mHealth in China and the United States: How Mobile Technology is Transforming Healthcare in the World's Two Largest Economies

In this paper, we explore ways mobile technology can help with these difficulties. Specifically, we look at avenues through which mobile devices boost productivity, aid communications, and help providers improve affordability, access, and treatment. Using data drawn from China and the United States as well as global trends, we look at recent developments andemerging opportunities in mobile health, or mHealth. We argue that mobile technology assists patients, health providers, and policymakers in several different respects. It helps patients by giving them tools to monitor their health conditions and communicate those results to physicians. It enables health providers to connect with colleagues and offers alternative sources of information for patients. It is also an important tool to inform policymakers on health delivery and medical outcomes

Monitoring Cardiovascular Disease-Patients with Mobile Computing Technologies

Physicians and healthcare networks have been slow to adopt electronic medical records and to integrate medical data with the ubiquitous mobile device. Mobile and wearable systems for continuous health monitoring constitute a key technology in helping the transition of health care to a more proactive and affordable healthcare. Cardiovascular Disease (CVD) includes dysfunctional conditions of the heart, arteries, and veins that supply oxygen to vital life-sustaining areas/organs of the body. CVD singly accounts for about 40% of all deaths worldwide. Over 80 per cent of CVD deaths take place in low- and middle-income countries. An estimated 17.5 million people died from cardiovascular disease in 2005, and expected to top 20 million per year by 2015. By 2030, more than 23 million people will die annually from CVDs. CVDs‘ patients face risks of recurrent acute cardiovascular events, hospital re-admission, and unfavourable quality of life. Heart Failure, (HF), leads to death if not properly managed and supervised. Current treatments for Congestive Heart Failure (CHF) provide a limited palliative outcome. New technologies are now pertinent to generate high-dimensional data that provide unprecedented opportunities for unbiased identification of biomarkers that can be used to optimize pre-operative planning, with the goal of avoiding costly post-operative complications and prolonged hospitalization. Due to the crucial role of remote monitoring for CVD patients, significant efforts from research communities and industry to propose and design a variety of CVD monitoring devices have become imperative. This paper builds a proof-of-concept and presents a cardiovascular monitoring system, Cardiovascular Disease Management System (CVDMS), for real-time information on patient‘s heart health status with respect to his/her heart beat in hemodynamics computation towards reducing re-admission incidence problem. Administered 485 questionnaires and interviewed 12 cardiologists, 45 physicians, and 23 pharmacists to gather details on vital CVD parameters. 469 of 485 questionnaires (96.70%) were validly completed and returned, while 16 (3.30%) were not. Searched internet databases and cognate texts for literature. A mobile CVDMS for HF was developed using UML, MySQL Server 5.0, Java servlets, Apache Tomcat 6.0 server, microcontroller, and Ozeki sms server. Patient completes a questionnaire on a J2ME platform-based computing device that measures the heartbeat rate. Biological signals acquired by CVDMS are processed by microcontroller. Pulses are counted within a space of one minute to know heartbeat rate per minute. The CVDMS application gets the heartbeat reading, and if the heart rate is abnormal, a trigger is set enabling the Ozeki SMS Gateway to send an alert to patient‘s next-of-kin and cardiologist. CVDMS guarantees individual patient‘s direct involvement to closely monitor changes in his/her vital signs and provide feedback to maintain an optimal health status. Medical personnel get alerted when life-threatening changes occur in establishing proper communication between patient and cardiologist via sms. Hemodynamics computation could be performed with the parameters obtained from the data supplied by CVDMS as a cardiovascular intervention to save many lives and improve quality of life. Keywords: artery stiffness; blood pressure; cardiologist; cardiovascular disease; heart attack; heart failure; hemodynamic volumetric parameters; hospital re-admission; hypertension; risk-factor

Ontology-driven monitoring of patient's vital signs enabling personalized medical detection and alert

A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs' monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient's condition on the most suited device within the physician's reach

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

Adding value to outpatient heart failure services and the patient journey through digital transformation of services

Introduction Heart failure (HF) is a chronic condition affecting over 900,000 people in the UK. The management of patients with HF frequently involves regular face-to-face appointments. Digital transformation of care with telemedicine, remote monitoring and mobile applications (Apps) may help improve patient experience and relieve demand on services. The Covid-19 pandemic resulted in an acceleration in telemedicine. This thesis evaluates pre-pandemic HF services at the Royal Brompton Hospital (RBH), identifying potential areas for improving patient journeys. Methods Retrospective cohort studies including over 200 patients were used to analyse the activities and actions resulting from HF clinic appointments over 3 years. Time-and-motion studies were conducted for each of the 4 consultant-led HF clinics at RBH, where flow through hospital was analysed for 58 patients. Eight clinicians and 8 patients who had undergone telemedicine consultations were interviewed about their experiences and perceptions, with narrative data thematically analysed. Focus groups and existing educational material were used to design an educational App for HF. Results Most HF patients under long-term follow-up were followed up twice yearly. At clinic visit, worsening HF symptoms and therapy change by clinicians were uncommon (21% and 36% of appointments respectively). Patients spent a median of 103 minutes in hospital on the day of an appointment for a median 20-minute consultation. The majority of consultations ran late. Clinicians and patients found telemedicine consultations generally acceptable, but both groups identified changes in time utilisation, clinical assessment, communication, and technology. Telemedicine appointments were shorter and involved less time waiting and travelling for patients. Patients and clinicians agreed that when patients are “stable”, telemedicine is preferred. A prototype HF educational “Avatar”-based App was produced. Conclusion Digital transformation of outpatient services, including telemedicine can improve patient and clinician experience, efficiency and rationalise limited resources, thus adding value to outpatient HF care.Open Acces

Innovative Business Model for Smart Healthcare Insurance

Information revolution and technology growth have made a considerable contribution to restraining the cost expansion and empowering the customer. They disrupted most business models in different industries. The customer-centric business model has pervaded the different sectors. Smart healthcare has made an enormous shift in patient life and raised their expectations of healthcare services quality. Healthcare insurance is an essential business in the healthcare sector; patients expect a new business model to meet their needs and enhance their wellness. This research develops a holistic smart healthcare architecture based on the recent development of information and communications technology. Then develops a disruptive healthcare insurance business model that adapts to this architecture and classifies the patient according to their technology needs. Finally, and implementing a prototype of a system that matches and suits the healthcare recipient condition to the proper healthcare insurance policy by applying Web Ontology Language (OWL) and rule-based reasoning model using SWRL using Protég

A Smart Service Platform for Cost Efficient Cardiac Health Monitoring

Aim: In this study we have investigated the problem of cost effective wireless heart health monitoring from a service design perspective. Subject and Methods: There is a great medical and economic need to support the diagnosis of a wide range of debilitating and indeed fatal non-communicable diseases, like Cardiovascular Disease (CVD), Atrial Fibrillation (AF), diabetes, and sleep disorders. To address this need, we put forward the idea that the combination of Heart Rate (HR) measurements, Internet of Things (IoT), and advanced Artificial Intelligence (AI), forms a Heart Health Monitoring Service Platform (HHMSP). This service platform can be used for multi-disease monitoring, where a distinct service meets the needs of patients having a specific disease. The service functionality is realized by combining common and distinct modules. This forms the technological basis which facilitates a hybrid diagnosis process where machines and practitioners work cooperatively to improve outcomes for patients. Results: Human checks and balances on independent machine decisions maintain safety and reliability of the diagnosis. Cost efficiency comes from efficient signal processing and replacing manual analysis with AI based machine classification. To show the practicality of the proposed service platform, we have implemented an AF monitoring service. Conclusion: Having common modules allows us to harvest the economies of scale. That is an advantage, because the fixed cost for the infrastructure is shared among a large group of customers. Distinct modules define which AI models are used and how the communication with practitioners, caregivers and patients is handled. That makes the proposed HHMSP agile enough to address safety, reliability and functionality needs from healthcare providers