Jackson Elizabeth F, Siddiqui Ayesha, Gutierrez Hialy, Kanté Almamy Malick, Austin Judy, Phillips James F
Heilbrunn Department of Population and Family Health, Columbia University Mailman School of Public Health, 60 Haven Ave, Suite B-2, New York, NY, 10032, USA.
Department of Family Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, USA.
BMC Health Serv Res. 2015 Dec 3;15:536. doi: 10.1186/s12913-015-1203-7.
Service Provision Assessment (SPA) surveys have been conducted to gauge primary health care and family planning clinical readiness throughout East and South Asia as well as sub-Saharan Africa. Intended to provide useful descriptive information on health system functioning to supplement the Demographic and Health Survey data, each SPA produces a plethora of discrete indicators that are so numerous as to be impossible to analyze in conjunction with population and health survey data or to rate the relative readiness of individual health facilities. Moreover, sequential SPA surveys have yet to be analyzed in ways that provide systematic evidence that service readiness is improving or deteriorating over time.
This paper presents an illustrative analysis of the 2006 Tanzania SPA with the goal of demonstrating a practical solution to SPA data utilization challenges using a subset of variables selected to represent the six building blocks of health system strength identified by the World Health Organization (WHO) with a focus on system readiness to provide service. Principal Components Analytical (PCA) models extract indices representing common variance of readiness indicators. Possible uses of results include the application of PCA loadings to checklist data, either for the comparison of current circumstances in a locality with a national standard, for the ranking of the relative strength of operation of clinics, or for the estimation of trends in clinic service quality improvement or deterioration over time.
Among hospitals and health centers in Tanzania, indices representing two components explain 32% of the common variance of 141 SPA indicators. For dispensaries, a single principal component explains 26% of the common variance of 86 SPA indicators. For hospitals/HCs, the principal component is characterized by preventive measures and indicators of basic primary health care capabilities. For dispensaries, the principal component is characterized by very basic newborn care as well as preparedness for delivery.
PCA of complex facility survey data generates composite scale coefficients that can be used to reduce indicators to indices for application in comparative analyses of clinical readiness, or for multi-level analysis of the impact of clinical capability on health outcomes or on survival.
已开展服务提供评估(SPA)调查,以衡量东亚、南亚以及撒哈拉以南非洲地区的初级卫生保健和计划生育临床准备情况。旨在提供有关卫生系统运作的有用描述性信息,以补充人口与健康调查数据,每次SPA都会产生大量离散指标,其数量之多以至于无法与人口和健康调查数据结合进行分析,也无法对各个卫生设施的相对准备情况进行评级。此外,尚未以能够提供系统证据证明服务准备情况随时间推移是改善还是恶化的方式对连续的SPA调查进行分析。
本文对2006年坦桑尼亚SPA进行了示例性分析,目的是通过选择一组变量来展示应对SPA数据利用挑战的实际解决方案,这些变量代表了世界卫生组织(WHO)确定的卫生系统实力的六个组成部分,重点是提供服务的系统准备情况。主成分分析(PCA)模型提取代表准备指标共同方差的指数。结果的可能用途包括将PCA载荷应用于清单数据,既可以将当地的当前情况与国家标准进行比较,对诊所运营的相对强度进行排名,也可以估计诊所服务质量随时间改善或恶化的趋势。
在坦桑尼亚的医院和卫生中心中,代表两个成分的指数解释了141个SPA指标共同方差的32%。对于医务室,单个主成分解释了86个SPA指标共同方差的26%。对于医院/卫生中心,主成分的特征是预防措施和基本初级卫生保健能力指标。对于医务室,主成分的特征是非常基本的新生儿护理以及分娩准备情况。
对复杂的设施调查数据进行主成分分析会生成综合量表系数,可用于将指标简化为指数,以应用于临床准备情况的比较分析,或用于对临床能力对健康结果或生存的影响进行多层次分析。