Objective. To identify and quantify the sources of the urban-rural disparity in facility-acquired contracture rates in nursing homes. Data Sources. Survey inspection data of U.S. nursing homes from 1999 to 2008 and standardized national rural definition file from the Rural-Urban Commuting Area Codes. Study Design. We estimated regressions of facility-level contracture rate as a function of urban-rural categories (urban, micropolitan, small rural town, and isolated small rural town) and other related facility characteristics to identify size of the urban-rural disparity. We used Blinder-Oaxaca decomposition techniques to determine the extent to which the disparity is attributable to the differences in facility and aggregate resident characteristics. Principal Findings. Rural nursing homes have higher contracture rates than urban nursing homes. About half of the urban-rural disparity is explained by differences in observable characteristics among urban and rural nursing homes. Differences in staffing levels explain less than 5 percent of the disparity, case-mix explains 6-8 percent, and structure and operational characteristics account for 10-22 percent of the disparity. Conclusion. While a lower level and quality of staffing are a concern for rural nursing homes, facility structure and funding sources explain a larger proportion of the urbanrural disparity in the quality of care. Key Words. Quality of care, disparities, rural, nursing homes, contractures, decomposition As the trends in population aging continues in the United States, the demand for all forms of long-term care is likely to increase in the coming decades. Meeting this rising demand is more challenging for rural areas because rural elderly have greater long-term care needs than their urban counterparts (Fennell and Campbell 2007) and there are well-documented differences in urban and rural long-term care providers (Phillips, Hawes, and Williams

Objective. To study the effect of minimum nurse staffing requirements on the subsequent employment of nursing home support staff. Data Sources. Nursing home data from the Online Survey Certification and Reporting (OSCAR) System merged with state nurse staffing requirements. Study Design. Facility-level housekeeping, food service, and activities staff levels are regressed on nurse staffing requirements and other controls using fixed effect panel regression. Data Extraction Method. OSCAR surveys from 1999 to 2004. Principal Findings. Increases in state direct care and licensed nurse staffing requirements are associated with decreases in the staffing levels of all types of support staff. Conclusions. Increased nursing home nurse staffing requirements lead to input substitution in the form of reduced support staffing levels. Key Words. Nursing homes, regulation, staffing requirements, support staff, housekeeping, food service, activities staff Nurse staffing is an important input in the production of high-quality nursing home (NH) care. Responding to concerns about inadequate nurse staffing levels, between 1999 and 2004, 14 states enacted or strengthened minimum nurse staffing policies. Without nurse staffing requirements, NH administrators choose the optimal amount of nurse staff and non-nurse inputs that maximize the facility's objectives. While requirements may guarantee a minimum level of nurse staff availability, administrators face resource constraints and increases in requirements may cause reductions in the use of non-nurse inputs. This substitution of inputs is likely to result in reduced employment of support staff, such as housekeepers, food service, and activities workers. This article studies whether NHs engage in input substitution by using fewer support staff after changes in nurse staffing requirements.

Nursing home staff should be trained to deliver disaster-related mental health intervention and in procedures for making referrals for follow-up evaluation and formal intervention.