The Structured Process to Identify Fit-For-Purpose Data: A Data Feasibility Assessment Framework.
Clin Pharmacol Ther
; 111(1): 122-134, 2022 01.
Article
in English
| MEDLINE | ID: covidwho-1706461
ABSTRACT
To complement real-world evidence (RWE) guidelines, the 2019 Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real-world Evidence (SPACE) framework 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 United States Food and Drug Administration (FDA)'s framework for a RWE 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, the Structured Process to Identify Fit-For-Purpose Data (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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Feasibility Studies
/
Data Collection
Type of study:
Experimental Studies
/
Prognostic study
/
Randomized controlled trials
/
Systematic review/Meta Analysis
Limits:
Humans
Language:
English
Journal:
Clin Pharmacol Ther
Year:
2022
Document Type:
Article
Affiliation country:
Cpt.2466
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