Quantitative study designs used in quality improvement and assessment.

Abstract

This article describes common quantitative design techniques that can be used to collect and analyze quality data. An understanding of the differences between these design techniques can help healthcare quality professionals make the most efficient use of their time, energies, and resources. To evaluate the advantages and disadvantages of these various study designs, it is necessary to assess factors that threaten the degree with which quality professionals may infer a cause-and-effect relationship from the data collected. Processes, the conduits of organizational function, often can be assessed by methods that do not take into account confounding and compromising circumstances that affect the outcomes of their analyses. An assumption that the implementation of process improvements may cause real change is incomplete without a consideration of other factors that might also have caused the same result. It is only through the identification, assessment, and exclusion of these alternative factors that administrators and healthcare quality professionals can assess the degree to which true process improvement or compliance has occurred. This article describes the advantages and disadvantages of common quantitative design techniques and reviews the corresponding threats to the interpretability of data obtained from their use.