Table 2.

Opportunities Presented to Enhance Health Services Research Through Qualitative Comparative Analysis (QCA)

	Qualitative Comparative Analysis (QCA)	Qualitative Analysis without QCA
Study Design
Steps required	Site visits, coding, identify themes, summarize themes, create and apply calibration structure, perform analysis.	Site visits, coding, identify themes.
Number of cases	About 10 (minimum)	1 or more
Results
Level of detail	Each condition is defined and ordered. A fuzzy set calibration can be used to express the level of presence of each condition at each site. Factors are represented numerically and can be quickly compared across sites.	A great level of detail may be expressed in prose, but may be cumbersome to compare across sites.
Type of results	Identifies different solution pathways associated with quality care. Raises possibility of testing solutions in different settings by providing detailed conditions on which organizations can focus.	Lists factors associated with low underuse with strength of association of proposed causal factors. Lacks condition details embedded within calibration structure and in associations with outcome. Lacking these details, organizations may focus on all factors equally.
Number of findings	One outcome per analysis; takes longer to identify combinations of factors associated with success or failure (e.g., low screening vs. low treatment rates).	Factors can be identified and grouped with different outcomes (e.g., facilitators of and barriers to screening/treatment completion) during the same analysis.
Presentation of findings	Focus on specific pathways hospitals use to achieve high quality; less focus on barriers to achieve low underuse.	General discussion of facilitators of and barriers to achieving low underuse.
Level of bias	Bias inherent in coding process and specification of conditions, but process of creating specific and objective measures of conditions forces greater level of proof/objectivity of findings.	Bias inherent in coding process