Authors:
Lisa DiMartino, Allison J. Carroll, Jennifer L. Ridgeway, Anna Revette, Joan M. Griffin, Bryan J. Weiner, Sandra A. Mitchell, Wynne E. Norton, Christine Cronin, Andrea L. Cheville, Ann Marie Flores, Justin D. Smith on behalf of the IMPACT Consortium
University of Washington affiliated authors are displayed in bold.
✪ Open Access
Published: February 2025
Read the full text in the open access journal Implementation Science Communications
Abstract:
Background
Methods of integrating qualitative data across diverse studies and within multi-site research consortia are less developed than those for integrating quantitative data. The development ofsuchmethods is essential to support the data exchange needed for cross-study qualitative inquiry and given the increasing emphasis on data sharing and open science. We describe methods for qualitative data integration within the National Cancer Institute’s Improving the Management of symPtoms During And following Cancer Treatment (IMPACT) Consortium funded by the Cancer MoonshotSM. Data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR). Our case study highlights potential solutions for unique challenges faced when integrating qualitative data across multiple settings in a research consortium.
Methods
The IMPACT consortium is comprised of three research centers (RCs) each conducting pragmatic trials examining the effectiveness of routine symptom management on patient-centered outcomes. After reaching consensus on use of CFIR as the common implementation determinant framework, RCs developed a semi-structured interview guide and tailored it to features of their healthcare setting and symptom management interventions. RCs conducted interviews/focus groups with healthcare system partners to examine contextual factors impacting implementation. RCs exchanged 1–2 transcripts (n = 5 total) for purposes of pilot testing the methodology.
Results
Given the heterogeneity of study settings and contexts, it was challenging to simultaneously assign codes at both domain and construct levels and the process was resource intensive. Recommendations include employing a common framework for data collection and analyses from the outset, coding at domain level first and then incorporating construct codes, and centralizing processes via a coordinating center (or similar entity) and combining coded transcripts using qualitative software. We also generated an iteratively refined codebook that employed the CFIR schema and incorporated CFIR 2.0 to provide detailed guidance for coders conducting cross-study qualitative inquiry.
Conclusions
Limited guidance exists on how to support qualitative data integration, data exchange, and sharing across multiple studies. This paper describes a systematic method for employing an implementation determinant framework-guided approach to foster data integration. This methodology can be adopted by other research consortia to support qualitative data integration, cross-site qualitative inquiry, and generate improved understanding of evidence-based intervention implementation.
Contributions to the literature
- Few standard practices exist for integrating qualitative data across different studies to conduct cross-study qualitative inquiry. Developing data integration procedures is critical to generating insights about practice improvement across settings and achieving goals of open science.
- This report describes a method for integrating qualitative data using the Consolidated Framework for Implementation Research illustrated within the context of NCI’s Improving the Management of symPtoms During And following Cancer Treatment (IMPACT) Consortium.
- The method describedcan be applied within research consortia and across multi-site studies to support qualitative data integration, thereby producing valuable insights to improve implementation of evidence-based interventions.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**