Hajat Anjum, Cilenti Dorothy, Harrison Lisa M, MacDonald Pia D M, Pavletic Denise, Mays Glen P, Baker Edward L
Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
J Public Health Manag Pract. 2009 Mar-Apr;15(2):E22-33. doi: 10.1097/01.PHH.0000346022.14426.84.
Local public health agencies (LPHAs) are faced with many challenges in their role as an integral part of the public health system. It is important to better understand the demands on and the capacity of LPHAs to respond to these challenges. Determining what factors can improve LPHA performance is critical to helping LPHAs face their challenges.The objective of this study was to determine what factors are associated with LPHA performance improvement in North Carolina from 1999 to 2004. In North Carolina, several data sources regarding predictors of LPHA performance, including LPHA workforce, LPHA characteristics, public health expenditures, and population characteristics, are available. Improvement in LPHA performance was measured by nine indicators across diverse services that were collected over multiple years. Linear regression was used to evaluate the significance of predictor variables.Our findings indicate that workforce characteristics such as occupational classification and experience of the workforce, LPHA characteristics such as number of full-time employees, as well as population characteristics are important predictors of LPHA performance.This study provides insight into what is needed to better address LPHA performance improvement. More importantly, study findings indicate which workforce characteristics can be targeted to enhance LPHA performance improvement over time.
地方公共卫生机构(LPHAs)作为公共卫生系统的一个组成部分,在履行职责时面临诸多挑战。更好地了解LPHAs所面临的需求以及应对这些挑战的能力非常重要。确定哪些因素能够提高LPHAs的绩效对于帮助它们应对挑战至关重要。本研究的目的是确定1999年至2004年北卡罗来纳州与LPHAs绩效提升相关的因素。在北卡罗来纳州,可以获取多个关于LPHAs绩效预测指标的数据源,包括LPHAs的工作人员、LPHAs的特征、公共卫生支出以及人口特征。LPHAs绩效的提升通过多年收集的多种服务的九个指标来衡量。使用线性回归来评估预测变量的显著性。我们的研究结果表明,诸如工作人员的职业分类和经验等劳动力特征、诸如全职员工数量等LPHAs特征以及人口特征是LPHAs绩效的重要预测指标。本研究为更好地实现LPHAs绩效提升所需的条件提供了见解。更重要的是,研究结果表明随着时间的推移,哪些劳动力特征可以作为目标来增强LPHAs的绩效提升。