NURSE STAFFING AND QUALITY OF HOSPITAL PATIENT CARE

本研究的目的是评估医院最近的变化 护理人员及其对病人护理质量的影响。 是否 护理人员的水平和组合有所下降，如果是这样，这是否 对患者护理质量的负面影响是一个令人担忧的问题， 医生和病人一样。此前的研究一直存在争议 而且没有结论 这项研究评估：1）最近的变化， 医院护理人员; 2）护士之间的结构关系 3）结构关系; 其他医院的特点和重组行动之间的关系， 一方面，另一方面，病人护理的质量;和4） 近期护理人员变动对病人质量的影响 在乎 研究假设是，从1992年至1996年：a） 护理人员的类别，病人负荷，持牌， 无证护理人员和全职或兼职护理人员 下降; B）护理人员的水平和组合较高 降低患者死亡率、再入院率和医院感染率 （c）医院重组整体而言， 死亡率、再入院率和医院感染率;以及d） 1992 - 1996年护理人员人数和组合的减少 与患者死亡率的增加有关， 再入院率和医院感染率。 一个面板数据集， 宾夕法尼亚州所有医院的病人和医院记录都被利用 在描述性模型和固定或随机效应线性回归中 模型来检验假设。

The aim of this research is to assess the recent changes in hospital nursing staff and their impact on the quality of patient care. Whether nursing staff levels and mix have declined, and if so, whether this has negatively impacted on the quality of patient care is a concern of practitioners and patients alike. Prior research has been controversial and inconclusive. This study assesses: 1 ) the recent changes in hospital nursing staff; 2) the structural relationship between nurse staffing and the quality of patient care; 3) the structural relationship between other hospital characteristics and restructuring actions on the one hand, and the quality of patient care on the other hand; and 4) the impact of the recent nursing staff changes on the quality of patient care. Research hypotheses are that from 1992-1996: a) the ratios of all categories of nursing personnel to patient load, of licensed to unlicensed nursing personnel, and of full to part time nursing personnel have declined; b) higher levels and mix of nursing staff are associated with lower patient mortality, readmission, and nosocomial infection rates; c) hospital restructuring overall is associated with higher mortality, readmission, and nosocomial infection rates; and d) the reductions in the level and mix of nursing staff from 1992-1996 described above are associated with increases in patient mortality, readmission, and nosocomial infection rates. A panel data set from patient and hospital records in all Pennsylvania hospitals is utilized in a descriptive model and a fixed or random effects linear regression model to test the hypotheses.