Abstract
BACKGROUND: Two of the current methodological barriers to implementation science efforts are the lack of agreement regarding constructs hypothesized to affect implementation success and identifiable measures of these constructs. In order to address these gaps, the main goals of this paper were to identify a multi-level framework that captures the predominant factors that impact implementation outcomes, conduct a systematic review of available measures assessing constructs subsumed within these primary factors, and determine the criterion validity of these measures in the search articles. METHOD: We conducted a systematic literature review to identify articles reporting the use or development of measures designed to assess constructs that predict the implementation of evidence-based health innovations. Articles published through 12 August 2012 were identified through MEDLINE, CINAHL, PsycINFO and the journal Implementation Science. We then utilized a modified five-factor framework in order to code whether each measure contained items that assess constructs representing structural, organizational, provider, patient, and innovation level factors. Further, we coded the criterion validity of each measure within the search articles obtained. RESULTS: Our review identified 62 measures. Results indicate that organization, provider, and innovation-level constructs have the greatest number of measures available for use, whereas structural and patient-level constructs have the least. Additionally, relatively few measures demonstrated criterion validity, or reliable association with an implementation outcome (e.g., fidelity). DISCUSSION: In light of these findings, our discussion centers on strategies that researchers can utilize in order to identify, adapt, and improve extant measures for use in their own implementation research. In total, our literature review and resulting measures compendium increases the capacity of researchers to conceptualize and measure implementation-related constructs in their ongoing and future research.