Objective: We aimed to provide an overview of telehealth used in the care for patients with amyotrophic lateral sclerosis (ALS), and identify the barriers to and facilitators of its implementation. Methods: We searched Pubmed and Embase to identify relevant articles. Full-text articles with original research reporting on the use of telehealth in ALS care, were included. Data were synthesized using the Consolidation Framework for Implementation Research. Two authors independently screened articles based on the inclusion criteria. Results: Sixteen articles were included that investigated three types of telehealth: Videoconferencing, home-based self-monitoring and remote NIV monitoring. Telehealth was mainly used by patients with respiratory impairment and focused on monitoring respiratory function. Facilitators for telehealth implementation were a positive attitude of patients (and caregivers) toward telehealth and the provision of training and ongoing support. Healthcare professionals were more likely to have a negative attitude toward telehealth, due to the lack of personal evaluation/contact and technical issues; this was a known barrier. Other important barriers to telehealth were lack of reimbursement and cost-effectiveness analyses. Barriers and facilitators identified in this review correspond to known determinants found in other healthcare settings. Conclusions: Our findings show that telehealth in ALS care is well-received by patients and their caregivers. Healthcare professionals, however, show mixed experiences and perceive barriers to telehealth use. Challenges related to finance and legislation may hinder telehealth implementation in ALS care. Future research should report the barriers and facilitators of implementation and determine the cost-effectiveness of telehealth.

Objective: To evaluate the use of telehealth as part of specialized care for patients with amyotrophic lateral sclerosis (ALS) and the user experiences of patients and healthcare professionals. Methods: Fifty patients with ALS were recruited from a single specialist center and used telehealth, consisting of an ALS-app for self-monitoring and messaging, alerts for symptom-worsening, and nurse practitioner follow-up. Patients self-monitored their well-being (daily report), body weight (weekly) and functional status (monthly). The use of the telehealth service was evaluated through adoption rate, dropout rate and adherence to self-monitoring. User-experiences were collected through online surveys among 23 patients and nine healthcare professionals, and interviews with 12 patients. Results: The adoption rate was 80%, dropout rate 4% and median follow-up was 11 months. Good adherence was seen in 49% of patients for well-being, 83% for body weight and 87% for functional assessment. For patients who discontinued using telehealth due to the end-of-life phase, median time between last measurement and death was 19 days. The majority of patients experienced using telehealth as easy, helpful, not burdensome, and reported satisfaction with flexible clinic visits and the continuity of care. Healthcare professionals reported that telehealth was of added value in ALS-care. Conclusions: ALS-care supplemented by home-monitoring and nurse practitioner follow-up was shown to be suitable and widely accepted by patients and healthcare professionals in our ALS clinic. Success factors were low self-monitoring burden, a user-friendly platform and the provision of personalized feedback. Further research is needed to replicate these findings in other ALS clinics.

Despite recent and potent technological advances, the real-world implementation of remote digital health technology in the care and monitoring of patients with motor neuron disease has not yet been realized. Digital health technology may increase the accessibility to and personalization of care, whereas remote biosensors could optimize the collection of vital clinical parameters, irrespective of patients’ ability to visit the clinic. To facilitate the wide-scale adoption of digital health care technology and to align current initiatives, we outline a road map that will identify clinically relevant digital parameters; mediate the development of benefit-to-burden criteria for innovative technology; and direct the validation, harmonization, and adoption of digital health care technology in real-world settings. We define two key end products of the road map: (1) a set of reliable digital parameters to capture data collected under free-living conditions that reflect patient-centric measures and facilitate clinical decision making and (2) an integrated, open-source system that provides personalized feedback to patients, health care providers, clinical researchers, and caregivers and is linked to a flexible and adaptable platform that integrates patient data in real time. Given the ever-changing care needs of patients and the relentless progression rate of motor neuron disease, the adoption of digital health care technology will significantly benefit the delivery of care and accelerate the development of effective treatments.

Background Poor monitoring of respiratory function may lead to late initiation of non-invasive ventilation (NIV) in patients with motor neuron diseases (MND). Monitoring could be improved by remotely assessing hypoventilation symptoms between clinic visits. We aimed to determine which patient-reported hypoventilation symptoms are best for screening reduced respiratory function in patients with MND, and compared them to the respiratory domain of the amyotrophic lateral sclerosis functional rating scale (ALSFRS-R). Methods This prospective multi-center study included 100 patients with MND, who were able to perform a supine vital capacity test. Reduced respiratory function was defined as a predicted supine vital capacity ≤ 80%. We developed a 14-item hypoventilation symptom questionnaire (HYSQ) based on guidelines, expert opinion and think-aloud interviews with patients. Symptoms of the HYSQ were related to dyspnea, sleep quality, sleepiness/fatigue and pneumonia. The diagnostic performances of these symptoms and the ALSFRS-R respiratory domain were determined from the receiver operating characteristic (ROC) curves, area under the curve (AUC), sensitivity, specificity, predictive values and accuracy. Results Dyspnea-related symptoms (dyspnea while eating/talking, while lying flat and during light activity) were combined into the MND Dyspnea Scale (MND-DS). ROC curves showed that the MND-DS had the best diagnostic performance, with the highest AUC = 0.72, sensitivity = 75% and accuracy = 71%. Sleep-quality symptoms, sleepiness/fatigue-related symptoms and the ALSFRS-R respiratory domain showed weak diagnostic performance. Conclusion The diagnostic performance of the MND-DS was better than the respiratory domain of the ALSFRS-R for screening reduced respiratory function in patients with MND, and is, therefore, the preferred method for (remotely) monitoring respiratory function.