A mixed methods study of factors influencing health managers acceptance of eHealth services in the Kingdom of Saudi Arabia.

The Kingdom of Saudi Arabia (KSA) is a country with one of the largest land masses and most difficult geographical terrain in the Middle East. The accessibility of advanced health services, especially for people in rural areas, has been considered one of the main health challenges. Health services across the country are accessible through three categories of providers. The Ministry of Health (MOH), which is the dominant health provider, is responsible for 60% of all health services and facilities. The private health sector and other government-run health authorities are the providers for the remaining 40%. Many initiatives to embrace technology in healthcare were launched by the MOH to advance the level of acceptance. One of the initiatives was the ambitious National eHealth Strategy, which was launched in 2011 to govern eHealth projects across the country, and to set consistent standards, policies, and procedures for the practice activities. This study was sponsored by the MOH as part of a bigger plan to involve stakeholders in the digital transformation. The overall aim of this doctoral research was to explore the factors that influence health managers' acceptance of eHealth services in KSA. The 1st phase was a systematic review (SR): based on a PRISMA-P guided protocol published with CRD Prospero, five databases were searched for studies published between 1993 and 2017. One reviewer performed the search; two reviewers screened the titles and abstracts. Exclusions were recorded with reasons. Tools appropriate to study design were applied independently by two reviewers to assess the quality of included studies. After duplicates were removed, 110 papers were screened and 15 studies met the inclusion criteria. From these 15 papers, 39 factors were identified as influencing varying levels of eHealth adoption and acceptance in KSA. Lack of studies on the views of health managers and limited studies from only a few geographical settings were also identified as knowledge gaps. The 2nd phase was a survey: an online questionnaire in both Arabic and English language was designed around the Unified Theory of Acceptance and Use of Technology (UTAUT) model determinants. Professionals with a health managerial role from multiple disciplines - such as health professions, administration, and health IT - were invited to take part in the study. Ethical approval had been gained. Participation links were distributed across a range of social media platforms. SPSS v25 was used for data analysis. Findings from the 2nd phase survey showed the significance (p < 0.05) of Performance Expectancy and Social Influence moderated by age to the Behavioural Intention of health managers as well as the Performance Expectancy and Facilitating Conditions to the actual Use Behaviour. Some ambiguous results need further investigations. The 3rd phase consisted of a mixture of face-to-face and telephone in-depth interviews with 21 health managers from Aseer province, KSA. Four umbrella domains were derived from the UTAUT model. The pre-defined themes from phases 1 and 2 were explored and mapped against the domains. Ethical approval had been gained. Microsoft Excel and NVivo were used for the data analysis. Through the interviews, ambiguity in the previous phase was clarified and the most influential factors based on the views of health managers in Aseer province, KSA, were identified. Three domains out of four showed significance: Performance Expectancy, Social Influence, and Facilitating Conditions. This mixed methods research design presented across three phases was adopted with the findings from each phase informing the next. Overall, the research confirmed the influence of the same factors on health managers' acceptance of eHealth services in KSA and generated original findings. First, by providing evidence that this area has not been previously studied through registering a protocol and publishing a systematic review. Second, by using social media platforms to support a novel recruitment approach for the study. Third, by employing UTAUT as a theoretical framework in both quantitative and qualitative phases. Finally, exploring eHealth practice in Aseer province, a part of KSA that has not previously been explored in the published literature. These original findings draw a clearer picture of the potential challenges faced by health managers in KSA in accepting and using eHealth services. The findings may also work as a foundational basis from which to better prepare other stakeholder groups for accepting eHealth services. By doing so, staff can more effectively utilise health technology interventions as key concepts in making successful and positive transformational and sustainable change to the delivery of healthcare

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Blockchain leveraged decentralized IoT eHealth framework

Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data

Design Strategy for Integrated Personal Health Records: Improving the User Experience of Digital Healthcare and Wellbeing

This dissertation addresses the timely problem of designing Integrated Personal Health Records (PHR). The goal is to provide citizens with digital user experiences, sustainable and flexible enough, for gaining control over their personal health information in a seamless way. Most importantly, so that people are able to reflect and act upon their selfknowledge, towards the accomplishment of their good health and wellbeing. Towards this end, the Integrated PHR as an emerging model in the field of Health IT, was the framework that set this research forward on exploring how communication and collaboration between patients and providers can be improved, which naturally impacts the field of HCI. Acknowledging that today patients are the ones who own all that is recorded about their health data, this new model was object of a design strategy that shaped the results presented in this dissertation. These have showed how patients can have more control of their health over time, through a patient-centered, organic system, which has the ability of combining multiple sources of data both from patient and provider side. As this new type of PHR fosters the creation of integrated networks, this milestone was achieved in this research by interacting with cross-channel user experiences that took part of nationwide healthcare ecosystems. The work presented herein, has demonstrated through the analysis and development of two use cases in cooperation with organizations connected to the Portuguese Ministry of Health, how an Integrated PHR can be a powerful personal tool, to be used by the citizen with undeniable value to the demands of an aging society. The use cases structured the thesis into two parts. The first part in collaboration with the Portuguese National Patient Portal, combines an Integrated PHR and incorporates the Portuguese Data Sharing Platform (PDS), which can be used by any Portuguese citizen. This use case study led to a proposal of the portal by also creating a foundational model for designing Integrated PHRs. The second part in collaboration with the Portuguese National Senior Telehealth Program (Saúde 24 Sénior), led to another proposal for an Integrated PHR, applying the outcomes from Part 1 and the requirements that derived from the findings explored in this second use case study. The proposed solution, has the potential to be used by the Portuguese senior community in the scope of home assistive care. Both proposals applied a user experience design methodology and included the development of two prototypes. The engagement of the stakeholders during the two case studies was accomplished with participatory design methods and followed a multidisciplinary approach to create solutions that would meet the human, politics and behavior interdependencies that were inherent to the process of working with large healthcare organizations. The provided contributions from this thesis intent to be part of a transition process that is changing the behavior of the healthcare sector, which is increasingly moving towards the improvement of the patient-provider relationship, patient engagement, collaborative care and positive computing, where digital technologies play a key role

Rapid health data repository allocation using predictive machine learning

Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Blockchain-based health record systems largely regulated by technology have emerged as another type of repository. Repositories for storing health data differ from one another based on cost, level of security and quality of performance. Not only has the type of repositories increased in recent years, but the quantum of health data to be stored has increased. For instance, the advent of wearable sensors that capture physiological signs has resulted in an exponential growth in digital health data. The increase in the types of repository and amount of data has driven a need for intelligent processes to select appropriate repositories as data is collected. However, the storage allocation decision is complex and nuanced. The challenges are exacerbated when health data are continuously streamed, as is the case with wearable sensors. Although patients are not always solely responsible for determining which repository should be used, they typically have some input into this decision. Patients can be expected to have idiosyncratic preferences regarding storage decisions depending on their unique contexts. In this paper, we propose a predictive model for the storage of health data that can meet patient needs and make storage decisions rapidly, in real-time, even with data streaming from wearable sensors. The model is built with a machine learning classifier that learns the mapping between characteristics of health data and features of storage repositories from a training set generated synthetically from correlations evident from small samples of experts. Results from the evaluation demonstrate the viability of the machine learning technique used. © The Author(s) 2020

Rockefeller Foundation 2010 Annual Report

Contains president's letter; 2010 program highlights, including support for Africa's green revolution, sustainable and equitable transportation policy, and healthy communities; grants list; financial report; and lists of trustees and staff

Factors influencing adoption of eHealth technologies in Ghana

This study covers factors influencing the adoption of electronic health (eHealth) technologies in Ghana. The study was designed as a quantitative survey with questionnaire as the main method of data gathering. A total of 1640 questionnaires were administered to users and potential users of eHealth technologies in both public and private healthcare centres in Ghana. The study concludes that institutional characteristics and healthcare manager characteristics have a high influence on eHealth adoption. However, factors related to performance expectancy and effort expectancy only have low influence on the adoption of eHealth devices and systems. Accordingly, the study makes recommendations to policymakers for improving eHealth adoption in the health sector. © The Author(s) 2019.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: All aspects of this study were funded by Cigna Global Wellbeing Solutions Ltd, UK

The implementation of a digital business strategy in hospitals: a case study on motives and difficulties of employees

In recent years digitalization has impacted most industries immensely. Organizations hope to increase their efficiency by improving communication and information exchange along the value chain while simultaneously reducing their costs. Even though the healthcare sector was quite late to follow, nowadays huge investments are made in this area to become patient centric, increase safety and reduce errors. Despite multiple studies analyzing how the digital hospital looks like and why digitalization is pursued, the human factor is often under-appreciated. Therefore, this case study aims to shed light on how employees perceive digitalization and the motives and difficulties in implementation they see. Our interviews with medical, administrative and IT staff of a hospital shows that even though the motives for digitalization are recognized, the impact of digitalization in the healthcare sector remains ambiguous to this day due to the challenges the industry is facing. Privacy issues, rejection on patient- and staff side and a lack of communication and guidance hinder the implementation of a digital business strategy. Additionally, our study reveals that technology is currently leading the process, which should not be the case as in a hospital the patient and therefore the processes that evolve around him should be in the center. Our implications and propositions help in solving these issues