Home monitoring with connected mobile devices for asthma attack prediction with machine learning.

Monitoring asthma is essential for self-management. However, traditional monitoring methods require high levels of active engagement, and some patients may find this tedious. Passive monitoring with mobile-health devices, especially when combined with machine-learning, provides an avenue to reduce management burden. Data for developing machine-learning algorithms are scarce, and gathering new data is expensive. A few datasets, such as the Asthma Mobile Health Study, are publicly available, but they only consist of self-reported diaries and lack any objective and passively collected data. To fill this gap, we carried out a 2-phase, 7-month AAMOS-00 observational study to monitor asthma using three smart-monitoring devices (smart-peak-flow-meter/smart-inhaler/smartwatch), and daily symptom questionnaires. Combined with localised weather, pollen, and air-quality reports, we collected a rich longitudinal dataset to explore the feasibility of passive monitoring and asthma attack prediction. This valuable anonymised dataset for phase-2 of the study (device monitoring) has been made publicly available. Between June-2021 and June-2022, in the midst of UK's COVID-19 lockdowns, 22 participants across the UK provided 2,054 unique patient-days of data.

The role of the California tier system in controlling population mobility during the COVID-19 pandemic.

BACKGROUND: Policies to restrict population mobility are a commonly used strategy to limit the transmission of contagious diseases. Among measures implemented during the COVID-19 pandemic were dynamic stay-at-home orders informed by real-time, regional-level data. California was the first state in the U.S. to implement this novel approach; however, the effectiveness of California's four-tier system on population mobility has not been quantified. METHODS: Utilizing data from mobile devices and county-level demographic data, we evaluated the impact of policy changes on population mobility and explored whether demographic characteristics explained variability in responsiveness to policy changes. For each California county, we calculated the proportion of people staying home and the average number of daily trips taken per 100 persons, across different trip distances and compared this to pre-COVID-19 levels. RESULTS: We found that overall mobility decreased when counties moved to a more restrictive tier and increased when moving to a less restrictive tier, as the policy intended. When placed in a more restrictive tier, the greatest decrease in mobility was observed for shorter and medium-range trips, while there was an unexpected increase in the longer trips. The mobility response varied by geographic region, as well as county-level median income, gross domestic product, economic, social, and educational contexts, the prevalence of farms, and recent election results. CONCLUSIONS: This analysis provides evidence of the effectiveness of the tier-based system in decreasing overall population mobility to ultimately reduce COVID-19 transmission. Results demonstrate that socio-political demographic indicators drive important variability in such patterns across counties.

SLIDE: Saliva-Based SARS-CoV-2 Self-Testing with RT-LAMP in a Mobile Device.

Regular, accurate, rapid, and inexpensive self-testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is urgently needed to quell pandemic propagation. The existing at-home nucleic acid testing (NAT) test has high sensitivity and specificity, but it requires users to mail the sample to the central lab, which often takes 3-5 days to obtain the results. On the other hand, rapid antigen tests for the SARS-CoV-2 antigen provide a fast sample to answer the test (15 min). However, the sensitivity of antigen tests is 30 to 40% lower than nucleic acid testing, which could miss a significant portion of infected patients. Here, we developed a fully integrated SARS-CoV-2 reverse transcription loop-mediated isothermal amplification (RT-LAMP) device using a self-collected saliva sample. This platform can automatically handle the complexity and can perform the functions, including (1) virus particles' thermal lysis preparation, (2) sample dispensing, (3) target sequence RT-LAMP amplification, (4) real-time detection, and (5) result report and communication. With a turnaround time of less than 45 min, our device achieved the limit of detection (LoD) of 5 copies/µL of the saliva sample, which is comparable with the LoD (6 copies/µL) using FDA-approved quantitative real-time polymerase chain reaction (qRT-PCR) assays with the same heat-lysis saliva sample preparation method. With clinical samples, our platform showed a good agreement with the results from the gold-standard RT-PCR method. These results show that our platform can perform self-administrated SARS-CoV-2 nucleic acid testing by laypersons with noninvasive saliva samples. We believe that our self-testing platform will have an ongoing benefit for COVID-19 control and fighting future pandemics.

Mobile Device Usage before and during the COVID-19 Pandemic among Rural and Urban Adults.

Technology has played a critical role during the COVID-19 pandemic. Despite affording a safe way for people to connect with others, the potential for problematic device usage (e.g., overuse, addiction) should be considered. The goal of this study was to examine mobile device use during the COVID-19 pandemic among rural and urban people in Canada. Based on an online survey conducted in the summer of 2021 in British Columbia (n = 465), participants self-reported spending more hours per day (M = 8.35 h) using technology during the pandemic compared to prior (M = 6.02 h), with higher increases among urban participants (p < 0.001). Mobile device usage scores were highest for reasons of social connectedness and productivity, with no rural/urban differences; however, urban participants reported higher use of mobile devices for their mental well-being (p = 0.001), but also reported higher, continuous use (p < 0.001), addiction (p < 0.001), and detrimental impacts on their physical health (p < 0.001) compared to rural participants. Because urban participants were more vulnerable to mobile device overuse and addiction during the pandemic, researchers and policy makers should consider the ongoing role and positive/negative impacts of mobile device use, paying particular attention to urban populations.

Impact of a pharmaceutical care service for patients with rheumatoid arthritis using a customised mobile device (the PROUD trial): study protocol for a randomised controlled trial.

INTRODUCTION: Rheumatoid arthritis (RA) generally requires lifelong treatment; however, its medication complexity might affect non-adherence. Pharmacist-led telehealth services were as effective as face-to-face services and reduced potential side effects in outpatients with chronic diseases. This study aims to analyse the effect of a telepharmacy service with a customised mobile device in comparison with the usual pharmacist service on the humanistic and clinical outcomes in patients with RA. METHODS AND ANALYSIS: The study is designed as a prospective, randomised, open-label, and controlled trial to compare the humanistic and clinical outcomes of the pharmaceutical care service with monthly telecommunications and a customised mobile application (telepharmacy care group) against the usual service by community pharmacists (usual care group) in 256 patients with RA and prescribed at least one of the disease-modifying antirheumatic drugs. Participants will be recruited from a tertiary hospital in Republic of Korea with written informed consent. The primary outcome will be the changes in health-related quality of life as measured by the Korean version of the EuroQoL's five-dimensional questionnaire at 6 months compared with baseline. The secondary outcomes will be the changes in the following: scores of the Korean version of the Compliance Questionnaire-Rheumatology and medication knowledge at 3 and 6 months compared with baseline; scores of the Korean version of the Pharmacy Service Questionnaire at 6 months compared with baseline; clinical parameters such as erythrocyte sedimentation rate, C reactive protein level, and pain score at 3 and 6 months compared with baseline; frequency of acute care utilisation over 6 months. Analysis will be carried out with intent-to-treat and per-protocol principles. ETHICS AND DISSEMINATION: The study protocol was reviewed and approved by the Institutional Review Board (IRB) of Daegu Catholic University Medical Center (IRB no. CR-21-082-L, 14 July 2021). The study findings will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: KCT0006508.

Multi-ROI Spectral Approach for the Continuous Remote Cardio-Respiratory Monitoring from Mobile Device Built-In Cameras.

Heart rate (HR) and respiratory rate (fR) can be estimated by processing videos framing the upper body and face regions without any physical contact with the subject. This paper proposed a technique for continuously monitoring HR and fR via a multi-ROI approach based on the spectral analysis of RGB video frames recorded with a mobile device (i.e., a smartphone's camera). The respiratory signal was estimated by the motion of the chest, whereas the cardiac signal was retrieved from the pulsatile activity at the level of right and left cheeks and forehead. Videos were recorded from 18 healthy volunteers in four sessions with different user-camera distances (i.e., 0.5 m and 1.0 m) and illumination conditions (i.e., natural and artificial light). For HR estimation, three approaches were investigated based on single or multi-ROI approaches. A commercially available multiparametric device was used to record reference respiratory signals and electrocardiogram (ECG). The results demonstrated that the multi-ROI approach outperforms the single-ROI approach providing temporal trends of both the vital parameters comparable to those provided by the reference, with a mean absolute error (MAE) consistently below 1 breaths·min-1 for fR in all the scenarios, and a MAE between 0.7 bpm and 6 bpm for HR estimation, whose values increase at higher distances.

Health care visits during the COVID-19 pandemic: A spatial and temporal analysis of mobile device data.

Transportation disruptions caused by COVID-19 have exacerbated difficulties in health care delivery and access, which may lead to changes in health care use. This study uses mobile device data from SafeGraph to explore the temporal patterns of visits to health care points of interest (POIs) during 2020 and examines how these patterns are associated with socio-demographic and spatial characteristics at the Census Block Group level in North Carolina. Specifically, using the K-medoid time-series clustering method, we identify three distinct types of temporal patterns of visits to health care facilities. Furthermore, by estimating multinomial logit models, we find that Census Block Groups with higher percentages of elderly persons, minorities, low-income individuals, and people without vehicle access are areas most at-risk for decreased health care access during the pandemic and exhibit lower health care access prior to the pandemic. The results suggest that the ability to conduct in-person medical visits during the pandemic has been unequally distributed, which highlights the importance of tailoring policy strategies for specific socio-demographic groups to ensure equitable health care access and delivery.

Risk factors of musculoskeletal symptoms among mobile device users during work from home.

Objectives. Coronavirus (COVID-19) is affecting people throughout the world. People are forced to conduct various activities at home using mobile devices (MDs) as a result of the outbreak. In this case, prolonged use of MDs is the major cause for work-related health problems. Methods. We used systematic cluster random sampling to sample a diverse group of Indians from India's various states. Subjects filled out a questionnaire with questions about their demographics, MD usage and musculoskeletal symptoms (MSSs) faced. The relationship between MSSs and various factors was investigated using χ2 and binomial logistic regression analysis. Results. An online survey yielded 720 responses. More than half of employees registered MSSs in their upper body regions. Age, gender and MD usage were correlated with MSSs in various body regions. According to the binomial logistic regression findings, gender was significantly linked to MSSs in each body region. Conclusions. Results show that MDs can be used effectively in intermediate leisure activities if they are used in accordance with their basic needs.

Usefulness of Mobile Electrocardiographic Devices to Reduce Urgent Healthcare Visits.

Mobile electrocardiogram (mECG) devices are being used increasingly, supplying recordings to providers and providing automatic rhythm interpretation. Given the intermittent nature of certain cardiac arrhythmias, mECGs allow instant access to a recording device. In the current COVID-19 pandemic, efforts to limit in-person patient interactions and avoid overwhelming emergency and inpatient services would add value. Our goal was to evaluate whether a mECG device would reduce healthcare utilization overall, particularly those of urgent nature. We identified a cohort of KardiaMobile (AliveCor, USA) mECG users and compared their healthcare utilization 1 year prior to obtaining the device and 1 year after. One hundred and twenty-eight patients were studied (mean age 64, 47% female). Mean duration of follow-up pre-intervention was 9.8 months. One hundred and twenty-three of 128 individuals completed post-intervention follow-up. Patients were less likely to have cardiac monitors ordered (30 vs 6; p <0.01), outpatient office visits (525 vs 382; p <0.01), cardiac-specific ED visits (51 vs 30; p <0.01), arrhythmia related ED visits (45 vs 20; p <0.01), and unplanned arrhythmia admissions (34 vs 11; p <0.01) in the year after obtaining a KardiaMobile device compared to the year prior to obtaining the device. Mobile technology is available for heart rhythm monitoring and can give feedback to the user. This study showed a reduction of in-person, healthcare utilization with mECG device use. In conclusion, this strategy would be expected to decrease the risk of exposure to patients and providers and would avoid overwhelming emergency and inpatient services.

Exploring Factors of Mobile Device Adoption in Nursing Education.

The world has seen an explosion in mobile device technology over the past decade, in addition to the impact that COVID-19 has placed on nursing education programs. More specifically, mobile devices have afforded users with endless possibilities. This upsurge in mobile technology has altered the way people use and interact with their device. One such example is how these devices are being utilized for the purposes of learning due to social distancing guidelines. Thus, it becomes important to explore and understand those factors that will influence the use of mobile devices for learning. The purpose of this study was to explore variables that might influence the adoption of mobile devices among nursing faculty. The Unified Theory of Acceptance and Use of Technology served as the theoretical basis for this study and guiding framework. An exploratory quantitative survey research design was utilized to explore specific variables and their impact on mobile device adoption among participants. It was found that 85%, six of the seven research variables were statistically significant predictors of mobile device adoption. Mobile devices have the potential to leverage a wealth of resources for both users and faculty. Therefore, recommendations for developing increased use of mobile device technology for teaching and learning will be suggested.

Pain distraction during awake low anterior resection and Cuddle Delivery initiative for inpatient: frugal procedural options to support surgery in the COVID-19 era.

OBJECTIVE: Since minimally invasive surgery and general anesthesia are both aerosol-generating procedures, their use became controversial during the outbreak of coronavirus disease 2019 (COVID-19). Moreover, social distancing resulted in serious psychological consequences for inpatients. This case report investigates pain distraction during awake laparotomy, as well as new possibilities for emotional postoperative support to inpatients. PATIENTS AND METHODS: A 72-year-old man affected by middle rectal adenocarcinoma underwent lower anterior resection plus total mesorectal excision under combined spinal-epidural anesthesia. A 3D mobile theatre (3DMT) was intraoperatively used for pain distraction. A postoperative "Cuddle delivery" service was instituted: video-messages from relatives and close friends were delivered daily to the patient through the 3DMT. Emotional correlations were investigated through a clinical interview by the psychologist of our Hospital. RESULTS: Intraoperative, as well as postoperative pain, resulted well-controlled: visual analogue scale (VAS) ≤3. Conversion to general anesthesia and postoperative intensive support/monitoring were unnecessary. The "Cuddle delivery" initiative positively fed our patient's mood and attitude, strengthening his bond to life. CONCLUSIONS: During pandemic, awake laparotomy under loco-regional anesthesia may be a crucial option in delivering acute care surgery to selected patients when intensive care beds are unavailable. Our procedure introduces potential ways to optimize this approach.

A Case Study of Two Emerging Nurse Leaders Specializing in Virtual Health during the COVID-19 Global Pandemic.

In the field of digital health research, nurse leaders have an opportunity to be integral to the design, implementation and evaluation of virtual care interventions. This case study details the experiences of two emerging nurse leaders during the COVID-19 pandemic in providing research and clinical leadership for a national virtual health trial. These nurse leaders trained and led a national team of 70 nurses across eight participating centres delivering the virtual care and remote monitoring intervention, using the normalization process theory. This case study presents a theoretically informed approach to training and leadership and discusses the experiences and lessons learned.

Countrywide population movement monitoring using mobile devices generated (big) data during the COVID-19 crisis.

Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a "mobility-index" and a "stay-at-home/resting-index" based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.

HOPES: An Integrative Digital Phenotyping Platform for Data Collection, Monitoring, and Machine Learning.

The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual's health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a comprehensive digital phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for security, privacy, ease of use, and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present, and analyze data. This includes a set of dashboards customized to the needs of research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.

Post Discharge after Surgery Virtual Care with Remote Automated Monitoring Technology (PVC-RAM): protocol for a randomized controlled trial.

BACKGROUND: After nonelective (i.e., semiurgent, urgent and emergent) surgeries, patients discharged from hospitals are at risk of readmissions, emergency department visits or death. During the coronavirus disease 2019 (COVID-19) pandemic, we are undertaking the Post Discharge after Surgery Virtual Care with Remote Automated Monitoring Technology (PVC-RAM) trial to determine if virtual care with remote automated monitoring (RAM) compared with standard care will increase the number of days adult patients remain alive at home after being discharged following nonelective surgery. METHODS: We are conducting a randomized controlled trial in which 900 adults who are being discharged after nonelective surgery from 8 Canadian hospitals are randomly assigned to receive virtual care with RAM or standard care. Outcome adjudicators are masked to group allocations. Patients in the experimental group learn how to use the study's tablet computer and RAM technology, which will measure their vital signs. For 30 days, patients take daily biophysical measurements and complete a recovery survey. Patients interact with nurses via the cellular modem-enabled tablet, who escalate care to preassigned and available physicians if RAM measurements exceed predetermined thresholds, patients report symptoms, a medication error is identified or the nurses have concerns they cannot resolve. The primary outcome is number of days alive at home during the 30 days after randomization. INTERPRETATION: This trial will inform management of patients after discharge following surgery in the COVID-19 pandemic and offer insights for management of patients who undergo nonelective surgery in a nonpandemic setting. Knowledge dissemination will be supported through an online multimedia resource centre, policy briefs, presentations, peer-reviewed journal publications and media engagement. TRIAL REGISTRATION: ClinicalTrials.gov, no. NCT04344665.

Rapid Deployment of Inpatient Telemedicine In Response to COVID-19 Across Three Health Systems.

OBJECTIVE: To reduce pathogen exposure, conserve personal protective equipment, and facilitate health care personnel work participation in the setting of the COVID-19 pandemic, three affiliated institutions rapidly and independently deployed inpatient telemedicine programs during March 2020. We describe key features and early learnings of these programs in the hospital setting. METHODS: Relevant clinical and operational leadership from an academic medical center, pediatric teaching hospital, and safety net county health system met to share learnings shortly after deploying inpatient telemedicine. A summative analysis of their learnings was re-circulated for approval. RESULTS: All three institutions faced pressure to urgently standup new telemedicine systems while still maintaining secure information exchange. Differences across patient demographics and technological capabilities led to variation in solution design, though key technical considerations were similar. Rapid deployment in each system relied on readily available consumer-grade technology, given the existing familiarity to patients and clinicians and minimal infrastructure investment. Preliminary data from the academic medical center over one month suggested positive adoption with 631 inpatient video calls lasting an average (standard deviation) of 16.5 minutes (19.6) based on inclusion criteria. DISCUSSION: The threat of an imminent surge of COVID-19 patients drove three institutions to rapidly develop inpatient telemedicine solutions. Concurrently, federal and state regulators temporarily relaxed restrictions that would have previously limited these efforts. Strategic direction from executive leadership, leveraging off-the-shelf hardware, vendor engagement, and clinical workflow integration facilitated rapid deployment. CONCLUSION: The rapid deployment of inpatient telemedicine is feasible across diverse settings as a response to the COVID-19 pandemic.