Development of a method for qualitative data integration to advance implementation science within research consortia

Area of Science:

• Implementation Science
• Qualitative Research Methods
• Health Services Research

Background:

• Qualitative data integration methods are less developed than quantitative approaches, hindering cross-study inquiry and data sharing.
• The National Cancer Institute's Improving the Management of symPtoms During And following Cancer Treatment (IMPACT) Consortium faces challenges in qualitative data integration.
• Emphasis on open science and data sharing necessitates robust methods for qualitative data integration.

Purpose of the Study:

• To describe a systematic method for qualitative data integration within a multi-site research consortium.
• To address challenges in integrating qualitative data across diverse settings and studies.
• To provide a replicable methodology for cross-site qualitative inquiry and data sharing.

Main Methods:

• The IMPACT Consortium utilized the Consolidated Framework for Implementation Research (CFIR) to guide data collection and analysis.
• A semi-structured interview guide was developed and tailored to specific healthcare settings and interventions.
• Pilot testing involved exchanging and analyzing qualitative transcripts across research centers.

Main Results:

• Integrating qualitative data across heterogeneous settings was resource-intensive and complex.
• Recommendations include using a common framework, coding hierarchically (domain then construct), and centralizing processes.
• An iteratively refined codebook based on CFIR 2.0 was developed to guide coders.

Conclusions:

• Limited guidance exists for qualitative data integration, exchange, and sharing across multiple studies.
• A systematic, framework-guided approach can foster qualitative data integration in research consortia.
• This methodology supports cross-site qualitative inquiry and enhances understanding of evidence-based intervention implementation.