Impact of Nurse Work Environment on Rural Quality of Care and Clinical Outcomes

描述(由申请人提供)：这项拟议的研究阐述了NINR消除由于地理位置而造成的健康差距的使命。现有的研究确定了影响护理质量和临床结果的社区因素(即贫困程度)和组织因素(即护士工作环境和医院特点)，但没有对乡村医院进行研究。在这项建议的K01中，结构性权变理论被用来概念化护士工作环境、农村社区特征、医院和护理单元特征、护理质量和临床结果(ML死亡率)之间的关系。这项拟议的指导性研究的目标是：a)开发护士评估的质量指标，并对照已建立的质量指标(医院收集的数据和大量公共数据集)测试这一指标；b)评估质量指标与小型乡村医院临床结果之间的关系；c)检查社区、医院、护理单位和护士工作环境的特征，这些特征可能影响小型乡村医院的护理质量指标和ML死亡率。为了实现这一目标，应聘者将追求职业发展计划，并将获得设计、开发和使用网络调查的知识和熟练程度；使用大型二级公共数据库；解决农村卫生研究带来的特殊挑战；以及掌握使用多层次数据进行大规模研究所需的统计方法和计算机应用的高级知识。候选人将准备在规划和进行复杂的农村护理健康研究方面发挥领导作用。培训将应用于拟议的研究，两个州的小型乡村医院将被邀请通过其首席护理官参与。数据将从多个来源收集：基于网络的员工护士调查、医院管理数据和大型公共数据库(即医院比较和州出院数据)。这些数据将使用多级建模和回归技术进行分析。这项研究将为未来的研究奠定基础，包括将医院的护理质量扩展到患者出院后的生活质量。这项研究的结果可能为管理者和政策制定者提供信息，了解护士工作环境中的因素以及农村社区、医院和护理单位的特点如何影响小型乡村医院患者的护理质量和ML死亡率。

DESCRIPTION (provided by applicant): The proposed study addresses NINR's mission of eliminating health disparities due to geographic location. Rural hospitals are absent from existing studies that identify community factors (i.e. level of poverty) and organizational factors (i.e. the nurse work environment and hospital characteristics) that influence quality of care and clinical outcomes. In this proposed K01, structural contingency theory is used to conceptualize the association between the nurse work environment, rural community characteristics, hospital and nursing unit characteristics, quality of care, and clinical outcomes (Ml mortality). The goals of this proposed mentored research are to: a) develop a nurse assessed quality indicator and test this measure against established quality indicators (hospital collected, and large public data sets); b) evaluate the relationship between quality indicators and clinical outcomes in small rural hospitals; c) examine characteristics of the community, hospital, nursing unit, and nurse work environment that may influence quality of care indicators and Ml mortality in small rural hospitals. To accomplish this, the candidate will pursue a career development program, and will gain knowledge and proficiency in designing, developing, and using Web surveys; using large secondary public data bases; negotiating the special challenges that rural health research poses; and acquiring advanced knowledge of statistical methods and computer applications needed to do large scale studies using multilevel data. The candidate will be prepared to assume a lead role in planning and conducting complex rural nursing health studies. The training will be applied to the proposed study where small rural hospitals in two states will be invited to participate through their chief nursing officer. Data will be collected from multiple sources: Web-based staff nurse surveys, hospital administrative data, and large public data bases (i.e. Hospital Compare and state discharge data). The data will be analyzed using multilevel modeling and regression techniques. This study will form the basis for future research that includes an expansion of quality of care in the hospital to patient's quality of life after discharge. Findings from this study may inform administrators and policy makers on how quality of care and Ml mortality rates for patients in small rural hospitals are influenced by factors in the nurses' work environment as well as characteristics of the rural community, hospital, and nursing unit.