Daniel Otzoy Garcia

💡 New Publication on Health Complexity: Using Causal Loop Diagrams to Address Complex Public Health Challenges, led by Jeroen Uleman and Naja Hulvej Rod from our Center, and in collaboration with Karien Stronks, Harry Rutter, and Onyebuchi Arah. 🏥 In this paper released in the International Journal of Epidemiology, the authors provide a comprehensive introduction to causal loop diagrams in the context of public health, including a step-by-step guide for developing these diagrams. They also demonstrate their application with a case study on the feedback loop between sleep disturbances and depressive symptoms. 📖 Read the full paper here: https://lnkd.in/dt-NhnXZ

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This looked like a Kumu powered visualization to us, and sure enough, it looks like you've recommended our software for visualizing Causal Loop Diagrams in your supplementary materials! It's an honor to be a part of a researcher's toolkit for working in complex public health challenges! #causalloopdiagrams #clds #dataviz #complexadaptivesystems

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📰 Discover a new publication on using Causal Loop Diagrams (#CLDs) to address complex public health challenges such as health inequality. 📰 CLDs, drawn from complex systems science, visualize the interconnectedness of variables across scales, providing a framework for identifying feedback loops and potential intervention points. The paper includes a step-by-step guide to developing CLDs, with a case study on the feedback loop between sleep disturbances and depressive symptoms. At DARE Foundation - Digital Lifelong Prevention, we believe that innovative tools like CLDs are essential for designing preventive measures that address the root causes of health issues. By identifying and analyzing these complex interactions, we can create more targeted and effective strategies for improving public health. Discover more about this innovative approach and its implications for prevention: https://lnkd.in/drQXsc6u #FondazioneDARE #DAREFoundation #DigitalPrevention #Prevenzionedigitale #Digitalhealth  #CLD #PublicHealth #HealthInequality

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#ArtificialIntelligence #AI in #healthcare 🌐 The OECD - OCDE published a brief document with the aim to highlight the main opportunities for AI to enhance health outcomes, identify the crucial risks associated with its implementation in healthcare, and suggest practical policy measures to ensure the responsible use of AI that upholds human rights and enhances health outcomes. The adoption of AI in health care is growing rapidly, promising significant benefits but also posing serious risks. Key recent initiatives have focused on ensuring AI's safe and ethical use. The OECD's 2019 AI Principles aim to address risks such as job displacement, inequities, privacy breaches, and harmful use of AI. Major events and reports in late 2023 emphasize the importance of safe AI implementation. AI has the potential to greatly enhance health care by addressing workforce shortages, public health threats, and the complexities of aging populations and chronic conditions. It can improve health professionals' efficiency and make health systems more patient-centered. However, failure to implement AI principles can lead to increased inequities, privacy risks, slow scientific progress, and diminished public trust. Current AI applications in health often use local data and serve limited populations, risking fragmentation and inequality in AI benefits. Strong, coordinated policies and robust governance are essential for maximizing AI’s benefits while minimizing risks. Common principles and frameworks should guide the development and deployment of AI in health care to ensure equitable and human-rights-respecting outcomes. Do you wish to place your AI enabled #medicaldevices on the #EuropeanMarket or #Swissmarket? We support you with our hands-on services to secure your #compliance and #regulatory strategy. Contact us ☞ [email protected] #AIinHealthcare #Collaboration #GlobalHealth #MedTech #publichealth #Innovation #Digitalhealth #HealthTech #regulatorycompliance #machinelearning #MLMD #EU #Europe #Switzerland #technology #wearables #readiness #riskmanagement #ehealth

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AI and HTA medical devices "The adaptation of the HTA process through a methodological framework for AI-based medical devices enhances the comparability of results across different evaluations and jurisdictions. By defining the necessary expertise, the framework supports the development of a skilled workforce capable of conducting robust and reliable HTAs of AI-based medical devices. A comprehensive adapted HTA framework for AI-based medical devices can provide valuable insights into the effectiveness, cost-effectiveness, and societal impact of AI-based medical devices, guiding their responsible implementation and maximizing their benefits for patients and health care systems." https://lnkd.in/d659ynYF

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Methods for Health Economic Evaluations  To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting: https://lnkd.in/dqTpcvTM.

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A Guide to the Fundamentals of Economic Evaluation in Public Health #admin To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting https://lnkd.in/d3mMU6ZE.

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A new paper by Andres Vecino-Ortiz of Department of International Health, Johns Hopkins Bloomberg School of Public Health and colleagues from IMEK Research Center in Marketing & Development and Pontificia Universidad Javeriana, with funding from Inter-American Development Bank, looks at the feasibility of using mobile phone surveys to conduct syndromic surveillance (where individuals can self-report symptoms related to infection) for COVID-19 in Colombia.    In emergency situations such as the COVID-19 pandemic, mobile phone surveys can be used as a low-risk and cost-effective method to detect outbreaks. Read more: https://lnkd.in/eyYSErUZ.

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📢 Bring Epidemiological Data to Life Join Dr. George Paul for an engaging practical session on analyzing and interpreting data from different study designs.  Sharpen your skills in turning raw data into actionable insights for public health.  📺 Watch now on our YouTube channel: https://lnkd.in/dgZXf32w  #Epidemiology #DataAnalysis #PublicHealth #CEMA #PracticalSkills  

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Interesting reading for #digitalhealth companies. "Methods for evaluating the efficacy and effectiveness of direct-to-consumer mobile health apps: a scoping review" https://lnkd.in/ev8js5zT This review is the first attempt to summarise the financial stages, study characteristics, and methods for evaluating mobile health apps (#mhealth) The authors searched for published studies that looked at efficacy, effectiveness or cost-effectiveness of health apps. They limited their analysis to current/popular apps; those downloadable on google play store and with >50k downloads. The review offers answers insights into -       What stage/sort of companies are conducting/publishing research ? -       What types of apps are they evaluating? -       Who is conducting this research? -       What are the study designs? The authors discuss some limitations of the typical studies out there including -       Short durations of follow-up -       Comparisons to waiting list control rather than active control groups -       Lack of diversity in study participants -       Lack of standardisation of measures They conclude we need ⭐Robust academic-industry partnerships ⭐Streamlining and simplifying of current processes to avoid exerting too much pressure on innovators who can’t afford full-scale evaluation ⭐How-to guidance- for example, via the link in comments Authors: Carley Prentice, Kimberley Peven,  Liudmila Zhaunova, Vaaruni Nayak, Tara Radovic, Anna Klepchukova, Henry Potts & Sonia Ponzo 

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Health Economic Evaluation #admin To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting https://lnkd.in/d3mMU6ZE.

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📢 Call for Papers: Governance of Health Data for AI Innovation After a successful track at the #DataforPolicy2024 Conference, we invite all authors working on #AI and data for healthcare to consider submitting their work for this special collection to be featured in the open-access journal Data & Policy (Cambridge University Press & Assessment) in 2025. We invite full-paper submissions from academia, governmental organizations and the private sector addressing the following themes (inspirational rather than exhaustive): ✅ Governance frameworks for accessing health data for AI innovation - clinical, administrative and health-related data. ✅ Ethical frameworks guiding the private sector’s use of health-related data to create private value and drive innovation. ✅ Ethical considerations for governmental institutions in using health data to create public value through AI-driven initiatives. ✅ Addressing infrastructural, legal, and cultural challenges in providing health data access for AI innovation, especially in the Global South. ✅ Digitisation and governance of Health data generated by government-run and public healthcare services. ✅ From e-Health to the “appification” of Health: Challenges in Managing Data from Health and Wellness Apps ✅ Increasing difficulties in accessing health data due to issues such as intellectual property, technical restrictions, and concerns about how AI is used. ✅ The lack of global standards and compatibility between different health data systems. ✅ The challenges that come with the shift in how health knowledge is created: moving from the traditional health-related research model of clinical trials to one that relies on analyzing large sets of health data ✅ Collaborations between public institutions and tech giants to advance health research, and the complications these partnerships bring. 📅 Deadline for submissions: 17 February 2025 ℹ️ How to submit: https://lnkd.in/duBkNTP9 Editors: Renan Gadoni Canaan & Teresa Scassa (University of Ottawa) #ArtificialIntelligence, #AI, #Health, #Data, #DataGovernance, #Bias, #HealthcareSystems

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On May 14 the Data.FI Project team in #Guatemala facilitated a data review meeting that brought together a wide range of governmental and implementing partners—including the National STI/HIV Program, the Epidemiology Unit, the Vice Ministry of Hospitals, the Guatemalan Social Security Institute, and the Executive Secretariat of the Commission of Ministers of Health of Central America.  This group convened as part of a technical working group (TWG) to analyze changes in several key HIV indicators, such as screening, number of new positive cases, and linkage of people to Comprehensive Care Units. The analysis included disaggregations by age, gender, and ethnic group, and was presented by the Epidemiology Unit.  After looking over the latest data, the TWG agreed on actions at the national level to close gaps or shortfalls, notably to increase coordination with the Comprehensive Care Units to continue cleaning data, and to improve coordination between Hospitals and the Directorate of Integrated Health Services Networks to improve the planning and provision of services. Data.FI's support for the work carried out by the HIV TWG is important because it fosters space for collaboration, stronger communication, and technical knowledge exchange at the national level. This has direct benefits for the people of Guatemala, as health officials make decisions that translate into better data quality, better planning, and better provision of HIV prevention, care, and treatment services. #USAID #PEPFAR #CentralAmerica #HIV #technicalworkinggroups #datareview #datause

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GREI Collaborative Webinar: The hows and whys of sharing data in generalist repositories 💡 📈 Register now: https://lnkd.in/eWvdStha Join us on October 29 for a webinar presented by the repositories participating in the The National Institutes of Health Generalist Repository Ecosystem Initiative (GREI) (Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo). The webinar will provide an overview of these repositories and guidance on best practices for sharing and discovering data in them. The presenters will also highlight real world examples of NIH-funded research published in the GREI repositories. Key takeaways from the session include: ✅ Overview of common & unique features of generalist repositories ✅ Discussion of when to share data in generalist repositories ✅ Guidance on generalist repository data sharing & discovery best practices ✅ Review of real world examples of NIH-funded research shared in generalist repositories The National Institutes of Health NIH Office of Data Science Strategy Digital Science

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Continuing our coverage of the excellent ISPOR—The Professional Society for Health Economics and Outcomes Research 2024 conference, here we Deep Dive into the session, ‘Targeted learning for #causalinference using #realworlddata.’ Suzanne M. (Medlior Health Outcomes Research Ltd.) was joined John Paul Ekwaru (Medlior), Mark van der Laan (University of California, Berkeley) and Stephen J. Duffield (NICE - National Institute for Health and Care Excellence). Read at The Evidence Base® #heor #healtheconomics #rwe #rwd #realworldevidence #healthdata #ISPORAnnual #artificialintelligence #AI #ML #machinelearning #datascience #HTA #healthtechnologyassessment

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