ABSTRACTS CAN BE SUBMITTED ONLY THROUGH THE ABSTRACT SUBMISSION FORM, BY THE 1st MAY 2025.
The Scientific Board welcomes abstracts from across the evidence ecosystem, inviting submissions related to this year’s theme of artificial intelligence (AI) and digital transformation, as well as any topic that strengthens the foundation of evidence-based healthcare.
Evidence generation
We encourage submissions on experiences or methodologies that enhance research value, minimize waste, and maintain research integrity in line with REWARD recommendations. Submissions addressing technological advancements and AI integration in healthcare are especially welcome.
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Increase research relevance
- Involving clinicians, patients and policy-makers to define priority and design primary research
- Using systematic reviews to justify and inform research design
- Designing studies to capture real-world evidence (e.g., pragmatic trials, big data applications)
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Improve research design, conduct and analysis
- Innovations such as platform trial designs and target trial emulation
- Implementing steps to minimize biases
- Enhancing the reproducibility of preliminary research results
- Utilizing AI-driven tools to improve study design, reduce human error, and automate data collection and analysis
- Addressing equity in AI applications by ensuring diverse representation in datasets and fairness in model outputs
- Ensuring data privacy and security in AI-driven research
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Streamlining research regulation and delivery
- Conducting research efficiently with a focus on regulatory compliance
- Reusing and repurposing data for further research
- Promoting open science and research integrity
- Leveraging digital solutions to expedite regulatory approvals and ensure compliance
- Using AI to detect biases or inconsistencies in research reporting
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Enhancing the accessibility and completeness of research reports
- Minimizing missing reporting bias
- Reporting studies with both positive and negative outcomes
- Adhering to established guidelines for research reporting
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Produce unbiased and usable research reports
- Providing clear descriptions of study interventions
- Reducing outcome reporting bias
- Interpreting research findings in the context of existing evidence
- Renewing reward and recognition systems for researchers
- Ensuring AI transparency, enabling researchers and stakeholders to understand AI models' reasoning
- Mitigating AI biases by incorporating fairness checks and validation processes to prevent disparities
Evidence synthesis
We invite submissions addressing methodological challenges in systematic reviews, clinical practice guidelines (CPGs), and health technology assessments (HTA), with a focus on methods and tools that enhance evidence synthesis in a digital age.
- Meeting the rapid needs of health decision-makers with rigorous methodologies, including rapid review techniques
- Advanced evidence synthesis methods
- Using AI and machine learning to search, retrieve, and evaluate evidence
- Improving the conduct and reporting of evidence syntheses
- Living systematic reviews and guidelines
- Assessment tools for evidence synthesis
- AI tools for updating clinical guidelines and HTA reports
- Publishing and updating evidence synthesis in the digital era
- Involving consumers and patients in evidence synthesis
- Managing conflicts of interest in evidence synthesis
Evidence translation
We welcome submissions on methodologies and experiences that facilitate the translation of evidence into healthcare decisions and communication, especially those that leverage digital tools and AI to bridge evidence with real-world applications.
- Prioritizing evidence translation in a digital-first landscape
- Adapting clinical practice guidelines to local contexts
- Applying machine learning and AI to evidence translation
- Disseminating and implementing care pathways with digital solutions
- Designing research to assess dissemination and implementation impact
- Strategies for evaluating dissemination and implementation effectiveness
- Capacity-building for evidence dissemination and implementation
- Reducing overuse and underuse in healthcare
- Encouraging evidence-based policymaking and advocacy/li>
- Involving patients and the public in healthcare decisions
- Ensuring interpretability of AI-driven decision support systems for clinician trust and effective use
- Using digital platforms to monitor and report on implementation strategies' effectiveness
Evidence teaching and communication
We encourage submissions on innovations in teaching and communicating evidence-based healthcare (EBHC) to diverse audiences, from students to healthcare professionals, as well as strategies to promote evidence literacy.
- Teaching EBHC with digital tools and AI-assisted platforms
- Effective communication strategies to counter misinformation and improve understanding of evidence-based practices
- Digital resources for EBHC learning
- AI-based tools for identifying and counteracting misinformation in healthcare
- Techniques for small and large group learning
- AI-supported virtual learning environments for diverse groups
- Methods for communicating key EBHC concepts
- Tools for promoting evidence literacy and shared decision-making, including patient decision aids and social media
One Health and Environmental Health
Exploring the interconnectedness of human, animal, and environmental health, emphasizing the holistic One Health approach to tackle current and future challenges. We welcome contributions that address the integration of evidence from multiple domains to improve health outcomes for people, animals, and the environment.
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Integrating One Health evidence
- Generating evidence that addresses the interconnections between human, animal, and environmental health
- Applying systematic approaches to understand the impact of environmental factors on health outcomes
- Leveraging AI to analyze complex data sets that include human, animal, and environmental health indicators
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Environmental health and sustainability
- Evaluating the impact of environmental exposures on public health
- Studying the effects of climate change on health and developing adaptation strategies
- Using digital tools to monitor and predict environmental health risks
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Cross-sector collaboration
- Encouraging collaboration between healthcare, veterinary, and environmental science sectors;
- Developing frameworks to implement One Health approaches at local, national, and international levels;
- Using AI and digital platforms to facilitate communication and data sharing across sectors
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Promoting resilience and prevention
- Identifying preventive measures to reduce the risk of zoonotic diseases and environmental health hazards;
- Using AI models to predict disease outbreaks and inform public health interventions;
- Building community resilience through education and awareness initiatives focused on the One Health approach
Publication of Accepted Abstracts
We are pleased to announce that all accepted abstracts that will be presented at the 11th EBHC International Conference, including those presented as oral long presentations, oral short presentations, and oral flash presentations, will be published in the BMJ Evidence-Based Medicine starting from November 2026. This represents an excellent opportunity for contributors to share their work with a wider audience, ensuring their findings play a significant role in advancing the dialogue within the evidence-based healthcare community.
ABSTRACTS TERMS AND CONDITIONS
Abstracts must be in english and have not appeared in full print before the conference.
Abstracts should be no longer than 5.000 characters and cannot include tables and figures. Any abbreviations should be defined where first mentioned and the abstract should be structured with the following subheadings:
- Background
- Aims
- Methods
- Results
- Limits
- Conclusions