TY - JOUR
T1 - Harmonizing Qualitative Data Across Multiple Health Systems to Identify Quality Improvement Interventions
T2 - A Methodological Framework Using PROSPR II Cervical Research Center Data as Exemplar
AU - Higashi, Robin T.
AU - Kruse, Gina
AU - Richards, Julie
AU - Sood, Anubha
AU - Chen, Patricia M.
AU - Quirk, Lisa
AU - Kramer, Justin
AU - Tiro, Jasmin A.
AU - Tuzzio, Leah
AU - Haas, Jennifer S.
AU - Figueroa Gray, Marlaine
AU - Lee, Simon C.
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Cancer Institute at the National Institutes of Health, UM1CA221940.
Publisher Copyright:
© The Author(s) 2023.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Background: Heterogeneity in healthcare systems’ organizational structures, policies and decisions influences practice implementation and care delivery. While quantitative data harmonization has been used to compare outcomes, few have conducted cross-site qualitative inquiry of healthcare delivery; thus, little is known about how to harmonize qualitative data across multiple settings. Objective: We illustrate a methodological approach for a theory-driven qualitative data harmonization process for the PROSPR II Cervical Research Center, a large multi-site, mixedmethods study evaluating cervical cancer screening across three diverse healthcare settings. Methods: We compared three geographically, socio-demographically, and structurally diverse healthcare systems using a multi-modal qualitative data collection strategy. We grounded our sampling strategy in a cervical cancer screening process model, then tailored it for system-specific differences (e.g., clinic staffing structure and individual roles). Data collection tools included domains corresponding to shared research objectives (e.g., abnormal follow-up) while accommodating local context. Analysis drew on operational domains from the screening process model and constructs from the Consolidated Framework for Implementation Research and Normalization Process Theory. Results: Exemplars demonstrate how data harmonization revealed insights suggesting opportunities to improve clinical processes across healthcare systems. Discussion: This analysis advances the application of qualitative methods in implementation science, where assessing context is key to responding to organizational challenges and shaping implementation strategies across multiple health systems. We demonstrate how systematically collecting, analyzing and harmonizing qualitative data elucidates the impact of process factors and accelerates efforts to identify opportunities for quality improvement interventions.
AB - Background: Heterogeneity in healthcare systems’ organizational structures, policies and decisions influences practice implementation and care delivery. While quantitative data harmonization has been used to compare outcomes, few have conducted cross-site qualitative inquiry of healthcare delivery; thus, little is known about how to harmonize qualitative data across multiple settings. Objective: We illustrate a methodological approach for a theory-driven qualitative data harmonization process for the PROSPR II Cervical Research Center, a large multi-site, mixedmethods study evaluating cervical cancer screening across three diverse healthcare settings. Methods: We compared three geographically, socio-demographically, and structurally diverse healthcare systems using a multi-modal qualitative data collection strategy. We grounded our sampling strategy in a cervical cancer screening process model, then tailored it for system-specific differences (e.g., clinic staffing structure and individual roles). Data collection tools included domains corresponding to shared research objectives (e.g., abnormal follow-up) while accommodating local context. Analysis drew on operational domains from the screening process model and constructs from the Consolidated Framework for Implementation Research and Normalization Process Theory. Results: Exemplars demonstrate how data harmonization revealed insights suggesting opportunities to improve clinical processes across healthcare systems. Discussion: This analysis advances the application of qualitative methods in implementation science, where assessing context is key to responding to organizational challenges and shaping implementation strategies across multiple health systems. We demonstrate how systematically collecting, analyzing and harmonizing qualitative data elucidates the impact of process factors and accelerates efforts to identify opportunities for quality improvement interventions.
KW - cancer prevention
KW - cancer screening
KW - grounded theory
KW - implementation science
KW - mixed methods
KW - qualitative evaluation
KW - qualitative research design
KW - structured observation
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U2 - 10.1177/16094069231157345
DO - 10.1177/16094069231157345
M3 - Article
AN - SCOPUS:85148453002
SN - 1609-4069
VL - 22
JO - The International Journal of Qualitative Methods
JF - The International Journal of Qualitative Methods
ER -