50,578 research outputs found

    Evaluation of patient perception towards dynamic health data sharing using blockchain based digital consent with the Dovetail digital consent application : a cross sectional exploratory study

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    Background New patient-centric integrated care models are enabled by the capability to exchange the patient’s data amongst stakeholders, who each specialise in different aspects of the patient’s care. This requires a robust, trusted and flexible mechanism for patients to offer consent to share their data. Furthermore, new IT technologies make it easier to give patients more control over their data, including the right to revoke consent. These characteristics challenge the traditional paper-based, single-organisation-led consent process. The Dovetail digital consent application uses a mobile application and blockchain based infrastructure to offer this capability, as part of a pilot allowing patients to have their data shared amongst digital tools, empowering patients to manage their condition within an integrated care setting. Objective To evaluate patient perceptions towards existing consent processes, and the Dovetail blockchain based digital consent application as a means to manage data sharing in the context of diabetes care. Method Patients with diabetes at a General Practitioner practice were recruited. Data were collected using focus groups and questionnaires. Thematic analysis of the focus group transcripts and descriptive statistics of the questionnaires was performed. Results There was a lack of understanding of existing consent processes in place, and many patients did not have any recollection of having previously given consent. The digital consent application received favourable feedback, with patients recognising the value of the capability offered by the application. Patients overwhelmingly favoured the digital consent application over existing practice. Conclusions Digital consent was received favourably, with patients recognising that it addresses the main limitations of the current process. Feedback on potential improvements was received. Future work includes confirmation of results in a broader demographic sample and across multiple conditions

    Developing Predictive Molecular Maps of Human Disease through Community-based Modeling

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    The failure of biology to identify the molecular causes of disease has led to disappointment in the rate of development of new medicines. By combining the power of community-based modeling with broad access to large datasets on a platform that promotes reproducible analyses we can work towards more predictive molecular maps that can deliver better therapeutics

    Working Together Toward Better Health Outcomes

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    Healthcare organizations and community-based organizations (CBOs) that provide human services are partnering in shared pursuit of better health outcomes. The Partnership for Healthy Outcomes – Nonprofit Finance Fund (NFF), the Center for Health Care Strategies (CHCS), and the Alliance for Strong Families and Communities (Alliance), with support from the Robert Wood Johnson Foundation (RWJF) – set out to capture and analyze the lessons emerging in this dynamic space. Information from more than 200 partnerships serving all 50 US states provide important lessons from, and for, partnerships that hope to improve access to care, address health inequities, and make progress on social issues like food, education, and housing
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