Reflections on defining a standard for computable expression of scientific knowledge: What teach us Yoda can.

Science advances at a slow pace but can be accelerated with a standard for computable expression of scientific knowledge, more precisely a technical standard for electronic data exchange of machine-interpretable data expressing scientific knowledge. Efforts to achieve this vision include Evidence-Based Medicine on Fast Healthcare Interoperability Resources (EBMonFHIR), COVID-19 Knowledge Accelerator (COKA), Computable Publishing LLC, Scientific Knowledge Accelerator Foundation, and the Fast Evidence Interoperability Resources (FEvIR) Platform. The vision for communicating scientific research results to be instantly found, viewed, sent, received, and incorporated into thousands of system is a Just-in-time Evidence Dissemination and Integration (JEDI) vision. Reflections on JEDI teachings in a fun way helps explain the focus on the "Resource" to make science computable, how a precise specification of evidence changes perspectives, the need to reset standard terminologies, the inclusive nature of efforts to achieve the vision, and the critical demand to realize the vision.

Making science computable: Developing code systems for statistics, study design, and risk of bias.

The COVID-19 crisis led a group of scientific and informatics experts to accelerate development of an infrastructure for electronic data exchange for the identification, processing, and reporting of scientific findings. The Fast Healthcare Interoperability Resources (FHIR®) standard which is overcoming the interoperability problems in health information exchange was extended to evidence-based medicine (EBM) knowledge with the EBMonFHIR project. A 13-step Code System Development Protocol was created in September 2020 to support global development of terminologies for exchange of scientific evidence. For Step 1, we assembled expert working groups with 55 people from 26 countries by October 2020. For Step 2, we identified 23 commonly used tools and systems for which the first version of code systems will be developed. For Step 3, a total of 368 non-redundant concepts were drafted to become display terms for four code systems (Statistic Type, Statistic Model, Study Design, Risk of Bias). Steps 4 through 13 will guide ongoing development and maintenance of these terminologies for scientific exchange. When completed, the code systems will facilitate identifying, processing, and reporting research results and the reliability of those results. More efficient and detailed scientific communication will reduce cost and burden and improve health outcomes, quality of life, and patient, caregiver, and healthcare professional satisfaction. We hope the achievements reached thus far will outlive COVID-19 and provide an infrastructure to make science computable for future generations. Anyone may join the effort at https://www.gps.health/covid19_knowledge_accelerator.html.

Developing trustworthy recommendations as part of an urgent response (1-2 weeks): a GRADE concept paper.

OBJECTIVES: The aim of this study is to propose an approach for developing trustworthy recommendations as part of urgent responses (1-2 week) in the clinical, public health, and health systems fields. STUDY DESIGN AND SETTING: We conducted a review of the literature, outlined a draft approach, refined the concept through iterative discussions, a workshop by the Grading of Recommendations Assessment, Development and Evaluation Rapid Guidelines project group, and obtained feedback from the larger Grading of Recommendations Assessment, Development and Evaluation working group. RESULTS: A request for developing recommendations within 2 week is the usual trigger for an urgent response. Although the approach builds on the general principles of trustworthy guideline development, we highlight the following steps: (1) assess the level of urgency; (2) assess feasibility; (3) set up the organizational logistics; (4) specify the question(s); (5) collect the information needed; (6) assess the adequacy of identified information; (7) develop the recommendations using one of the 4 potential approaches: adopt existing recommendations, adapt existing recommendations, develop new recommendations using existing adequate systematic review, or develop new recommendations using expert panel input; and (8) consider an updating plan. CONCLUSION: An urgent response for developing recommendations requires building a cohesive, skilled, and highly motivated multidisciplinary team with the necessary clinical, scientific, and methodological expertise; adapting to shifting needs; complying with the principles of transparency; and properly managing conflicts of interest.