Pocantico II: The Global Challenge of Health Systems, 2007

Summarizes discussions among global health leaders at a September 2007 meeting on public health monitoring, professional competencies, access to technologies and innovations, improving systems with information technology, and leveraging private sectors

A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

Envisioning patient safety in Telehealth: a research perspective

This article explores the need for research into patient safety in large-scale Telehealth systems faced with the perspective of its development extended to healthcare systems. Telehealth systems give rise to significant advantages in improving the quality of healthcare services as well as bringing about the possibility of new types of risk. A theoretical framework is proposed for patient safety for its approach as an emerging property in complex socio-technical systems (CSTS) and their modelling in layers. As regards this framework, the differential characteristic Telehealth elements of the system have been identified, with a greater emphasis on the level of Telehealth system and its typical subsystems. The bases of the analysis are based on references in the literature and the experience accumulated by the researchers in the area. In particular, a case describing an example of Telehealth to control patients undergoing treatment with oral anticoagulants is used. As a result, a series of areas of research into and topics regarding Telehealth patient safety are proposed to cover the detectable gaps. Both the theoretical and practical implications of the study are discussed and future perspectives are reflected on.This research has been partially supported by grants FISPI09-90110 ‘Innovation Platform in new services based on telemedicine and e-health for chronic and dependent patients -PITES’ from the Ministry of Health & Consumer Affairs; and FISPI13-00508 ‘Innovation platform in new services based on Telemedicine and e- Health: definition, design and development of tools for interoperability, patient safety and support to decision (PITES-ISA)’ from the Ministry of Economy and Competitiveness (Secretary of State of Research, Development and Innovation). The funders had no role in the study, decision to publish, or drafting of the manuscript.S

Mobile health systems and emergence

Changes in the age distribution of the population and increased prevalence of chronic illnesses, together with a shortage of health professionals and other resources, will increasingly challenge the ability of national healthcare systems to meet rising demand for services. Large-scale use of eHealth and mHealth services enabled by advances in ICT are frequently cited as providing part of the solution to this crisis in future provision. As part of this picture, self-monitoring and remote monitoring of patients, for example by means of smartphone apps and body-worn sensors, is on the way to becoming mainstream. In future, each individual’s personal health system may be able to access a large number of devices, including sensors embedded in the environment as well as in-body smart medical implants, in order to provide (semi-)autonomous health-related services to the user. This article presents some examples of mHealth systems based on emerging technologies, including body area networks (BANs), wireless and mobile technologies, miniature body-worn sensors and distributed decision support. Applications are described in the areas of management of chronic illnesses and management of (large- scale) emergency situations. In the latter setting BANs form part of an advanced ICT system proposed for future major incident management; including BANs for monitoring casualties and emergency services personnel during first response. Some challenges and possibilities arising from current and future emerging mHealth technologies, and the question of how emergence theory might have a bearing on understanding these challenges, is discussed here

A Study of eHealth from the Perspective of Social Sciences

The field of social sciences has become increasingly important in eHealth. Patients currently engage more proactively with health services. This means that eHealth is linked to many different areas of Social Sciences. The main purpose of this research is to analyze the state-of-the-art research on eHealth from the perspective of social sciences. To this end, a bibliometric analysis was conducted using the Web of Science database. The main findings show the evolution of publications, the most influential countries, the most relevant journals and papers, and the importance of the different areas of knowledge. Although there are some studies on eHealth within social sciences, most of them focus on very specific aspects and do not develop a holistic analysis. Thus, this paper contributes to academia by analyzing the state-of-the-art of research, as well as identifying the most relevant trends and proposing future lines of research such as the potential of eHealth as a professional training instrument, development of predictive models in eHealth, analysis of the eHealth technology acceptance model (TAM), efficient integration of eHealth within public systems, efficient budget management, or improvement in the quality of service for patients

E-health and e-welfare of Finland : Check Point 2022

The report provides an overview of progressive nationwide activities towards better e-services in Finland. The information system services of social welfare and health care are monitored by systematic gathering, analysis, and use of data, which allows the tracking of the progress of operations and the realisation of goals. In 2020 and 2021, six data collections were carried out to produce data for the monitoring of the Finnish ‘Information to support well-being and service renewal, eHealth and eSocial Strategy’. Some of the results presented in the report are also openly available in database cubes