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FIT FOR PURPOSE IN ACTION: DESIGN, IMPLEMENTATION, AND EVALUATION OF THE NATIONAL INTERNET FLU SURVEY
Jill A Dever1, Ashley Amaya1, Anup Srivastav2
1RTI International, 701 13th St NW, Suite 750, Washington, DC 20005-3967, USA.
Summary
The fit for purpose (FfP) framework guides survey design, ensuring data quality and usefulness by balancing analytic needs with practical constraints. This approach was applied to the National Internet Flu Survey (NIFS) for accurate influenza data collection.
Area of Science:
- Public Health
- Survey Methodology
- Health Services Research
Background:
- Survey quality and usefulness are defined by specific analytic needs, requiring careful consideration of design trade-offs.
- Practical constraints like budget and timelines necessitate a structured approach to survey design.
- The concept of 'fit for purpose' (FfP) offers a framework for evaluating these trade-offs and ensuring data quality.
Purpose of the Study:
- To demonstrate the application of a fit for purpose (FfP) framework in designing and evaluating a national survey.
- To assess the quality of the National Internet Flu Survey (NIFS) in meeting its objectives.
- To compare the FfP characteristics of the NIFS with other national health surveys.
Main Methods:
- Development and implementation of an FfP framework tailored for survey design and quality assessment.
- Application of the FfP framework to the National Internet Flu Survey (NIFS), an annual internet-based survey on influenza.
- Comparative analysis of FfP characteristics between the NIFS and the National Flu Survey, National Health Interview Survey, and Behavioral Risk Factor Surveillance System.
Main Results:
- The FfP framework provided a structured approach for critical design decisions in the NIFS.
- The NIFS demonstrated strengths in meeting its objectives, with specific areas identified for further evaluation.
- Comparative analysis revealed distinct FfP characteristics across different national surveys, highlighting unique strengths and limitations.
Conclusions:
- The fit for purpose (FfP) framework is crucial for designing effective surveys and defining data quality.
- Implementing an FfP framework aids in evaluating survey performance against intended objectives.
- FfP metrics can clearly communicate the intended use and limitations of survey data to users.
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