Connected Health: An Open Innovation Perspective.

The concept of connected health has gained traction in recent years as a new technology enabled and networked model of health care delivery. It is often used as an umbrella term for eHealth, digital health, health informatics, telemedicine, mHealth and involves the establishment and management of a network of stakeholders with the aim of improving health care quality and out- comes. Yet a lack of open interactions and knowledge networks and the missing integration of the larger constituency of interdisciplinary experts are limiting the execution of the model and restricting its potential to devise services and interventions around patient’s needs with shared health related data. Drawing parallels between the concept of connected health and open innovation, the networked innovation model, which involves efficient management of knowledge flows and complex networks for successful innovations; in this paper we outline the practice of open innovation in health care and suggest connecting stakeholders in the health care ecosystem in an open innovative format. In doing so we present a categorization of firms in the health care ecosystem into open innovation profiles for getting connected and propose an open innovative framework for maximizing the potential of the concept of connected health

“Data is the new oil”: citizen science and informed consent in an era of researchers handling of an economically valuable resource

As with other areas of the social world, academic research in the contemporary healthcare setting has undergone adaptation and change. For example, research methods are increasingly incorporating citizen participation in the research process, and there has been an increase in collaborative research that brings academic and industry partners together. There have been numerous positive outcomes associated with both of these growing methodological and collaborative processes; nonetheless, both bring with them ethical considerations that require careful thought and attention. This paper addresses the ethical considerations that research teams must consider when using participatory methods and/or when working with industry and outlines a novel informed consent matrix designed to maintain the high ethical standard to which academic research in the healthcare arena has traditionally adhered

Establishing consensus on key public health indicators for the monitoring and evaluating childhood obesity interventions: a Delphi panel study

Background: Childhood obesity is influenced by myriad individual, societal and environmental factors that are not typically reflected in current interventions. Socio-ecological conditions evolve and require ongoing monitoring in terms of assessing their influence on child health. The aim of this study was to identify and prioritise indicators deemed relevant by public health authorities for monitoring and evaluating childhood obesity interventions. Method: A three-round Delphi Panel composed of experts from regions across Europe, with a remit in childhood obesity intervention, were asked to identify indicators that were a priority in their efforts to address childhood obesity in their respective jurisdictions. In Round 1, 16 panellists answered a series of open-ended questions to identify the most relevant indicators concerning the evaluation and subsequent monitoring of interventions addressing childhood obesity, focusing on three main domains: built environments, dietary environments, and health inequalities. In Rounds 2 and 3, panellists rated the importance of each of the identified indicators within these domains, and the responses were then analysed quantitatively. Results: Twenty-seven expert panellists were invited to participate in the study. Of these, 16/27 completed round 1 (5 9% response rate), 14/16 completed round 2 (87.5% response rate), and 8/14 completed the third and final round (57% response rate). Consensus (defined as > 70% agreement) was reached on a total of 45 of the 87 indicators (49%) across three primary domains (built and dietary environments and health inequalities), with 100% consensus reached for 5 of these indicators (6%). Conclusion: Forty-five potential indicators were identified, pertaining primarily to the dietary environment, built environment and health inequalities. These results have important implications more widely for evaluating interventions aimed at childhood obesity reduction and prevention.European Commission Horizon 2020Science Foundation IrelandInsight Research CentreRoyal College of Surgeons in Ireland2021-02-19 JG: broken PDF replace

Health literacy in Europe. comparative results of the European health literacy survey (HLS-EU)

Sørensen K, Pelikan JM, Röthlin F, et al. Health literacy in Europe. comparative results of the European health literacy survey (HLS-EU). The European Journal of Public Health. 2015;25(6):1053-1058

BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment

Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.Comment: Accepted version to be published in 2020, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, Canad

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions

Health literacy and public health: A systematic review and integration of definitions and models

<p>Abstract</p> <p>Background</p> <p>Health literacy concerns the knowledge and competences of persons to meet the complex demands of health in modern society. Although its importance is increasingly recognised, there is no consensus about the definition of health literacy or about its conceptual dimensions, which limits the possibilities for measurement and comparison. The aim of the study is to review definitions and models on health literacy to develop an integrated definition and conceptual model capturing the most comprehensive evidence-based dimensions of health literacy.</p> <p>Methods</p> <p>A systematic literature review was performed to identify definitions and conceptual frameworks of health literacy. A content analysis of the definitions and conceptual frameworks was carried out to identify the central dimensions of health literacy and develop an integrated model.</p> <p>Results</p> <p>The review resulted in 17 definitions of health literacy and 12 conceptual models. Based on the content analysis, an integrative conceptual model was developed containing 12 dimensions referring to the knowledge, motivation and competencies of accessing, understanding, appraising and applying health-related information within the healthcare, disease prevention and health promotion setting, respectively.</p> <p>Conclusions</p> <p>Based upon this review, a model is proposed integrating medical and public health views of health literacy. The model can serve as a basis for developing health literacy enhancing interventions and provide a conceptual basis for the development and validation of measurement tools, capturing the different dimensions of health literacy within the healthcare, disease prevention and health promotion settings.</p