Service provider

About: Service provider is a research topic. Over the lifetime, 55107 publications have been published within this topic receiving 894381 citations. The topic is also known as: external service provider & internal service provider.

Integrating care for older people with complex needs: key insights and lessons from a seven-country cross-case analysis

Abstract: Background: To address the challenges of caring for a growing number of older people with a mix of both health problems and functional impairment, programmes in different countries have different approaches to integrating health and social service supports. Objective: The goal of this analysis is to identify important lessons for policy makers and service providers to enable better design, implementation and spread of successful integrated care models. Methods: This paper provides a structured cross-case synthesis of seven integrated care programmes in Australia, Canada, the Netherlands, New Zealand, Sweden, the UK and the USA. Key findings: All seven programmes involved bottom-up innovation driven by local needs and included: (1) a single point of entry, (2) holistic care assessments, (3) comprehensive care planning, (4) care co-ordination and (5) a well-connected provider network. The process of achieving successful integration involves collaboration and, although the specific types of collaboration varied considerably across the seven case studies, all involved a care coordinator or case manager. Most programmes were not systematically evaluated but the two with formal external evaluations showed benefit and have been expanded. Conclusions: Case managers or care coordinators who support patient-centred collaborative care are key to successful integration in all our cases as are policies that provide funds and support for local initiatives that allow for bottom-up innovation. However, more robust and systematic evaluation of these initiatives is needed to clarify the ‘business case’ for integrated health and social care and to ensure successful generalization of local successes.

Clinical Trials Offshored: On Private Sector Science and Public Health

Abstract: This article addresses the offshoring of clinical trials to middle- and low-income countries, and the complicated ways in which they have become integral to public health and quality of care in these contexts. I focus on the operations of United States-based contract research organizations (CROs), which make up a specialized global industry focusing on the recruitment of human subjects and investigators; they are key players in an outsourced world of clinical development ‘service providers’. To get an on-the-ground understanding of the offshored clinical trial, I worked with regulators, health services administrators, and research clinicians in Eastern Europe and Latin America, two clinical trial market ‘growth regions’. By addressing the strategies of evidence-making that inform clinical trial offshoring, this article identifies the context-specific calculations by which experimental groups are being identified. It also addresses aspects of the clinical trial operational model, in which the failure to predict safety outcomes or a paradigm of expected failure is being exported along with the offshored trial. By highlighting the uncertainties of clinical research, this article points to gaps in systems of human protection as it considers new forms of accountability in private sector science and public health.

A healthcare monitoring system using random forest and internet of things (IoT)

Abstract: The Internet of Things (IoT) enabled various types of applications in the field of information technology, smart and connected health care is notably a crucial one is one of them. Our physical and mental health information can be used to bring about a positive transformation change in the health care landscape using networked sensors. It makes it possible for monitoring to come to the people who don't have ready access to effective health monitoring system. The captured data can then be analyzed using various machine learning algorithms and then shared through wireless connectivity with medical professionals who can make appropriate recommendations. These scenarios already exist, but we intend to enhance it by analyzing the past data for predicting future problems using prescriptive analytics. It will allow us to move from reactive to visionary approach by rapidly spotting trends and making recommendations on behalf of the actual medical service provider. In this paper, the authors have applied different machine learning techniques and considered public datasets of health care stored in the cloud to build a system, which allows for real time and remote health monitoring built on IoT infrastructure and associated with cloud computing. The system will be allowed to drive recommendations based on the historic and empirical data lying on the cloud. The authors have proposed a framework to uncover knowledge in a database, bringing light to disguise patterns which can help in credible decision making. This paper has evaluated prediction systems for diseases such as heart diseases, breast cancer, diabetes, spect_heart, thyroid, dermatology, liver disorders and surgical data using a number of input attributes related to that particular disease. Experimental results are conducted using a few machine learning algorithms considered in this paper like K-NN, Support Vector Machine, Decision Trees, Random Forest, and MLP.

What is 5G? Emerging 5G Mobile Services and Network Requirements

Abstract: In this paper, emerging 5G mobile services are investigated and categorized from the perspective of not service providers, but end-users. The development of 5G mobile services is based on an intensive analysis of the global trends in mobile services. Additionally, several indispensable service requirements, essential for realizing service scenarios presented, are described. To illustrate the changes in societies and in daily life in the 5G era, five megatrends, including the explosion of mobile data traffic, the rapid increase in connected devices, everything on the cloud, hyper-realistic media for convergence services and knowledge as a service enabled by big-data analysis, are examined. Based on such trends, we classify the new 5G services into five categories in terms of the end-users’ experience as follows: immersive 5G services, intelligent 5G services, omnipresent 5G services, autonomous 5G services and public 5G services. Moreover, several 5G service scenarios in each service category are presented, and essential technical requirements for realizing the aforementioned 5G services are suggested, along with a competitiveness analysis on 5G services/devices/network industries and the current condition of 5G technologies.