 minutes in 97.3% (6786/6974; initial) to 98.2% (269/274; final) of the cases. In 93.54% (6524/6974; initial) to 97.1% (266/274; final) of the cases, the HCPs agreed (4 or 5 on the Likert scale) that patients were able to comprehend the questions in the tool. The HCPs were willing to use the tool again in the same patient, 90.47% (6310/6974; initial) of the cases. The HCPs reported MSProDiscuss to be useful in discussing MS symptoms and their impact on daily activities (6121/6974, 87.76% initial and 252/274, 92% final) and cognitive function (5482/6974, 78.61% initial and 271/274, 79.2% final), as well as in discussing progression in general (6102/6974, 87.49% initial and 246/274, 89.8% final). While completing the final questionnaire, 94.9% (260/274) of the HCPs agreed that the questions were similar to those asked in regular consultation, and the tool helped to better understand the impact of MS symptoms on daily activities (249/274, 90.9%) and cognitive function (220/274, 80.3%). Overall, 92% (252/274) of the HCPs reported that they would recommend MSProDiscuss to a colleague, and 85.8% (235/274) were willing to integrate it into their clinical practice.

Conclusions

MSProDiscuss is a usable and useful tool to facilitate a physician-patient discussion on MS disease progression in daily clinical practice. Most of the HCPs agreed that the tool is easy to use and were willing to integrate MSProDiscuss into their daily clinical practice.

The Potential Impact of Digital Biomarkers in Multiple Sclerosis in The Netherlands: An Early Health Technology Assessment of MS Sherpa

(1) Background: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce. MS sherpa is an eHealth intervention with digital biomarkers, aimed at monitoring symptom progression and disease activity. To show the added value of digital biomarker-based eHealth interventions to the MS care path, an early Health Technology Assessment (eHTA) was performed, with MS sherpa as an example, to assess the potential impact on treatment switches. (2) Methods: The eHTA was performed according to the Dutch guidelines for health economic evaluations. A decision analytic MS model was used to estimate the costs and benefits of MS standard care with and without use of MS sherpa, expressed in incremental cost-effectiveness ratios (ICERs) from both societal and health care perspectives. The efficacy of MS sherpa on early detection of active disease and the initiation of a treatment switch were modeled for a range of assumed efficacy (5%, 10%, 15%, 20%). (3) Results: From a societal perspective, for the efficacy of 15% or 20%, MS sherpa became dominant, which means cost-saving compared to the standard of care. MS sherpa is cost-effective in the 5% and 10% scenarios (ICERs EUR 14,535 and EUR 4069, respectively). From the health care perspective, all scenarios were cost-effective. Sensitivity analysis showed that increasing the efficacy of MS sherpa in detecting active disease early leading to treatment switches be the most impactful factor in the MS model. (4) Conclusions: The results indicate the potential of eHealth interventions to be cost-effective or even cost-saving in the MS care path. As such, digital biomarker-based eHealth interventions, like MS sherpa, are promising cost-effective solutions in optimizing MS disease management for people with MS, by detecting active disease early and helping neurologists in decisions on treatment switch.

Developing a Digital Solution for Remote Assessment in Multiple Sclerosis: From Concept to Software as a Medical Device

There is increasing interest in the development and deployment of digital solutions to improve patient care and facilitate monitoring in medical practice, e.g., by remote observation of disease symptoms in the patients’ home environment. Digital health solutions today range from non-regulated wellness applications and research-grade exploratory instruments to regulated software as a medical device (SaMD). This paper discusses the considerations and complexities in developing innovative, effective, and validated SaMD for multiple sclerosis (MS). The development of SaMD requires a formalised approach (design control), inclusive of technical verification and analytical validation to ensure reliability. SaMD must be clinically evaluated, characterised for benefit and risk, and must conform to regulatory requirements associated with device classification. Cybersecurity and data privacy are also critical. Careful consideration of patient and provider needs throughout the design and testing process help developers overcome challenges of adoption in medical practice. Here, we explore the development pathway for SaMD in MS, leveraging experiences from the development of Floodlight™ MS, a continually evolving bundled solution of SaMD for remote functional assessment of MS. The development process will be charted while reflecting on common challenges in the digital space, with a view to providing insights for future developers.

A Mobile App for Measuring Real Time Fatigue in Patients with Multiple Sclerosis: Introducing the Fimo Health App

Although fatigue is one of the most disabling symptoms of MS, its pathogenesis is not well understood yet. This study aims to introduce a new holistic approach to measure fatigue and its influencing factors via a mobile app. Fatigue is measured with different patient-reported outcome measures (Visual Analog Scale, Fatigue Severity Scale) and tests (Symbol Digit Modalities Test). The influencing vital and environmental factors are captured with a smartwatch and phone sensors. Patients can track these factors within the app. To individually counteract their fatigue, a fatigue course, based on the current treatment guidelines, was implemented. The course implies knowledge about fatigue and MS, exercises, energy-conservation management, and cognitive behavioral therapy. Based on the Transtheoretical Model of Behavior Change, the design of the Fimo health app follows the ten strategies of the process of change, which is a proven approach to designing health intervention programs. By monitoring fatigue and individual influencing factors, patients can better understand and manage their fatigue. They can share their data and insights about fatigue and its influencing factors with their doctors. Thus, they can receive individualized therapies and drug plans.

Profiles of eHealth Adoption in Persons with Multiple Sclerosis and Their Caregivers

(1) Background: Persons with multiple sclerosis (pwMS) are often characterized as ideal adopters of new digital healthcare trends, but it is worth thinking about whether and which pwMS will be targeted and served by a particular eHealth service like a patient portal. With our study, we wanted to explore needs and barriers for subgroups of pwMS and their caregivers when interacting with eHealth services in care and daily living. (2) Methods: This study comprises results from two surveys: one collecting data from pwMS and their relatives (as informal caregivers) and another one providing information on the opinions and attitudes of healthcare professionals (HCPs). Data were analyzed descriptively and via generalized linear models. (3) Results: 185 pwMS, 25 informal caregivers, and 24 HCPs in the field of MS participated. Nine out of ten pwMS used information technology on a daily base. Individual impairments like in vision and cognition resulted in individual needs like the desire to actively monitor their disease course or communicate with their physician in person. HCPs reported that a complete medication overview, additional medication information, overview of future visits and a reminder of medication intake would be very helpful eHealth features for pwMS, while they themselves preferred features organizing and enriching future visits. (4) Conclusions: A closer look at the various profiles of eHealth adoption in pwMS and their caregivers indicated that there is a broad and robust enthusiasm across several subgroups that does not exclude anyone in general, but constitutes specific areas of interest. For pwMS, the focus was on eHealth services that connect previously collected information and make them easily accessible and understandable.

Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

In multiple sclerosis (MS), gait impairment is one of the most prominent symptoms. For a sensitive assessment of pathological gait patterns, a comprehensive analysis and processing of several gait analysis systems is necessary. The objective of this work was to determine the best diagnostic gait system (DIERS pedogait, GAITRite system, and Mobility Lab) using six machine learning algorithms for the differentiation between people with multiple sclerosis (pwMS) and healthy controls, between pwMS with and without fatigue and between pwMS with mild and moderate impairment. The data of the three gait systems were assessed on 54 pwMS and 38 healthy controls. Gaussian Naive Bayes, Decision Tree, k-Nearest Neighbor, and Support Vector Machines (SVM) with linear, radial basis function (rbf) and polynomial kernel were applied for the detection of subtle walking changes. The best performance for a healthy-sick classification was achieved on the DIERS data with a SVM rbf kernel (κ = 0.49 ± 0.11). For differentiating between pwMS with mild and moderate disability, the GAITRite data with the SVM linear kernel (κ = 0.61 ± 0.06) showed the best performance. This study demonstrates that machine learning methods are suitable for identifying pathologic gait patterns in early MS.

Improving Digital Patient Care: Lessons Learned from Patient-Reported and Expert-Reported Experience Measures for the Clinical Practice of Multidimensional Walking Assessment

Background: Walking assessment (WA) enables meaningful patient mobility assessment. In this context, patient satisfaction with WA can influence assessment compliance and indirectly affect outcomes. One opportunity to assess patient satisfaction is patient-reported and expert-reported experience measures (PREM). Research on PREMs and WA in daily clinical multiple sclerosis (MS) practice does not exist yet. Methods: We surveyed people with MS about their experience and assessed healthcare professionals’ experience via an interview after patients completed WA. Results: Gait parameters were related to perceived difficulty and strain during performance. Less impaired patients perceived the WA to be less difficult and exhausting but were less likely to use WA results for themselves. Men and patients with higher impairment would perform WA more frequently. A good workflow, a fully performed WA with standardized testing, fully functional measurement systems, support and safeguarding by staff in case of falls, direct feedback after the testing, and patients’ motivation are identified by the experts as necessary factors for a successful WA. Conclusions: As patients’ experience has an impact on patients’ outcomes, long-term monitoring of PREMs should become an integral part of the healthcare service to identify and avoid problems early.

Digital Twins for Multiple Sclerosis

An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient's characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters - including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient's life circumstances and plans, and medical procedures - a digital twin paired to the patient's characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients' well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.