01 Aug 2016
Gimbel S, Rustagi AS, Robinson J, Kouyate S, Coutinho J, Nduati R, et al. (2016). Evaluation of a Systems Analysis and Improvement Approach to Optimize Prevention of Mother-To-Child Transmission of HIV Using the Consolidated Framework for Implementation Research. J Acquir Immune Defic Syndr. 72(Suppl 2), S108-16. doi: 10.1097/QAI.0000000000001055
Background: Despite large investments to prevent mother-to-child-transmission (PMTCT), pediatric HIV elimination goals are not on track in many countries. The Systems Analysis and Improvement Approach (SAIA) study was a cluster randomized trial to test whether a package of systems engineering tools could strengthen PMTCT programs. We sought to (1) define core and adaptable components of the SAIA intervention, and (2) explain the heterogeneity in SAIA’s success between facilities.
Methods: The Consolidated Framework for Implementation Research (CFIR) guided all data collection efforts. CFIR constructs were assessed in focus group discussions and interviews with study and facility staff in 6 health facilities (1 high-performing and 1 low-performing site per country, identified by study staff) in December 2014 at the end of the intervention period. SAIA staff identified the intervention’s core and adaptable components at an end-of-study meeting in August 2015. Two independent analysts used CFIR constructs to code transcripts before reaching consensus.
Results: Flow mapping and continuous quality improvement were the core to the SAIA in all settings, whereas the PMTCT cascade analysis tool was the core in high HIV prevalence settings. Five CFIR constructs distinguished strongly between high and low performers: 2 in inner setting (networks and communication, available resources) and 3 in process (external change agents, executing, reflecting and evaluating).
Discussion: The CFIR is a valuable tool to categorize elements of an intervention as core versus adaptable, and to understand heterogeneity in study implementation. Future intervention studies should apply evidence-based implementation science frameworks, like the CFIR, to provide salient data to expand implementation to other settings.