Article type
Abstract
"Background: In May 2022, Japan's first evidence portal, the EBPM Database was launched. So far the database compiles over 60 evidence reviews and has gathered significant attention, serving thousands of users. It draws inspiration from projects like the What Works Centre, Campbell Collaboration, and 3ie, focusing on summarizing research findings and ensuring their accessibility to government officials in both central and local governments through an intuitive user interface.
Objectives: The project aimed to enhance the accessibility and utility of evidence for policy-making in Japan. It sought to address the challenges of evidence-based policy-making (EBPM) by providing a comprehensive, user-friendly repository of research findings. Moreover, the project aimed to foster wider community engagement in evidence review and contribution, thereby advancing the quality and depth of evidence available for policy decisions.
Methods: The database follows The Maryland Scientific Methods Scale (SMS) for assessing evidence strength, while also incorporating advanced economic methodologies to address complex interventions such as structural estimation. Its development emphasizes open collaboration, with the review process and source code made available on GitHub, encouraging public and expert participation. The project also explores innovative approaches to content generation and review, including the use of generative AI to streamline processes.
Results: Since its launch, the EBPM Database has significantly impacted the EBPM landscape in Japan. For example, the database is listed as a useful tool. It has introduced a unique framework for evaluating and categorizing research outcomes, contributing to more nuanced understanding and application of evidence in policy-making. However, there are still challenges for scaling for society including the coverage, engagement of both evidence providers and users.
Conclusions: Addressing the challenges requires securing additional resources, leveraging technology like generative AI to lower review costs, clarifying the review process for greater participation, and enhancing engagement with governmental bodies.
Relevance and Importance: This project is directly relevant to the accessibility of evidence, crucial for informing policy decisions.
Public/Consumer Involvement: The open access nature of the project and the encouragement of broad participation through GitHub suggest a commitment to inclusivity and collaborative effort, aligning with the ethos of co-production in evidence generation."
Objectives: The project aimed to enhance the accessibility and utility of evidence for policy-making in Japan. It sought to address the challenges of evidence-based policy-making (EBPM) by providing a comprehensive, user-friendly repository of research findings. Moreover, the project aimed to foster wider community engagement in evidence review and contribution, thereby advancing the quality and depth of evidence available for policy decisions.
Methods: The database follows The Maryland Scientific Methods Scale (SMS) for assessing evidence strength, while also incorporating advanced economic methodologies to address complex interventions such as structural estimation. Its development emphasizes open collaboration, with the review process and source code made available on GitHub, encouraging public and expert participation. The project also explores innovative approaches to content generation and review, including the use of generative AI to streamline processes.
Results: Since its launch, the EBPM Database has significantly impacted the EBPM landscape in Japan. For example, the database is listed as a useful tool. It has introduced a unique framework for evaluating and categorizing research outcomes, contributing to more nuanced understanding and application of evidence in policy-making. However, there are still challenges for scaling for society including the coverage, engagement of both evidence providers and users.
Conclusions: Addressing the challenges requires securing additional resources, leveraging technology like generative AI to lower review costs, clarifying the review process for greater participation, and enhancing engagement with governmental bodies.
Relevance and Importance: This project is directly relevant to the accessibility of evidence, crucial for informing policy decisions.
Public/Consumer Involvement: The open access nature of the project and the encouragement of broad participation through GitHub suggest a commitment to inclusivity and collaborative effort, aligning with the ethos of co-production in evidence generation."