Costs, effects and implementation of routine data emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions: a systematic review protocol

INTRODUCTION: Emergency admission risk prediction models are increasingly used to identify patients, typically with one or more chronic conditions, for proactive management in primary care to avoid admissions, save costs and improve patient experience. AIM: To identify and review the published evidence on the costs, effects and implementation of emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions. METHODS: We shall search for studies of healthcare interventions using routine data-generated emergency admission risk models. We shall report: the effects on emergency admissions and health costs; clinician and patient views; and implementation findings. We shall search ASSIA, CINAHL, the Cochrane Library, HMIC, ISI Web of Science, MEDLINE and Scopus from 2005, review references in and citations of included articles, search key journals and contact experts. Study selection, data extraction and quality assessment will be performed by two independent reviewers. ETHICS AND DISSEMINATION: No ethical permissions are required for this study using published data. Findings will be disseminated widely, including publication in a peer-reviewed journal and through conferences in primary and emergency care and chronic conditions. We judge our results will help a wide audience including primary care practitioners and commissioners, and policymakers. TRIAL REGISTRATION NUMBER: CRD42015016874; Pre-results

A framework for cloud-based context-aware information services for citizens in smart cities

© 2014 Khan et al.; licensee Springer. Background: In the context of smart cities, public participation and citizen science are key ingredients for informed and intelligent planning decisions and policy-making. However, citizens face a practical challenge in formulating coherent information sets from the large volumes of data available to them. These large data volumes materialise due to the increased utilisation of information and communication technologies in urban settings and local authorities’ reliance on such technologies to govern urban settlements efficiently. To encourage effective public participation in urban governance of smart cities, the public needs to be facilitated with the right contextual information about the characteristics and processes of their urban surroundings in order to contribute to the aspects of urban governance that affect them such as socio-economic activities, quality of life, citizens well-being etc. The cities on the other hand face challenges in terms of crowd sourcing with quality data collection and standardisation, services inter-operability, provisioning of computational and data storage infrastructure. Focus: In this paper, we highlight the issues that give rise to these multi-faceted challenges for citizens and public administrations of smart cities, identify the artefacts and stakeholders involved at both ends of the spectrum (data/service producers and consumers) and propose a conceptual framework to address these challenges. Based upon this conceptual framework, we present a Cloud-based architecture for context-aware citizen services for smart cities and discuss the components of the architecture through a common smart city scenario. A proof of concept implementation of the proposed architecture is also presented and evaluated. The results show the effectiveness of the cloud-based infrastructure for the development of a contextual service for citizens

Measurement and Evaluation of Smart City Outcomes for Smarter Governance

Global urbanization trends are associated with a proliferation of smart city developments enabled by advanced Information and Communication Technologies designed to address contemporary challenges and develop innovative solutions in cities and regions. This chapter sets out to examine the relationship between smart city development and smart governance, both the contribution of governance to smart city development and its potential benefits for city governance. Building on an analysis of research on UK smart city case studies, this chapter argues that the contribution of smart city developments and their success outcomes to governance is influenced by how cities address the challenges of measurement and evaluation of smart city developments