Information technologies that facilitate care coordination: provider and patient perspectives

Health information technology is a core infrastructure for the chronic care model, integrated care, and other organized care delivery models. From the provider perspective, health information exchange (HIE) helps aggregate and share information about a patient or population from several sources. HIE technologies include direct messages, transfer of care, and event notification services. From the patient perspective, personal health records, secure messaging, text messages, and other mHealth applications may coordinate patients and providers. Patient-reported outcomes and social media technologies enable patients to share health information with many stakeholders, including providers, caregivers, and other patients. An information architecture that integrates personal health record and mHealth applications, with HIEs that combine the electronic health records of multiple healthcare systems will create a rich, dynamic ecosystem for patient collaboration

‘Enabling Technologies’ and ‘User-Participation’ as main Factors for Success of E-health Systems in Developing Countries like Pakistan

IT-applications in healthcare offers a novel way for improving the standard of healthcare services especially in developing states .In Pakistan both Government and private sector healthcare institutions are trying to take advantage of IT-applications for healthcare services just to come up with the rational-decisions for many healthcare-related problems in the country. ICTs for healthcare services provide opportunities for improvement by providing better, reliable and secure services to the patients, healthcare providers, staff and other stake holders both inside a hospital and also to distant patients where no physical healthcare infrastructure is available. This paper evaluates the effects of two key factors (enabling technologies and user participation) to see their influence on success of e-health systems in hospitals of Pakistan. The healthcare organizations having proper hardware and software and user participation in the development of IS ensures successful adoption and use of e-health systems in healthcare organizations anywhere including developing states. Keywords: Enabling Technologies, User-participation, E-health System, Developing Countrie

Miniaturized soft bio-hybrid robotics: a step forward into healthcare applications

Soft robotics is an emerging discipline that employs soft flexible materials such as fluids, gels and elastomers in order to enhance the use of robotics in healthcare applications. Compared to their rigid counterparts, soft robotic systems have flexible and rheological properties that are closely related to biological systems, thus allowing the development of adaptive and flexible interactions with complex dynamic environments. With new technologies arising in bioengineering, the integration of living cells into soft robotic systems offers the possibility of accomplishing multiple complex functions such as sensing and actuating upon external stimuli. These emerging bio-hybrid systems are showing promising outcomes and opening up new avenues in the field of soft robotics for applications in healthcare and other field

The Impact of Big Data on the Healthcare Information Systems

This article explores the possible impact of big data on healthcare information systems. Possible research issues include: 1). What applications in healthcare information systems are impacted most? 2). What algorithm/programs will be used for big data? 3). What privacy, security, and ethical issues are there for big data? In the biology area, big data becomes the newest technology for genomics. Other possible areas include pharmacovigilance, patient care, and medical supply chain management

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months