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Published on: February 19, 2021
The Longitudinal Implementation Strategy Tracking System (LISTS): feasibility, usability, and pilot testing of a
Justin D Smith1,2, Wynne E Norton3, Sandra A Mitchell3
1Department of Population Health Sciences, School of Medicine, University of Utah, Spencer Fox Eccles, Salt Lake City, UT, USA. jd.smith@hsc.utah.edu.
The Longitudinal Implementation Strategy Tracking System (LISTS) provides a feasible and acceptable method for tracking implementation strategies over time. This novel system aids in understanding how strategies change, improving future research and practice.
Area of Science:
- Implementation Science
- Health Services Research
- Clinical Research Methodology
Background:
- Systematic methods are crucial for characterizing the dynamic use of implementation strategies over time.
- The Longitudinal Implementation Strategy Tracking System (LISTS) was developed to address this need.
- LISTS aims to improve the precision and reliability of documenting changes in implementation strategy use.
Purpose of the Study:
- To describe the development and preliminary evaluation of the LISTS methodology.
- To assess the feasibility, acceptability, and usability of LISTS in real-world settings.
- To provide a systematic approach for tracking implementation strategy modifications.
Main Methods:
- LISTS was developed iteratively with implementation researchers and practitioners.
- The system comprises a strategy assessment, data capture platform, and User's Guide.
- LISTS was evaluated over 12 months in three stepped-wedge trials within the IMPACT Consortium.
Main Results:
- Initial evaluations indicate LISTS is a feasible, acceptable, and content-valid method.
- Users identified opportunities for method improvement in future studies.
- The system demonstrated utility in characterizing and tracking implementation strategy use.
Conclusions:
- LISTS was collaboratively developed to fill a gap in systematically tracking implementation strategy use.
- Preliminary feedback suggests LISTS is feasible and usable.
- Future developments may include enhanced features and interoperability, supporting data analysis and synthesis across studies.
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