Study Design. This mixed methods, cross-sectional study used structured interviews to obtain information about presence of, and variation in, GH-relevant structures and processes of care. Qualitative questions explored reasons for variation in model implementation. Data Collection/Extraction Methods. Interview data were analyzed using relatedsample tests, and qualitative data were iteratively analyzed using a directed content approach. Principal Findings. GH homes showed substantial variation in practices to support resident choice and decision making; neither GH nor legacy homes provided complete choice, and all GH homes excluded residents from some key decisions. GH homes were most consistent with the model and one another in elements to create a real home, such as private rooms and baths and open kitchens, and in staff-related elements, such as self-managed work teams and consistent, universal workers. Conclusions. Although variation in model implementation complicates evaluation, if expansion is to continue, it is essential to examine GH elements and their outcomes.

Objective. To develop a conceptual model that explained common and divergent care processes in Green House (GH) nursing homes with high and low hospital transfer rates. Data Sources/Settings. Eighty-four face-to-face, semistructured interviews were conducted with direct care, professional, and administrative staff with knowledge of care processes in six GH organizations in six states. Study Design/Data Collection. The qualitative grounded theory method was used for data collection and analysis. Data were analyzed using open, axial, and selective coding. Data collection and analysis occurred iteratively. Principal Findings. Elements of the GH model created significant opportunities to identify, communicate, and respond to early changes in resident condition. Staff in GH homes with lower hospital transfer rates employed care processes that maximized these opportunities. Staff in GH homes with higher transfer rates failed to maximize, or actively undermined, these opportunities. Conclusions. Variations in how the GH model was implemented across GH homes suggest possible explanations for inconsistencies found in past research on the care outcomes, including hospital transfer rates, in culture change models. The findings further suggest that the details of culture change implementation are important considerations in model replication and policies that create incentives for care improvements. Key Words. Medical decision making, nursing, qualitative research, long-term care, nursing homes, culture change Evidence suggests that between 25 percent and 70 percent of hospital transfers from nursing homes are "potentially avoidable" (Ouslander and Maslow 2012; U.S. Department of Health and Human Services [USDHHS] 2013;Ouslander et al. 2014). Older adults from long-term care settings are particularly vulnerable to the risks of hospitalization, which include hospital-acquired complications, morbidity, mortality, and excess health care expenditure

Government policies have been enacted to support culture change. However, there is currently little guidance for regulators, providers, or consumers regarding variability in how culture change practices are implemented and consequences of these variations. This article outlines the importance of understanding these practices at a level of detail that distinguishes and supports those that are most promising.

Reinforcing the GH model requires a highly skilled team of staff with the ability to frequently and collaboratively solve both mundane and complex problems in ways that are consistent with the GH model. This raises questions about the type of human resources practices and policy supports that could assist organizations in sustaining culture change.

Future research should focus on developing a conceptual understanding of consistent assignment focused on definition, measurement, and links to outcomes. To inform current policies, testing consistent assignment should include attention to contexts within and levels at which it is most effective.