Methods, applications, interpretations and challenges of interrupted time series (ITS) data: protocol for a scoping...

Area of Science:

• Epidemiology
• Biostatistics
• Health Services Research

Background:

• Interrupted time series (ITS) design is crucial for evaluating interventions.
• ITS data analysis is increasingly used for evidence implementation interventions.
• Current statistical methods for ITS lack clear guidance on optimal application and interpretation.

Purpose of the Study:

• To conduct a scoping review of existing ITS data analysis methods.
• To summarize characteristics, properties, and reporting of these methods.
• To identify gaps and deficiencies in current ITS analysis methodologies.

Main Methods:

• Systematic search of electronic databases (MEDLINE, JSTOR) from inception to August 2016.
• Independent screening and data abstraction by two reviewers.
• Synthesis of methods used, their application, strengths, limitations, and reporting transparency.

Main Results:

• A comprehensive summary of statistical methods applied to ITS data in health research.
• Detailed comparison of method characteristics, similarities, and differences.
• Identification of areas needing methodological improvement and clearer reporting standards.

Conclusions:

• The review will provide a clear overview of ITS analysis techniques.
• It aims to enhance the understanding and application of ITS designs in health research.
• Findings will guide researchers in selecting appropriate methods and interpreting results more effectively.