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The Analysis Results Standard (ARS) Model has several possible implementations including leveraging analysis results metadata to aid in automation as well as representing analysis results as data in a dataset structure. The creation of an ARS technical specification could be used support automation, traceability, and the creation of data displays. An analysis results dataset could support reuse and reproducibility of results data. The following is an example of how the ARS Model could be used in a modernized workflow that shifts the focus from retrospective reporting to prospective planning (Figure 2).
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First, end an end-users generate the could use the ARS Model to guide in the generation of a technical specification prior to generating a display, rather than after the display has been created. This approach will allow for better planning and standardization of the analysis process, resulting in more consistent and traceable reporting.The proposed workflow (Figure 2) involves several steps. First, the end-user will develop a technical specification, which will The technical specification could include metadata about the statistical methods, data sources, and displays to be generated (Figure 2, Use Case 1). Once the technical specification has been developed, the end-user will can use it to generate an analysis results dataset, which will contain contains the results data needed to generate the display (Figure 2, Use Case 2). The analysis results dataset will could be designed to support reuse and reproducibility of the results data, enabling more efficient and effective analysis reporting.
Finally, the machine-readable analysis results dataset serves as the ‘single source of truth’ capturing the analysis results metadata and results data in a standardized format. This dataset can then be used to generate displays for multiple reporting purposes, such as traditional analysis reporting for the clinical study report (CSR), in-text tables for the CSR, safety reporting, meta-analyses, dynamic applications, ClinicalTrials.gov, publications, and presentations. This streamlined approach ensures consistency and accuracy in the generation of displays across various deliverables, making it more efficient and reliable for reporting and communication of analysis results.
- Open-source tools for designing, specifying, building, and generating analysis results data
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Overall, this new workflow will would enable end-users to generate analysis results metadata prospectively, with greater standardization, consistency, and traceability of analysis results reporting, enabling better decision-making and regulatory submissions. By shifting Shifting the focus from retrospective reporting to prospective planning , we believe that this approach will would help to address many of the current limitations of analysis results reporting and support the development of more efficient and effective analysis standards.
Figure 2: Workflow with Future Extensions and Use Cases
Use of LinkML for the development of the ARS Logical Model
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