OBJECTIVE: Current clinical evidence on the effects of home blood pressure telemonitoring (HBPT) on improving blood pressure control comes entirely from developed countries. Thus, we performed this randomized controlled trial to evaluate whether HBPT plus support (patient education and clinician remote hypertension management) improves blood pressure control more than usual care (UC) in the Chinese population. METHODS: This single-center, randomized controlled study was conducted in Beijing, China. Patients aged 30-75 years were eligible for enrolment if they had blood pressure [systolic (SBP) ≥ 140 mmHg and/or diastolic (DBP) ≥ 90 mmHg; or SBP ≥ 130 mmHg and/or DBP ≥ 80 mmHg with diabetes]. We recruited 190 patients randomized to either the HBPT or the UC groups for 12 weeks. The primary endpoints were blood pressure reduction and the proportion of patients achieving the target blood pressure. RESULTS: Totally, 172 patients completed the study, the HBPT plus support group ( n = 84), and the UC group ( n = 88). Patients in the plus support group showed a greater reduction in mean ambulatory blood pressure than those in the UC group. The plus support group had a significantly higher proportion of patients who achieved the target blood pressure and maintained a dipper blood pressure pattern at the 12th week of follow-up. Additionally, the patients in the plus support group showed lower blood pressure variability and higher drug adherence than those in the UC group. CONCLUSION HBPT plus additional support results in greater blood pressure reduction, better blood pressure control, a higher proportion of dipper blood pressure patterns, lower blood pressure variability, and higher drug adherence than UC. The development of telemedicine may be the cornerstone of hypertension management in primary care.
Humans ; Blood Pressure ; Blood Pressure Monitoring, Ambulatory ; Hypertension/therapy* ; Telemedicine/methods* ; Hypotension

BACKGROUND: In the wake of the coronavirus disease 2019 (COVID-19) pandemic, people need to practice social distancing in order to protect themselves from SARS-CoV-2 infection. In such stressful situations, remote cardiac rehabilitation (CR) might be a viable alternative to the outpatient CR program. METHODS: We prospectively investigated patients hospitalized for heart failure (HF) with a left ventricular ejection fraction of < 50%. As for patients who participated in the remote CR program, telephone support was provided by cardiologists and nurses who specialized in HF every 2 weeks after discharge. The emergency readmission rate within 30 days of discharge was compared among the outpatient CR, remote CR, and non-CR groups, and the EQ-5D score was compared between the outpatient CR and remote CR groups. RESULTS: The participation rate of HF patients in our remote CR program elevated during the COVID-19 pandemic. As observed in the outpatient CR group (n = 69), the emergency readmission rate within 30 days of discharge was lower in the remote CR group (n = 30) than in the non-CR group (n = 137) (P = 0.02). The EQ-5D score was higher in the remote CR group than in the outpatient CR group (P = 0.03) 30 days after discharge. CONCLUSIONS Remote CR is as effective as outpatient CR for improving the short-term prognosis of patients hospitalized for heart failure post-discharge. This suggests that the remote CR program can be provided as a good alternative to the outpatient CR program.
Aged ; Betacoronavirus ; Cardiac Rehabilitation ; methods ; Coronavirus Infections ; epidemiology ; Heart Failure ; rehabilitation ; Humans ; Japan ; Middle Aged ; Monitoring, Ambulatory ; Pandemics ; Pneumonia, Viral ; epidemiology ; Prospective Studies ; Self Care ; Telemedicine ; methods ; Telephone

The ongoing pandemic in Singapore is part of a global pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To control the spread of COVID-19 and prevent the healthcare system from being overwhelmed, 'circuit breaker' measures were introduced between 7 April and 1 June 2020 in Singapore. There is thus a crucial need for innovative approaches to the provision and delivery of healthcare in the context of safe-distancing by harnessing telemedicine, especially for patients with chronic diseases who have traditionally been managed in tertiary institutions. We present a summary of how the Virtual Monitoring Clinic has benefited the practice of our outpatient rheumatology service during the COVID-19 pandemic. The virtual consultations address the need for safe-distancing by limiting face-to-face appointments and unnecessary exposure of patients to the hospital where feasible. This approach ensures that the patients are monitored appropriately for drug toxicities and side-effects, maintained on good disease control, and provided with patient education.
Ambulatory Care/methods* ; Antirheumatic Agents/therapeutic use* ; COVID-19 ; Delivery of Health Care ; Humans ; Nurse Practitioners ; Pharmacists ; Rheumatic Diseases/drug therapy* ; Rheumatology/methods* ; SARS-CoV-2 ; Singapore ; Telemedicine/organization & administration* ; Tertiary Care Centers

Allergy and Immunology ; Ambulatory Care ; Autoimmune Diseases/therapy* ; COVID-19 ; Communicable Disease Control ; Connective Tissue Diseases/therapy* ; Delivery of Health Care/methods* ; Dermatology ; Humans ; Immunosuppressive Agents/therapeutic use* ; Patient Selection ; SARS-CoV-2 ; Singapore ; Skin Diseases, Vesiculobullous/therapy* ; Telemedicine/methods* ; Tertiary Care Centers ; Vasculitis/therapy*

INTRODUCTION: Telestroke allows for remote determination of suitability for treatment with thrombolysis in patients with acute ischaemic stroke. However, this approach is time-dependent and most centres have yet to achieve the recommended treatment times. We describe a quality improvement initiative aimed at improving the telestroke workflow and treatment times at our centre. METHODS: A multidisciplinary workgroup comprising clinicians, stroke case managers and radiology staff was formed to oversee the initiative. A phase-by-phase review of the existing workflow was done to identify the reasons for delay. Phase-specific measures were then introduced to address these delays, and a data-monitoring system was established to track the impact of these measures. The initiatives were implemented through four Plan-Do-Study-Act cycles. The door-to-needle (DTN) times for thrombolysis and clinical outcomes before and after the interventions were compared. RESULTS: A total of 104 patients were evaluated. The median DTN time improved from 96 minutes to 78 minutes post implementation of initiatives (p = 0.003). Fewer patients had symptomatic intracranial haemorrhages (8.5% vs. 24.2%; p = 0.03), and more patients had improvements in their National Institutes of Health Stroke Scale score (47.9% vs. 25.0%; p = 0.031) after the initiatives were introduced. CONCLUSION The quality improvement initiative resulted in a reduction in median DTN time. Our approach allowed for a systematic method to resolve delays within the telestroke workflow. This initiative is part of an ongoing effort aimed at providing thrombolysis safely to eligible patients in the shortest possible time.
Adult ; Aged ; Aged, 80 and over ; Emergency Service, Hospital ; organization & administration ; Female ; Humans ; Interprofessional Relations ; Intracranial Hemorrhages ; prevention & control ; Male ; Middle Aged ; Quality Improvement ; Severity of Illness Index ; Singapore ; Stroke ; therapy ; Telemedicine ; methods ; organization & administration ; standards ; Thrombolytic Therapy ; methods ; Time ; Tissue Plasminogen Activator ; therapeutic use ; Treatment Outcome

OBJECTIVES: This study analyzed the health technology trends and sentiments of users using Twitter data in an attempt to examine the public's opinions and identify their needs. METHODS: Twitter data related to health technology, from January 2010 to October 2016, were collected. An ontology related to health technology was developed. Frequently occurring keywords were analyzed and visualized with the word cloud technique. The keywords were then reclassified and analyzed using the developed ontology and sentiment dictionary. Python and the R program were used for crawling, natural language processing, and sentiment analysis. RESULTS: In the developed ontology, the keywords are divided into ‘health technology‘ and ‘health information‘. Under health technology, there are are six subcategories, namely, health technology, wearable technology, biotechnology, mobile health, medical technology, and telemedicine. Under health information, there are four subcategories, namely, health information, privacy, clinical informatics, and consumer health informatics. The number of tweets about health technology has consistently increased since 2010; the number of posts in 2014 was double that in 2010, which was about 150 thousand posts. Posts about mHealth accounted for the majority, and the dominant words were ‘care‘, ‘new‘, ‘mental‘, and ‘fitness‘. Sentiment analysis by subcategory showed that most of the posts in nearly all subcategories had a positive tone with a positive score. CONCLUSIONS: Interests in mHealth have risen recently, and consequently, posts about mHealth were the most frequent. Examining social media users' responses to new health technology can be a useful method to understand the trends in rapidly evolving fields.
Biomedical Technology ; Biotechnology ; Boidae ; Data Mining ; Informatics ; Medical Informatics ; Methods ; Natural Language Processing ; Privacy ; Public Opinion ; Social Media ; Telemedicine

The purpose of this study was to evaluate the accuracy of a mobile wireless digital automatic blood pressure monitor for clinical use and mobile health (mHealth). In this study, a manual sphygmomanometer and a digital blood pressure monitor were tested in 100 participants in a repetitive and sequential manner to measure blood pressure. The guidelines for measurement used the Korea Food & Drug Administration protocol, which reflects international standards, such as the American National Standard Institution/Association for the Advancement of Medical Instrumentation SP 10: 1992 and the British Hypertension Society protocol. Measurements were generally consistent across observers according to the measured mean ± SD, which ranged in 0.1 ± 2.6 mmHg for systolic blood pressure (SBP) and 0.5 ± 2.2 mmHg for diastolic blood pressure (DBP). For the device and the observer, the difference in average blood pressure (mean ± SD) was 2.3 ± 4.7 mmHg for SBP and 2.0 ± 4.2 mmHg for DBP. The SBP and DBP measured in this study showed accurate measurements that satisfied all criteria, including an average difference that did not exceed 5 mmHg and a standard deviation that did not exceed 8 mmHg. The mobile wireless digital blood pressure monitor has the potential for clinical use and managing one's own health.
Blood Pressure Monitors* ; Blood Pressure* ; Hypertension ; Korea ; Methods* ; Self Care* ; Sphygmomanometers ; Telemedicine

OBJECTIVES: Smartphones represent a promising technology for patient-centered healthcare. It is claimed that data mining techniques have improved mobile apps to address patients’ needs at subgroup and individual levels. This study reviewed the current literature regarding data mining applications in patient-centered mobile-based information systems. METHODS: We systematically searched PubMed, Scopus, and Web of Science for original studies reported from 2014 to 2016. After screening 226 records at the title/abstract level, the full texts of 92 relevant papers were retrieved and checked against inclusion criteria. Finally, 30 papers were included in this study and reviewed. RESULTS: Data mining techniques have been reported in development of mobile health apps for three main purposes: data analysis for follow-up and monitoring, early diagnosis and detection for screening purpose, classification/prediction of outcomes, and risk calculation (n = 27); data collection (n = 3); and provision of recommendations (n = 2). The most accurate and frequently applied data mining method was support vector machine; however, decision tree has shown superior performance to enhance mobile apps applied for patients’ self-management. CONCLUSIONS: Embedded data-mining-based feature in mobile apps, such as case detection, prediction/classification, risk estimation, or collection of patient data, particularly during self-management, would save, apply, and analyze patient data during and after care. More intelligent methods, such as artificial neural networks, fuzzy logic, and genetic algorithms, and even the hybrid methods may result in more patients-centered recommendations, providing education, guidance, alerts, and awareness of personalized output.
Artificial Intelligence ; Data Collection ; Data Mining* ; Decision Trees ; Delivery of Health Care ; Early Diagnosis ; Education ; Follow-Up Studies ; Fuzzy Logic ; Humans ; Information Systems* ; Mass Screening ; Methods ; Mobile Applications ; Patient Care ; Self Care ; Smartphone ; Statistics as Topic ; Support Vector Machine ; Telemedicine

OBJECTIVES: This article reviews an evaluation vector model driven from a participatory action research leveraging a collective inquiry system named SMILE (Stanford Mobile Inquiry-based Learning Environment). METHODS: SMILE has been implemented in a diverse set of collective inquiry generation and analysis scenarios including community health care-specific professional development sessions and community-based participatory action research projects. In each scenario, participants are given opportunities to construct inquiries around physical and emotional health-related phenomena in their own community. RESULTS: Participants formulated inquiries as well as potential clinical treatments and hypothetical scenarios to address health concerns or clarify misunderstandings or misdiagnoses often found in their community practices. From medical universities to rural village health promotion organizations, all participatory inquiries and potential solutions can be collected and analyzed. The inquiry and solution sets represent an evaluation vector which helps educators better understand community health issues at a much deeper level. CONCLUSIONS: SMILE helps collect problems that are most important and central to their community health concerns. The evaluation vector, consisting participatory and collective inquiries and potential solutions, helps the researchers assess the participants' level of understanding on issues around health concerns and practices while helping the community adequately formulate follow-up action plans. The method used in SMILE requires much further enhancement with machine learning and advanced data visualization.
Community-Based Participatory Research ; Diagnostic Errors ; Follow-Up Studies ; Health Promotion ; Health Services Research* ; Learning* ; Machine Learning ; Methods ; Public Health ; Public Health Informatics ; Social Learning ; Telemedicine

BACKGROUND: Work-related stress is one of the major causes of occupational ill health. In line with the regulatory framework on occupational health and safety (OSH), adequate models for assessing and managing risk need to be identified so as to minimize the impact of this stress not only on workers' health, but also on productivity. METHODS: After close analysis of the Italian and European reference regulatory framework and work-related stress assessment and management models used in some European countries, we adopted the UK Health and Safety Executive's (HSE) Management Standards (MS) approach, adapting it to the Italian context in order to provide a suitable methodological proposal for Italy. RESULTS: We have developed a work-related stress risk assessment strategy, meeting regulatory requirements, now available on a specific web platform that includes software, tutorials, and other tools to assist companies in their assessments. CONCLUSION: This methodological proposal is new on the Italian work-related stress risk assessment scene. Besides providing an evaluation approach using scientifically validated instruments, it ensures the active participation of occupational health professionals in each company. The assessment tools provided enable companies not only to comply with the law, but also to contribute to a database for monitoring and assessment and give access to a reserved area for data analysis and comparisons.
Efficiency ; Health Policy ; Italy* ; Jurisprudence ; Methods ; Occupational Health ; Risk Assessment* ; Statistics as Topic ; Telemedicine