New intelligent network approach for monitoring physiological parameters : the case of Benin

Benin health system is facing many challenges as: (i) affordable high-quality health care to a growing population providing need, (ii) patients’ hospitalization time reduction, (iii) and presence time of the nursing staff optimization. Such challenges can be solved by remote monitoring of patients. To achieve this, five steps were followed. 1) Identification of the Wireless Body Area Network (WBAN) systems’ characteristics and the patient physiological parameters’ monitoring. 2) The national Integrated Patient Monitoring Network (RIMP) architecture modeling in a cloud of Technocenters. 3) Cross-analysis between the characteristics and the functional requirements identified. 4) Each Technocenter’s functionality simulation through: a) the design approach choice inspired by the life cycle of V systems; b) functional modeling through SysML Language; c) the communication technology and different architectures of sensor networks choice studying. 5) An estimate of the material resources of the national RIMP according to physiological parameters. A National Integrated Network for Patient Monitoring (RNIMP) remotely, ambulatory or not, was designed for Beninese health system. The implementation of the RNIMP will contribute to improve patients’ care in Benin. The proposed network is supported by a repository that can be used for its implementation, monitoring and evaluation. It is a table of 36 characteristic elements each of which must satisfy 5 requirements relating to: medical application, design factors, safety, performance indicators and materiovigilance

Cultural competency in the delivery of health services for Indigenous people

Aim and objectives This review aims to examine available evidence on cultural competence in health care settings to identify key approaches and strategies that can contribute to improving the development and implementation of Indigenous health services and programs. The objectives are to: 1. define cultural competency –– we consider the significance of cultural competence and how it has been defined in international and local literature, including the use of similar terms and meanings 2. report on the quantity, nature and quality of available evidence –– we look at available evidence on cultural competency in Australia, New Zealand, Canada and the United States, including how cultural competence has been measured, and assess the quality of the evidence against basic methodological criteria 3. identify approaches and strategies that are effective in improving cultural competency among health services staff 4. examine the relationship between cultural competency and health outcomes 5. develop an evidence-informed conceptual framework of cultural competency

Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.Comment: 29 pages, 30 figures, 5 tables. Keywords: Big Data, Body Area Network, Body Sensor Network, Edge Computing, Fog Computing, Medical Cyberphysical Systems, Medical Internet-of-Things, Telecare, Tele-treatment, Wearable Devices, Chapter in Handbook of Large-Scale Distributed Computing in Smart Healthcare (2017), Springe

Commercialisation of eHealth Innovations in the Market of UK Healthcare Sector: A Framework for Sustainable Business Model.

This is the peer reviewed version of the following article: Festus Oluseyi Oderanti, and Feng Li, ‘Commercialization of eHealth innovations in the market of the UK healthcare sector: A framework for a sustainable business model’, Psychology & Marketing, Vol. 35 (2): 120-137, February 2018, which has been published in final form at https://doi.org/10.1002/mar.21074. Under embargo until 10 January 2020. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Demographic trends with extended life expectancy are placing increasing pressures on the UK state-funded healthcare budgets. eHealth innovations are expected to facilitate new avenues for cost-effective and safe methods of care, for enabling elderly people to live independently at their own homes and for assisting governments to cope with the demographic challenges. However, despite heavy investment in these innovations, large-scale deployment of eHealth continues to face significant obstacles, and lack of sustainable business models (BMs) is widely regarded as part of the greatest barriers. Through various empirical methods that include facilitated workshops, case studies of relevant organizations, and user groups, this paper investigates the reasons the private market of eHealth innovations has proved difficult to establish, and therefore it develops a framework for sustainable BMs that could elimiesnate barriers of eHealth innovation commercialization. Results of the study suggest that to achieve sustainable commercialization, BM frameworks and innovation diffusion characteristics should be considered complements but not substitutes.Peer reviewe

Ethical issues of electronic patient data and informatics in clinical trial settings

The field of cancer bio-informatics unites the disciplines of scientific and clinical research withclinical practice and the treatment of individual patients. There is a need to study patients andsometimes their families, over many decades, to follow disease progress and long-term outcomes.This may require research teams to access the routinely-collected health data from generalpractice and hospital health records, prior to and after the cancer diagnosis is made. This clinicalinformation will increasingly include data provided by patients or acquired from them throughwearable devices that can monitor or deliver treatment, and data acquired from genetic relativesof the patient.All of these data, whether explicitly collected for the purpose of a clinical study, or routinelycollected as part of a patient?s life-time healthcare journey, are personal health data. There areethical and legal requirements to manage these data with care. This chapter explores the ethicalrequirements for collecting, holding, analysing and sharing personal health data, and thelegislation covering such activities

Recruiting Older Workers: Realities and Needs of the Future Workforce

This chapter examines literature pertaining to the recruitment of older workers. It begins by addressing the question of relevance and why older worker recruitment matters. It then examines what is known about older workers, including their attitudes, motivations, and behaviors. Next the chapter addresses what employers are looking for in older workers and, more specifically, discusses the continuum of employers’ practices from those that aggressively try to attract and retain older workers and apply a conservation model of older worker management to those that apply a depreciation model and focus primarily on retrenchment and downsizing older employees. Finally, it addresses how employers can recruit older workers through changes in organizational policies and practices

Developing an Intervention Toolbox for the Common Health Problems in the Workplace

Development of the Health ↔ Work Toolbox is described. The toolbox aims to reduce the workplace impact of common health problems (musculoskeletal, mental health, and stress complaints) by focusing on tackling work-relevant symptoms. Based on biopsychosocial principles this toolbox supplements current approaches by occupying the zone between primary prevention and healthcare. It provides a set of evidence-informed principles and processes (knowledge + tools) for tackling work-relevant common health problems. The toolbox comprises a proactive element aimed at empowering line managers to create good jobs, and a ‘just in time’ responsive element for supporting individuals struggling with a work-relevant health problem. The key intention is helping people with common health problems to maintain work participation. The extensive conceptual and practical development process, including a comprehensive evidence review, produced a functional prototype toolbox that is evidence based and flexible in its use. End-user feedback was mostly positive. Moving the prototype to a fully-fledged internet resource requires specialist design expertise. The Health ↔ Work Toolbox appears to have potential to contribute to the goal of augmenting existing primary prevention strategies and healthcare delivery by providing a more comprehensive workplace approach to constraining sickness absence