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Remote patient management in patients with heart failure might help to detect early signs and symptoms of cardiac decompensation, thus enabling a prompt initiation of the appropriate treatment and care before a full manifestation of a heart failure decompensation. We aimed to investigate the efficacy of our remote patient management intervention on mortality and morbidity in a well defined heart failure population. The Telemedical Interventional Management in Heart Failure II (TIM-HF2) trial was a prospective, randomised, controlled, parallel-group, unmasked (with randomisation concealment), multicentre trial with pragmatic elements introduced for data collection. The trial was done in Germany, and patients were recruited from hospitals and cardiology practices. Eligible patients had heart failure, were in New York Heart Association class II or III, had been admitted to hospital for heart failure within 12 months before randomisation, and had a left ventricular ejection fraction (LVEF) of 45% or lower (or if higher than 45%, oral diuretics were being prescribed). Patients with major depression were excluded. Patients were randomly assigned (1:1) using a secure web-based system to either remote patient management plus usual care or to usual care only and were followed up for a maximum of 393 days. The primary outcome was percentage of days lost due to unplanned cardiovascular hospital admissions or all-cause death, analysed in the full analysis set. Key secondary outcomes were all-cause and cardiovascular mortality. This study is registered with ClinicalTrials.gov, number NCT01878630, and has now been completed. Between Aug 13, 2013, and May 12, 2017, 1571 patients were randomly assigned to remote patient management (n=796) or usual care (n=775). Of these 1571 patients, 765 in the remote patient management group and 773 in the usual care group started their assigned care, and were included in the full analysis set. The percentage of days lost due to unplanned cardiovascular hospital admissions and all-cause death was 4·88% (95% CI 4·55–5·23) in the remote patient management group and 6·64% (6·19–7·13) in the usual care group (ratio 0·80, 95% CI 0·65–1·00; p=0·0460). Patients assigned to remote patient management lost a mean of 17·8 days (95% CI 16·6–19·1) per year compared with 24·2 days (22·6–26·0) per year for patients assigned to usual care. The all-cause death rate was 7·86 (95% CI 6·14–10·10) per 100 person-years of follow-up in the remote patient management group compared with 11·34 (9·21–13·95) per 100 person-years of follow-up in the usual care group (hazard ratio [HR] 0·70, 95% CI 0·50–0·96; p=0·0280). Cardiovascular mortality was not significantly different between the two groups (HR 0·671, 95% CI 0·45–1·01; p=0·0560). The TIM-HF2 trial suggests that a structured remote patient management intervention, when used in a well defined heart failure population, could reduce the percentage of days lost due to unplanned cardiovascular hospital admissions and all-cause mortality. German Federal Ministry of Education and Research.

Purpose of ReviewThe purpose of this review is to describe the determinants of satisfaction with telemedicine (TM) and how they compare with in-person visits from both the perspective of patients and of providers.Recent FindingsThe use of TM will expand only if patients and providers are at least as satisfied with it as they are with in-person visits. Since deviations from expected care can result in reduced satisfaction regardless of the quality of the visit or objective medical outcomes, it is important to understand and to help form those expectations when possible. Patients consistently report 95–100% satisfaction rate with TM when compared with in-person appointments. They tend to cite the convenience of decreased travel times and costs as the main drivers for satisfaction with TM. Providers tend to be satisfied with TM if they have input into its development, there is administrative support, the technology is reliable and easy to use, and if there is adequate reimbursement for its use.SummarySatisfaction with TM is necessary for adoption of this new technology. To improve satisfaction it is important to consider factors that drive it both for patients and for providers.

Previous studies on telemedicine interventions have shown that older diabetic patients experience difficulty in using computers, which is a barrier to remote communication between medical teams and older diabetic patients. However, older people in China tend to find it easy to use mobile phones and personal messaging apps that have a user-friendly interface. Therefore, we designed a mobile health (mHealth) system for older people with diabetes that is based on mobile phones, has a streamlined operation interface, and incorporates maximum automation. The goal of the research was to investigate the use of mobile phone-based telemedicine apps for management of older Chinese patients with type 2 diabetes mellitus (T2DM). Variables of interest included efficacy and safety. A total of 91 older (aged over 65 years) patients with T2DM who presented to our department were randomly assigned to one of two groups. Patients in the intervention group (n=44) were provided glucometers capable of data transmission and received advice pertaining to medication, diet, and exercise via the mHealth telemedicine system. Patients assigned to the control group (n=47) received routine outpatient care with no additional intervention. Patients in both groups were followed up at regular 3-month intervals. After 3 months, patients in the intervention group showed significant (P<.05) improvement in postprandial plasma glucose level. After 6 months, patients in the intervention group exhibited a decreasing trend in postprandial plasma glucose and glycated hemoglobin levels compared with the baseline and those in the control group (P<.05). Mobile phone-based telemedicine apps help improve glycemic control in older Chinese patients with T2DM. China Clinical Trial Registration Center ChiCTR 1800015214; http://www.chictr.org.cn/showprojen.aspx?proj=25949 (Archived by WebCite at http://www.webcitation.org/73wKj1GMq).

\"This new volume explores how the merging of interactive multimedia with artificial intelligence has created new and advanced tools in healthcare. It looks at how the latest technologies (artificial intelligence, deep learning, machine learning, big data, IoT, smart device, etc.) help to manage health data, diagnose health issues, monitor treatment, predict pandemic diseases, and more. The book covers several important applications of multimedia in healthcare, including for data visualization purposes, for computer vision for elder healthcare monitoring, for detection of lung nodules, for health monitoring and management systems using machine learning techniques, and for fusion applications in medical image processing. The book goes into detail on the various methods and techniques for supporting multimedia systems for e-healthcare. The chapter authors discuss using data mining and machine learning techniques in the context of COVID-19 diagnosis and prediction, in detecting knee osteoarthritis using texture descriptor algorithms, in applying algorithms in fetal ECG enhancement using blockchain for wearable internet of things in healthcare, and more. A chapter also reviews how doctors can make good use of genomics and genetic data through advanced technology. The book concludes with discussions of open issues, challenges, and future research directions for using intelligent interactive multimedia in healthcare. Key features Provides an in-depth understanding of emerging technologies and integration of artificial intelligence, deep learning, big data, IoT in healthcare Details specific applications for the use of AI, big data, and IoT in healthcare Discusses how AI technology can help in formulating protective measures for COVID-19 and other diseases Includes case studies Intelligent Interactive Multimedia Systems for e-Healthcare Applications will be valuable to undergraduate and graduate students planning their careers in either industry or research and to software engineers for using multimedia with artificial intelligence, deep learning, big data, and IoT for healthcare applications\"-- Provided by publisher.

Purpose of ReviewTelemedicine is a rapidly growing healthcare sector that can improve access to care for underserved populations and offer flexibility and convenience to patients and clinicians alike. However, uncertainty about insurance coverage and reimbursement policies for telemedicine has historically been a major barrier to adoption, especially among physicians in private practice (the majority of practicing allergists).Recent FindingsThe COVID-19 public health emergency has highlighted the importance of telehealth as a safe and effective healthcare delivery model, with governments and payers rapidly expanding coverage and payment in an effort to ensure public access to healthcare in the midst of an infectious pandemic. This comprehensive review of updated telemedicine coverage and payment policies will include a tabular guide on how to appropriately bill and optimize reimbursement for telemedicine services.SummaryThis review of current trends in telemedicine coverage, billing, and reimbursement will outline the historical and current state of telemedicine payment policies in the USA, with special focus on recent policy changes implemented in light of COVID-19. The authors will also explore the potential future landscape of telehealth coverage and reimbursement beyond the resolution of the public health emergency.

Disasters and pandemics pose unique challenges to health care delivery. As health care resources continue to be stretched due to the increasing burden of the coronavirus disease (COVID-19) pandemic, telemedicine, including tele-education, may be an effective way to rationally allocate medical resources. During the COVID-19 pandemic, a multimodal telemedicine network in Sichuan Province in Western China was activated immediately after the first outbreak in January 2020. The network synergizes a newly established 5G service, a smartphone app, and an existing telemedicine system. Telemedicine was demonstrated to be feasible, acceptable, and effective in Western China, and allowed for significant improvements in health care outcomes. The success of telemedicine here may be a useful reference for other parts of the world.