Nurse Staffing & Nursing Care Quality in Nursing Homes

描述（由申请人提供）：2000年，全国21%的护理机构因护理质量不足而被引用，13%因住院医师评估差而被引用，17%因未能提供全面的护理计划而被引用。护理人员配备对养老院护理的提供有重要影响。尽管如此，在过去的几年里，特别是在《平衡预算法案》下，护士的配备水平有所不同。目前还不清楚这些人员的变化会如何影响养老院的护理质量。本研究的目的是：(1)利用管理资料和评估资料，评估护理质量建构的效度和信度；2)在制度框架下检查护理质量的差异或变化；3)确定护理人员配备和护理充足性对护理质量的影响，控制制度（环境和市场）因素的影响；4)评估《平衡预算法》对养老院实践和质量的影响；5)对高性能养老院进行基准和概况分析；6)对环境或制度因素对养老院护士人员配备、护理充足性和护理质量的影响进行多层次分析；7)利用养老院行政数据（OSCAR）和最小数据集（MDS）居民评估数据确定护理质量指标的并发效度。

DESCRIPTION (provided by applicant): In 2000 21% of nursing facilities nationally were cited for general quality of care deficiencies, 13% for poor resident assessment, and 17% for failure to provide a comprehensive care plan. Nurse staffing has an important influence on the delivery of nursing home care. Nonetheless, nurse-staffing levels varied over the past years, particularly under the Balanced Budget Act. It is unclear how those staff changes may have affected nursing homes' quality of care. The purposes of this study are to 1) assess the validity and reliability of the construct of nursing care quality, using administrative and assessment data; 2) examine differences or variations in nursing care quality with an institutional framework; 3) identify the effect of nurse staffing and nursing care adequacy on nursing care quality, controlling the effects of institutional (contextual and market) factors; 4) evaluate the impact of the Balanced Budget Act on nursing home practice and quality; 5) perform benchmarking and profile analysis of high-performance nursing homes, 6) perform multilevel analysis of the effects of contextual or institutional factors on nurse staffing, nursing care adequacy and nursing care quality of nursing homes;7) determine the concurrent validity of nursing care quality indicators, using nursing homes' administrative data (OSCAR) and Minimum Data Set (MDS) resident assessment data. The study will use an administrative dataset--the Online Survey, Certification, and Reporting (OSCAR)_compiled from a panel of 14,000 facilities in 1997-2004. These panel data will be merged with the Area Resource File to capture the contextual and market characteristics associated with the distribution of nursing home facilities. Multivariate statistical modeling techniques will be used to analyze the eight waves of OSCAR data and four years of MDS data to be available: confirmatory factor analysis of nursing care quality in nursing homes (Aim 1), covariance structure modeling of institutional determinants of nursing care quality (Aim 2), multilevel analysis of the mediating effect of nurse staffing on nursing care quality (Aim 3), growth curve modeling of changes in nurse staffing and in quality (Aim 4), benchmarking analysis of high-quality facilities (Aim 5), multilevel covariance analysis and growth curve modeling of contextual effects on the structure-process-outcome of nursing care quality (Aim 6), and concurrent validation with OSCAR and MDS quality indicators by confirmatory factor analysis (Aim7). Our proposal focuses on important predictors of the trajectories of nursing facilities' nurse staffing and quality. Our findings will demonstrate the importance of nurse staffing and drive the development of operational strategies to improve the structural and process aspects of nursing home quality.