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The Structured Process to Identify Fit-for-purpose Data (SPIFD): A data feasibility assessment framework.

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To complement real-world evidence guidelines, the 2019 SPACE framework (A Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real-world Evidence) elucidated a process for designing… Click to show full abstract

To complement real-world evidence guidelines, the 2019 SPACE framework (A Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real-world Evidence) elucidated a process for designing valid and transparent real-world studies. As an extension to SPACE, here we provide a structured framework for conducting feasibility assessments -- a step-by-step guide to identify decision grade, fit-for-purpose data, which complements the FDA's framework for a real-world evidence program. The process was informed by our collective experience conducting systematic feasibility assessments of existing data sources for pharmacoepidemiology studies to support regulatory decisions. Used with the SPACE framework, SPIFD provides a systematic process for conducting feasibility assessments to determine if a data source is fit for decision-making, helping ensure justification and transparency throughout study development, from articulation of a specific and meaningful research question to identification of fit-for-purpose data and study design.

Keywords: real world; framework; fit purpose; process; purpose data; feasibility

Journal Title: Clinical pharmacology and therapeutics
Year Published: 2021

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