The National Response for Preventing Healthcare-Associated Infections
System Capacity and Sustainability for Improvement
Published in: Medical Care, v. 52, no. 2, suppl. 1, Feb. 2014, p. S83-S90
Posted on RAND.org on February 01, 2014
BACKGROUND: Strengthening capacity across the healthcare system for improvement is critical to ensuring that past efforts and investments establish a foundation for sustaining progress in patient safety. OBJECTIVES: The objective of this analysis was to identify key system capacity issues for sustainability from evaluation of the Action Plan to prevent healthcare–associated infections, a major national initiative launched by the US Department of Health and Human Services in 2009. RESEARCH DESIGN: The analysis involves the review and synthesis of results across the components of a 3-year evaluation of the Action Plan, as described in the evaluation framework and detailed in separate analyses elsewhere in this special issue. Data collection methods included interviews with government and private stakeholders, document and literature reviews, and observations of meetings and conferences at multiple time points. MEASURES: Key developments in healthcare–associated infection prevention system capacity were extracted on the basis of "major activities" identified through multiple methods and organized into the level of progress based on perspectives of multiple stakeholders. Activities within each level were then examined and compared according to our evaluation's framework of 4 system functions and 5 system properties. RESULTS: Key system capacity and sustainability issues for the Action Plan to be addressed centered on coordination and alignment (among participating agencies, with other federal initiatives, and across levels of healthcare), infrastructure for data and accountability (including more efficient technologies and unintended consequences), cultural embedding of prevention practices, and uncertainty and variability in resources. CONCLUSIONS: Sustainability depends on improvements across system functions and properties and how they reinforce each other. Change is more robust if different system elements support and incentivize behavior in similar directions.