Background: Integrated care can generate health and social care efficiencies through the defragmentation of care and adoption of patient-centered preventive models. eHealth can be a key enabling technology for integrated care. Objective: The aim of this study was to assess the effectiveness and cost-effectiveness of the implementation of a mobile health (mHealth)-enabled integrated care model for complex chronic patients. Methods: As part of the CONNECARE Horizon 2020 project, a prospective, pragmatic, two-arm, parallel implementation trial was held in a rural region of Catalonia, Spain. During 3 months, elderly patients with chronic obstructive pulmonary disease or heart failure and their carers experienced the combined benefits of the CONNECARE organizational integrated care model and the eHealth platform supporting it, consisting of a patient self-management app, a set of integrated sensors, and a web-based platform connecting professionals from different settings, or usual care. We assessed changes in health status with the 12-Item Short-Form Survey (SF-12), unplanned visits and admissions during a 6-month follow up, and the incremental cost-effectiveness ratio (ICER). Results: A total of 48 patients were included in the integrated care arm and 28 patients receiving usual care were included in the control arm (mean age 82 years, SD 7 years; mean Charlson index 7, SD 2). Integrated care patients showed a significant increase in the SF-12 physical domain with a mean change of +3.7 (SD 8.4) (P=.004) and total SF-12 score with a mean change of +5.8 (SD 12.8) (P=.003); however, the differences in differences between groups were not statistically significant. Integrated care patients had 57% less unplanned visits (P=.004) and 50% less hospital admissions related to their main chronic diseases (P=.32). The integrated care program generated savings in different cost scenarios and the ICER demonstrated the cost-effectiveness of the program. Conclusions: The implementation of a patient-centered mHealth-enabled integrated care model empowering the patient, and connecting primary, hospital, and social care professionals reduced unplanned contacts with the health system and health costs, and was cost-effective. These findings support the notion of system-wide cross-organizational care pathways supported by mHealth as a successful way to implement integrated care.

The novel BackHome system offers individuals with disabilities a range of useful services available via brain‐computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users’ home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user‐centred design approach. The final BackHome system is the result of a 3‐year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle‐free BCI equipment; one‐click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life.

Background: Osteoarthritis is a disabling condition that is often associated with other comorbidities. Total hip or knee arthroplasty is an effective surgical treatment for osteoarthritis when indicated, but comorbidities can impair their results by increasing complications and social and economic costs. Integrated care (IC) models supported by eHealth can increase efficiency through defragmentation of care and promote patient-centeredness. Objective: This study aims to assess the effectiveness and cost-effectiveness of implementing a mobile health (mHealth)–enabled IC model for complex chronic patients undergoing primary total hip or knee arthroplasty. Methods: As part of the Horizon 2020 Personalized Connected Care for Complex Chronic Patients (CONNECARE) project, a prospective, pragmatic, two-arm, parallel implementation trial was conducted in the rural region of Lleida, Catalonia, Spain. For 3 months, complex chronic patients undergoing total hip or knee arthroplasty and their caregivers received the combined benefits of the CONNECARE organizational IC model and the eHealth platform supporting it, consisting of a patient self-management app, a set of integrated sensors, and a web-based platform connecting professionals from different settings, or usual care (UC). We assessed changes in health status (12-item short-form survey [SF-12]), unplanned visits and admissions during a 6-month follow-up, and the incremental cost-effectiveness ratio. Results: A total of 29 patients were recruited for the mHealth-enabled IC arm, and 30 patients were recruited for the UC arm. Both groups were statistically comparable for baseline characteristics, such as age; sex; type of arthroplasty; and Charlson index, American Society of Anesthesiologists classification, Barthel index, Hospital Anxiety and Depression scale, Western Ontario and McMaster Universities Osteoarthritis Index, and Pfeiffer mental status questionnaire scores. Patients in both groups had significant increases in the SF-12 physical domain and total SF-12 score, but differences in differences between the groups were not statistically significant. IC patients had 50% fewer unplanned visits (P=.006). Only 1 hospital admission was recorded during the follow-up (UC arm). The IC program generated savings in different cost scenarios, and the incremental cost-effectiveness ratio demonstrated cost-effectiveness. Conclusions: Chronic patients undergoing hip or knee arthroplasty can benefit from the implementation of patient-centered mHealth-enabled IC models aimed at empowering patients and facilitating transitions from specialized hospital care to primary care. Such models can reduce unplanned contacts with the health system and reduce overall health costs, proving to be cost-effective. Overall, our findings support the notion of system-wide cross-organizational care pathways supported by mHealth as a successful way to implement IC for patients undergoing elective surgery.

Current brain-computer interface software is often tailored to the needs of scientists and technicians and therefore complex to allow for versatile use. To facilitate home use of brain-computer interfaces (BCIs) a multifunctional P300 BCI with a graphical user interface intended for non-expert set-up and control was designed and implemented. The system includes applications for spelling, web access, entertainment, artistic expression and environmental control. In addition to new software, it also includes new hardware for the recording of electroencephalogram (EEG) signals. The EEG system consists of a small and wireless amplifier attached to a cap that can be equipped with gel-based or dry contact electrodes. The system was systematically evaluated with a healthy sample, and targeted end users of BCI technology i.e. people with a varying degree of motor impairment tested the BCI in a series of individual case studies. Usability was assessed in terms of effectiveness, efficiency and satisfaction. Feedback of users was gathered with structured questionnaires. Two groups of healthy participants completed an experimental protocol with the gel-based and the dry contact electrodes (N=10 each). The results demonstrated that all healthy participants gained control over the system and achieved satisfactory to high accuracies with both gel-based and dry electrodes (average error rates of 6 and 13%). Average satisfaction ratings were high, but certain aspects of the system such as the wearing comfort of the dry electrodes and design of the cap, and speed (in both groups) were criticized by some participants. Six potential end users tested the system during supervised sessions. The achieved accuracies varied greatly from no control to high control with accuracies comparable to that of healthy volunteers. Satisfaction ratings of the two end-users that gained control of the system were lower as compared to healthy participants. The advantages and disadvantages of the BCI and its applications are discussed and suggestions are presented for improvements to pave the way for user friendly BCIs intended to be used as assistive technology by persons with severe paralysis.

Background: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but treatment compliance is often unsatisfactory. Objective: The aim of this study was to assess the effectiveness and cost-effectiveness of an intelligent monitoring system for improving CPAP compliance. Methods: This is a prospective, open label, parallel, randomized controlled trial including 60 newly diagnosed patients with OSA requiring CPAP (Apnea–Hypopnea Index [AHI] >15) from Lleida, Spain. Participants were randomized (1:1) to standard management or the MiSAOS intelligent monitoring system, involving (1) early compliance detection, thus providing measures of patient’s CPAP compliance from the very first days of usage; (2) machine learning–based prediction of midterm future CPAP compliance; and (3) rule-based recommendations for the patient (app) and care team. Clinical and anthropometric variables, daytime sleepiness, and quality of life were recorded at baseline and after 6 months, together with patient’s compliance, satisfaction, and health care costs. Results: Randomized patients had a mean age of 57 (SD 11) years, mean AHI of 50 (SD 27), and 13% (8/60) were women. Patients in the intervention arm had a mean (95% CI) of 1.14 (0.04-2.23) hours/day higher adjusted CPAP compliance than controls (P=.047). Patients’ satisfaction was excellent in both arms, and up to 88% (15/17) of intervention patients reported willingness to keep using the MiSAOS app in the future. No significant differences were found in costs (control: mean €90.2 (SD 53.14) (US $105.76 [SD 62.31]); intervention: mean €96.2 (SD 62.13) (US $112.70 [SD 72.85]); P=.70; €1=US $1.17 was considered throughout). Overall costs combined with results on compliance demonstrated cost-effectiveness in a bootstrap-based simulation analysis. Conclusions: A machine learning–based intelligent monitoring system increased daily compliance, reported excellent patient satisfaction similar to that reported in usual care, and did not incur in a substantial increase in costs, thus proving cost-effectiveness. This study supports the implementation of intelligent eHealth frameworks for the management of patients with CPAP-treated OSA and confirms the value of patients’ empowerment in the management of chronic diseases. Trial Registration: ClinicalTrials.gov NCT03116958; https://clinicaltrials.gov/ct2/show/NCT03116958

Background: Integrated care (IC) can promote health and social care efficiency through prioritization of preventive patient-centered models and defragmentation of care and collaboration across health tiers, and mobile health (mHealth) can be the cornerstone allowing for the adoption of IC. Objective: This study aims to assess the acceptability, usability, and satisfaction of an mHealth-enabled IC model for complex chronic patients in both patients and health professionals. Methods: As part of the CONNECARE Horizon 2020 project, a prospective, pragmatic, 2-arm, parallel, hybrid effectiveness-implementation trial was conducted from July 2018 to August 2019 in a rural region of Catalonia, Spain. Home-dwelling patients 55 years and older with chronic conditions and a history of hospitalizations for chronic obstructive pulmonary disease or heart failure (use case [UC] 1), or a scheduled major elective hip or knee arthroplasty (UC2) were recruited. During the 3 months, patients experienced an mHealth-enabled IC model, including a self-management app for patients, a set of integrated sensors, and a web-based platform connecting professionals from different settings or usual care. The Person-Centered Coordinated Care Experience Questionnaire (P3CEQ) and the Nijmegen Continuity Questionnaire (NCQ) assessed person-centeredness and continuity of care. Acceptability was assessed for IC arm patients and staff with the Net Promoter Score (NPS) and the System Usability Scale (SUS). Results: The analyses included 77 IC patients, 58 controls who completed the follow-up, and 30 health care professionals. The mean age was 78 (SD 9) years in both study arms. Perception of patient-centeredness was similarly high in both arms (usual care: mean P3CEQ score 16.1, SD 3.3; IC: mean P3CEQ score 16.3, SD 2.4). IC patients reported better continuity of care than controls (usual care: mean NCQ score 3.7, SD 0.9; IC: mean NCQ score 4.0, SD 1; P=.04). The scores for patient acceptability (UC1: NPS +67%; UC2: NPS +45%) and usability (UC1: mean SUS score 79, SD 14; UC2: mean SUS score 68, SD 24) were outstanding. Professionals’ acceptability was low (UC1: NPS −25%; UC2: NPS −35%), whereas usability was average (UC1: mean SUS score 63, SD 20; UC2: mean SUS score 62, SD 19). The actual use of technology was high; 77% (58/75) of patients reported physical activity for at least 60 days, and the ratio of times reported over times prescribed for other sensors ranged from 37% for oxygen saturation to 67% for weight. Conclusions: The mHealth-enabled IC model showed outstanding results from the patients’ perspective in 2 different UCs but lacked maturity and integration with legacy systems to be fully accepted by professionals. This paper provides useful lessons learned through the development and assessment process and may be of use to organizations willing to develop or implement mHealth-enabled IC for older adults.