1,549 research outputs found

    Creating an Experiential Learning Based Multi-Disciplinary Program

    Get PDF
    For many years, curriculum development has considered learning outcomes at the program level largely via learning outcomes at the course level. Some programs have modified their designs to use different structures such as condensed courses or project based learning. Recently, there has been an increased interest in experiential learning as a way to facilitate student acquisition of real-world applicable capabilities while enhancing student learning of ‘soft skills’ such as professionalism, communication, and team management. Historically, such engagement including complexities of real-world problems has been accomplished through internships, co-op, capstone courses, or project based learning. In this paper we present an innovative model for experiential curriculum design based on skill requirements and learning outcomes derived from industry needs combined with technology enabled learning. The curriculum has been designed in a highly modular approach to ensure flexibility in student learning pathways to meet the requirements of the work related learning projects that are integrated as part of the program design. The conceptual model of this approach to curriculum design will be presented through a case study of the development of the informatics program at UOIT. Areas of caution are explored to identify recommendations for risk mitigation when developing a program utilizing this type of learning environment. In particular, student selection, technical infrastructure requirements, learning outcome measurement, faculty scheduling, and program management are considered

    Characterising extant technology related barriers & enablers for streamlined delivery of BP@home in North Central London: Report for NCL LTC Clinical Network

    Get PDF
    Report objectives: This report summarises the key findings of a place-based evaluation to identify barriers and enablers to the streamlined use of digital tools to support successful implementation of BP@home in North Central London (NCL). Specifically, we characterised the IT landscape in NCL, investigated the views and experiences of HCPs regarding the use of place-based IT solutions and processes, and synthesised a list of evidence-based recommendations for the consideration of NCL leadership team. Methods: We used a mixed methods research approach and six phases of investigation to address these aims, including desktop research, personal interviews and focus groups, action research, data analysis, synthesis and reporting. Results: The evaluation showed that there was a lack of standardisation across IT systems, internal processes and templates in PCNs in NCL, leading to challenges in implementing and using digital tools to support BP@home. These challenges were not unique to NCL. AccurX and the locally created NCL template are the most widely used IT tools to support the program in NCL. Other digital platforms being tested in NCL include Suvera, each with unique strengths and weaknesses. Other digital tools, such as Omron Connect, could be considered to support management of hypertension and other chronic conditions. HCPs faced challenges with patient engagement, data quality, IT system integration and resource allocation, but generally felt that the current approach works. Basic requirements for the use and adoption of IT tools and systems include adequate resources, stakeholder engagement, user-friendly interfaces, and interoperability between different systems. We proposed 16 actionable insights and recommendations that could be implemented to help improve the delivery of BP@home in NCL. These include standardising IT systems, improving patient engagement, providing adequate training and support, and promoting the benefits of remote monitoring. Conclusion: On balance, we recommend that NCL continues to deliver BP@home using the current standard IT offer that facilitates asynchronous engagement with patients (i.e., AccurX). Embedding a quality improvement approach to identify mechanisms to continually improve the BP@home offer in NCL is recommended. Clinical leadership could also review the evaluation findings of alternative tools currently being tested locally (e.g., pilot using Suvera across one PCN) to drive evidence-based commissioning decision as the BP@home initiative becomes even more embedded in routine general practice

    State strategies of governance in biomedical innovation: aligning conceptual approaches for understanding 'Rising Powers' in the global context

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>'Innovation' has become a policy focus in its own right in many states as they compete to position themselves in the emerging knowledge economies. Innovation in biomedicine is a global enterprise in which 'Rising Power' states figure prominently, and which undoubtedly will re-shape health systems and health economies globally. Scientific and technological innovation processes and policies raise difficult issues in the domains of science/technology, civil society, and the economic and healthcare marketplace. The production of knowledge in these fields is complex, uncertain, inter-disciplinary and inter-institutional, and subject to a continuing political struggle for advantage. As part of this struggle, a wide variety of issues - regulation, intellectual property, ethics, scientific boundaries, healthcare market formation - are raised and policy agendas negotiated.</p> <p>Methods</p> <p>A range of social science disciplines and approaches have conceptualised such innovation processes. Against a background of concepts such as the competition state and the developmental state, and national innovation systems, we give an overview of a range of approaches that have potential for advancing understanding of governance of global life science and biomedical innovation, with special reference to the 'Rising Powers', in order to examine convergences and divergences between them. Conceptual approaches that we focus on include those drawn from political science/political economy, sociology of technology; Innovation Studies and Science & Technology Studies. The paper is part of a project supported by the UK ESRC's Rising Powers programme.</p> <p>Results</p> <p>We show convergences and complementarities between the approaches discussed, and argue that the role of the national state itself has become relatively neglected in much of the relevant theorising.</p> <p>Conclusions</p> <p>We conclude that an approach is required that enables innovation and governance to be seen as 'co-producing' each other in a multi-level, global ecology of innovation, taking account of the particular, differing characteristics of different emerging scientific fields and technologies. We suggest key points to take account of in order in the future to move toward a satisfactory integrative conceptual framework, capable of better understanding the processes of the emergence, state steerage and transnational governance of innovative biomedical sectors in the Rising Powers and global context.</p

    Bridging the Global Divide in AI Regulation: A Proposal for a Contextual, Coherent, and Commensurable Framework

    Full text link
    This paper examines the current landscape of AI regulations, highlighting the divergent approaches being taken, and proposes an alternative contextual, coherent, and commensurable (3C) framework. The EU, Canada, South Korea, and Brazil follow a horizontal or lateral approach that postulates the homogeneity of AI systems, seeks to identify common causes of harm, and demands uniform human interventions. In contrast, the U.K., Israel, Switzerland, Japan, and China have pursued a context-specific or modular approach, tailoring regulations to the specific use cases of AI systems. The U.S. is reevaluating its strategy, with growing support for controlling existential risks associated with AI. Addressing such fragmentation of AI regulations is crucial to ensure the interoperability of AI. The present degree of proportionality, granularity, and foreseeability of the EU AI Act is not sufficient to garner consensus. The context-specific approach holds greater promises but requires further development in terms of details, coherency, and commensurability. To strike a balance, this paper proposes a hybrid 3C framework. To ensure contextuality, the framework categorizes AI into distinct types based on their usage and interaction with humans: autonomous, allocative, punitive, cognitive, and generative AI. To ensure coherency, each category is assigned specific regulatory objectives: safety for autonomous AI; fairness and explainability for allocative AI; accuracy and explainability for punitive AI; accuracy, robustness, and privacy for cognitive AI; and the mitigation of infringement and misuse for generative AI. To ensure commensurability, the framework promotes the adoption of international industry standards that convert principles into quantifiable metrics. In doing so, the framework is expected to foster international collaboration and standardization without imposing excessive compliance costs

    On-site customer analytics and reporting (OSCAR):a portable clinical data warehouse for the in-house linking of hospital and telehealth data

    Get PDF
    This document conveys the results of the On-Site Customer Analytics and Reporting (OSCAR) project. This nine-month project started on January 2014 and was conducted at Philips Research in the Chronic Disease Management group as part of the H2H Analytics Project. Philips has access to telehealth data from their Philips Motiva tele-monitoring and other services. Previous projects within Philips Re-search provided a data warehouse for Motiva data and a proof-of-concept (DACTyL) solution that demonstrated the linking of hospital and Motiva data and subsequent reporting. Severe limitations with the DACTyL solution resulted in the initiation of OSCAR. A very important one was the unwillingness of hospitals to share personal patient data outside their premises due to stringent privacy policies, while at the same time patient personal data is required in order to link the hospital data with the Motiva data. Equally important is the fact that DACTyL considered the use of only Motiva as a telehealth source and only a single input interface for the hospitals. OSCAR was initiated to propose a suitable architecture and develop a prototype solution, in contrast to the proof-of-concept DACTyL, with the twofold aim to overcome the limitations of DACTyL in order to be deployed in a real-life hospital environment and to expand the scope to an extensible solution that can be used in the future for multiple telehealth services and multiple hospital environments. In the course of the project, a software solution was designed and consequently deployed in the form of a virtual machine. The solution implements a data warehouse that links and hosts the collected hospital and telehealth data. Hospital data are collected with the use of a modular service oriented data collection component by exposing web services described in WSDL that accept configurable XML data messages. ETL processes propagate the data, link, and load it on the OS-CAR data warehouse. Automated reporting is achieved using dash-boards that provide insight into the data stored in the data warehouse. Furthermore, the linked data is available for export to Philips Re-search in de-identified format

    A study assessing the characteristics of big data environments that predict high research impact: application of qualitative and quantitative methods

    Full text link
    BACKGROUND: Big data offers new opportunities to enhance healthcare practice. While researchers have shown increasing interest to use them, little is known about what drives research impact. We explored predictors of research impact, across three major sources of healthcare big data derived from the government and the private sector. METHODS: This study was based on a mixed methods approach. Using quantitative analysis, we first clustered peer-reviewed original research that used data from government sources derived through the Veterans Health Administration (VHA), and private sources of data from IBM MarketScan and Optum, using social network analysis. We analyzed a battery of research impact measures as a function of the data sources. Other main predictors were topic clusters and authors’ social influence. Additionally, we conducted key informant interviews (KII) with a purposive sample of high impact researchers who have knowledge of the data. We then compiled findings of KIIs into two case studies to provide a rich understanding of drivers of research impact. RESULTS: Analysis of 1,907 peer-reviewed publications using VHA, IBM MarketScan and Optum found that the overall research enterprise was highly dynamic and growing over time. With less than 4 years of observation, research productivity, use of machine learning (ML), natural language processing (NLP), and the Journal Impact Factor showed substantial growth. Studies that used ML and NLP, however, showed limited visibility. After adjustments, VHA studies had generally higher impact (10% and 27% higher annualized Google citation rates) compared to MarketScan and Optum (p<0.001 for both). Analysis of co-authorship networks showed that no single social actor, either a community of scientists or institutions, was dominating. Other key opportunities to achieve high impact based on KIIs include methodological innovations, under-studied populations and predictive modeling based on rich clinical data. CONCLUSIONS: Big data for purposes of research analytics has grown within the three data sources studied between 2013 and 2016. Despite important challenges, the research community is reacting favorably to the opportunities offered both by big data and advanced analytic methods. Big data may be a logical and cost-efficient choice to emulate research initiatives where RCTs are not possible

    Prescribing Exploitation

    Get PDF

    Comparison of european health related ICT projects

    Get PDF
    Introdução: No mundo globalizado dos nossos dias, é expectável que os profissionais de saúde prestem os seus serviços a pacientes estrangeiros nalgum ponto das suas carreiras. A diferença de idiomas, sistemas de saúde e infraestruturas são barreiras para uma prestação de cuidados semelhantes aos que os cidadãos conhecem nos seus países de origem. Novas soluções interoperáveis para a partilha de informação clínica a níveis transfronteiriços figuram, por isso, na lista das prioridades digitais da agenda política dos Estados-Membros da União Europeia (UE) (1). A adoção da Diretiva 2011/24/UE do Parlamento Europeu e do Conselho, de Março de 2011, sobre os Direitos dos Pacientes nos cuidados de saúde transfronteiriços, representa o auge da liberdade dos cidadãos para receberem cuidados de saúde noutros Estados-Membros da União Europeia, com qualidade e segurança (2). Com o objetivo de facilitar ‘a prestação de serviços públicos Europeus, promovendo a interoperabilidade transfronteiriça e inter-sectorial’ (7), a European Interoperability Framework (EIF) estabelece uma série de recomendações que promovem várias políticas e iniciativas na UE, ao mesmo tempo que define quatro dimensões para a interoperabilidade: legal, organizacional, semântica e técnica. Objetivo: O objetivo do presente estudo é abordar o desafio da transição de soluções-piloto para uma infraestrutura transfronteiriça de larga-escala, que apoie os Estados-Membros da União Europeia na prestação de serviços públicos, especialmente no setor de saúde. Metodologias: Esta revisão aborda, empiricamente, informação publicada e não-publicada sobre eHealth e sistemas de partilha de dados clínicos, resumindo e correlacionando as conclusões mais importantes de diferentes fontes. É particularmente centrada na análise transversal de quatro projetos Europeus: epSOS, eSENS, Trillium Bridge e EXPAND. Resultados: As Diretivas de Proteção de Dados 95/46/CE e dos Direitos dos Pacientes nos cuidados de saúde transfronteiriços 2011/24/UE são os principais instrumentos legais abordados em todas as iniciativas, não obstante da existência de legislações nacionais. Métodos de trabalho estabelecidos no âmbito das organizações de saúde necessitam de ser adaptados e otimizados, de acordo com as novas arquiteturas de comunicação, mas serão os usuários os principais responsáveis pela sua integração nos seus próprios sistemas, procedimentos e culturas de trabalho. A interpretação universal de dados em saúde pode ser alcançada com terminologias mutuamente aceites, sistemas de codificação e criação de meta-informação, como o mapeamento da Health Level Seven Release 2 (HL 7 R2). O padrão de comunicação Clinical Document Architecture (CDA) estabelece uma estrutura consistente entre sistemas de informação clínica utilizados na Europa. Conclusões: Ainda existem inúmeras barreiras para uma prestação transeuropeia eficaz de serviços públicos. Apesar de um certo nível de complexidade que ainda marca os sistemas de informação em saúde, são várias as vantagens da sua utilização: o acesso rápido e seguro a dados de saúde relevantes para as decisões clínicas, confidencialidade dos mesmos, centralização e organização de acordo com classificações médicas internacionais, bem como a promoção de controlo estatístico e otimização de desempenho (12). A interoperabilidade não é uma finalidade ou uma questão de presença ou ausência, é antes um processo que poderá ser melhorado ao longo do tempo (59). Mais estudos serão necessários para entender como poderemos melhorar os nossos sistemas de informação, para uma partilha sustentável de dados cada vez mais complexos, como a informação em saúde.Introduction: With the globalized world of our days, health professionals are expected to provide their services to foreign patients at some point in their careers. Different languages, health systems and infrastructures are barriers to a sound provision of health care as people have been used to in their home countries. New interoperable solutions for the exchange of clinical data at cross-border levels are now listed as new digital priorities in the political agenda of the European Union (EU) Member States (MS) (1). The adoption of the Directive 2011/24/EU of the European Parliament and the Council of March 2011 on Patient’s Rights in cross-border health care was the pinnacle to assure citizen’s freedom to receive health care in another EU Member State, with quality and safety (2). With the purpose of facilitating ‘the delivery of European public services by fostering cross-border and cross-sectoral interoperability’ (7), the European Interoperability Framework (EIF) establishes a series of recommendations that promote several EU policy initiatives, while defining four dimensions for interoperability: legal, organizational, semantic, and technical. Objective: The purpose of the present review is to address the challenge of stirring from point-solution pilots to a large-scale deployment of cross-border facilities that support EU Member States in delivering public services, especially in health sector. Methodologies: This study empirically addresses published and unpublished information in eHealth and clinical data exchange systems, summarizing and correlating the most important conclusions of different sources. Particularly, it is centered in a transversal analysis of four different European projects focused on providing solutions for cross-border health care services: epSOS, eSENS, Trillium Bridge and EXPAND. Results: The Data Protection Directive 95/46/EC and the Patient’s Rights in cross-border health care Directive 2011/24/EU are the major legal instruments to comply with by all initiatives, notwithstanding the existence of national legislations. Established workflows within heath organizations need to be adapted and optimized according to new communication architectures, but users are ultimately responsible for integrating them in their own systems, procedures and working cultures. A universal interpretation of health data can be achieved with mutually accepted terminologies, coding systems and creation of metadata, such as Health Level Seven Release 2 (HL 7 R2) mapping. The Clinical Document Architecture (CDA) communication standard establishes structure consistency among health IT systems used in Europe. Conclusions: There are still numerous barriers in effective delivery of public services in a pan-European setting. Although a certain level of complexity is still present in health information systems, several advantages can still be highlighted such as rapid and secure access to health data relevant for the decision-making at the care point, confidentiality promotion, centralization and structuring according with medical standards and the promotion of statistical control and performance optimization (12). Interoperability is not an ending or a question of being present or absent, but rather a process that can be improved over time (59). More studies are needed to understand how we can better connect our IT systems towards a sustainable exchange route of richer and even more intricate data, as sensitive as health information
    corecore