A National Dialogue on Health Information Technology and Privacy

Increasingly, government leaders recognize that solving the complex problems facing America today will require more than simply keeping citizens informed. Meeting challenges like rising health care costs, climate change and energy independence requires increased level of collaboration. Traditionally, government agencies have operated in silos -- separated not only from citizens, but from each other, as well. Nevertheless, some have begun to reach across and outside of government to access the collective brainpower of organizations, stakeholders and individuals.The National Dialogue on Health Information Technology and Privacy was one such initiative. It was conceived by leaders in government who sought to demonstrate that it is not only possible, but beneficial and economical, to engage openly and broadly on an issue that is both national in scope and deeply relevant to the everyday lives of citizens. The results of this first-of-its-kind online event are captured in this report, together with important lessons learned along the way.This report served as a call to action. On his first full day in office, President Obama put government on notice that this new, more collaborative model can no longer be confined to the efforts of early adopters. He called upon every executive department and agency to "harness new technology" and make government "transparent, participatory, and collaborative." Government is quickly transitioning to a new generation of managers and leaders, for whom online collaboration is not a new frontier but a fact of everyday life. We owe it to them -- and the citizens we serve -- to recognize and embrace the myriad tools available to fulfill the promise of good government in the 21st Century.Key FindingsThe Panel recommended that the Administration give stakeholders the opportunity to further participate in the discussion of heath IT and privacy through broader outreach and by helping the public to understand the value of a person-centered view of healthcare information technology

Data science for health-care: Patient condition recognition

>Magister Scientiae - MScThe emergence of the Internet of Things (IoT) and Artificial Intelligence (AI) have elicited increased interest in many areas of our daily lives. These include health, agriculture, aviation, manufacturing, cities management and many others. In the health sector, portable vital sign monitoring devices are being developed using the IoT technology to collect patients’ vital signs in real-time. The vital sign data acquired by wearable devices is quantitative and machine learning techniques can be applied to find hidden patterns in the dataset and help the medical practitioner with decision making. There are about 30000 diseases known to man and no human being can possibly remember all of them, their relations to other diseases, their symptoms and whether the symptoms exhibited by the patients are early warnings of a fatal disease. In light of this, Medical Decision Support Systems (MDSS) can provide assistance in making these crucial assessments. In most decision support systems factors a ect each other; they can be contradictory, competitive, and complementary. All these factors contribute to the overall decision and have di erent degrees of influence [85]. However, while there is more need for automated processes to improve the health-care sector, most of MDSS and the associated devices are still under clinical trials. This thesis revisits cyber physical health systems (CPHS) with the objective of designing and implementing a data analytics platform that provides patient condition monitoring services in terms of patient prioritisation and disease identification [1]. Di erent machine learning algorithms are investigated by the platform as potential candidate for achieving patient prioritisation. These include multiple linear regression, multiple logistic regression, classification and regression decision trees, single hidden layer neural networks and deep neural networks. Graph theory concepts are used to design and implement disease identification. The data analytics platform analyses data from biomedical sensors and other descriptive data provided by the patients (this can be recent data or historical data) stored in a cloud which can be private local health Information organisation (LHIO) or belonging to a regional health information organisation (RHIO). Users of the data analytics platform consisting of medical practitioners and patients are assumed to interact with the platform through cities’ pharmacies , rural E-Health kiosks end user applications

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

Vehicular Networks for Combating a Worldwide Pandemic: Preventing the Spread of COVID-19

As a worldwide pandemic, the coronavirus disease-19 (COVID-19) has caused serious restrictions in people's social life, along with the loss of lives, the collapse of economies and the disruption of humanitarian aids. Despite the advance of technological developments, we, as researchers, have witnessed that several issues need further investigation for a better response to a pandemic outbreak. With this motivation, researchers recently started developing ideas to stop or at least reduce the spread of the pandemic. While there have been some prior works on wireless networks for combating a pandemic scenario, vehicular networks and their potential bottlenecks have not yet been fully examined. This article provides an extensive discussion on vehicular networking for combating a pandemic. We provide the major applications of vehicular networking for combating COVID-19 in public transportation, in-vehicle diagnosis, border patrol and social distance monitoring. Next, we identify the unique characteristics of the collected data in terms of privacy, flexibility and coverage, then highlight corresponding future directions in privacy preservation, resource allocation, data caching and data routing. We believe that this work paves the way for the development of new products and algorithms that can facilitate the social life and help controlling the spread of the pandemic.Comment: 8pages5figure

A Review of Atrial Fibrillation Detection Methods as a Service

Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals

Platform independent web-based telecardiology for connected heart care

Most of the commercial telecardiology systems are platform-dependent and operating system (OS)-dependent. This causes inconvenience to medical officer for retrieving data from database and hence reduce the work efficiency. In this paper, a platformindependent and OS-independent web-based telecardiology system, named VirtualDave System, is proposed based on client-server model and developed in Hypertext Markup Language 5 (HTML5), Active Server Pages (ASP) scripting and C# languages. This system allows users to log on and access the patient medical data from any technology devices that equipped with web browser and internet access. Besides, it also allows targeted users to communicate and get remote medical consultation without long distance traveling and long-time queuing. Verification result shows that this proposed system could be executed in any platform regardless the OS. This web-based telecardiology could significantly help to improve the health care services especially in rural area