Field Emma, Usurup Jethro, Nathan Sally, Rosewell Alexander
Menzies School of Health Research, Spring Hill, QLD 4000, Australia, and Abt Associates and School of Public Health and Community Medicine, University of New South Wales, UNSW Sydney, NSW 2052, Australia
Abt Associates
Rural Remote Health. 2018 Oct;18(4):4484. doi: 10.22605/RRH4484. Epub 2018 Oct 5.
The Rural Primary Health Services Delivery Project aims to improve the quality and coverage of health services to rural populations in Papua New Guinea. There are limitations in measuring performance of such projects through analysis of health information system data alone due to data quality issues and a multitude of unmeasured factors that affect performance. A mixed methods study was undertaken to understand the contextual factors that affect health service performance.
A performance assessment framework was developed including service delivery indicators derived from the National Health Information System. Prior to implementation, a baseline analysis of the indicators was undertaken. Subsequently, semi-structured interviews were conducted with health administrators, in which they were asked about factors they perceived to influence health facility performance. During the interviews, key informants were provided with health indicators for their province and asked to interpret the performance of facilities. Interviews were transcribed and inductive thematic analysis performed.
Performance indicators varied greatly within and between districts. Key informants cited a number of reasons for this variation. Health facilities accessible by road in urban areas, with competent and/or higher level staff and health services operated by churches or private companies, were cited as contributors to high performance. For high performing districts, key informants also discussed use of health information, planning and targeted strategies to improve performance. Inadequate numbers of staff, poorly skilled staff, funding delays and challenging geography were major contributors noted for poor performance.
Analysis of quantitative indicators needs to be performed at health facility level in order to understand district level performance. Interpretation of performance through key informant interviews provided useful insight into previously undocumented contextual factors affecting health delivery performance. The sequential explanatory mixed methods design could be applied to evaluations of other health service delivery programs in similar contexts.
农村初级卫生服务提供项目旨在提高巴布亚新几内亚农村人口的卫生服务质量和覆盖范围。仅通过分析卫生信息系统数据来衡量此类项目的绩效存在局限性，原因在于数据质量问题以及众多影响绩效的未测量因素。为此开展了一项混合方法研究，以了解影响卫生服务绩效的背景因素。
制定了一个绩效评估框架，其中包括源自国家卫生信息系统的服务提供指标。在实施之前，对这些指标进行了基线分析。随后，对卫生管理人员进行了半结构化访谈，询问他们认为影响卫生机构绩效的因素。在访谈过程中，向关键信息提供者提供了其所在省份的卫生指标，并要求他们解读各机构的绩效。访谈内容进行了转录，并开展了归纳主题分析。
各地区内部和之间的绩效指标差异很大。关键信息提供者列举了造成这种差异的一些原因。城市地区可通过公路到达的卫生机构、拥有称职和/或高级别工作人员以及由教会或私人公司运营的卫生服务，被认为是高绩效的促成因素。对于高绩效地区，关键信息提供者还讨论了卫生信息的使用、规划和有针对性的战略以提高绩效。工作人员数量不足、技能水平低下、资金延迟以及地理条件具有挑战性是绩效不佳的主要促成因素。
需要在卫生机构层面进行定量指标分析，以便了解地区层面的绩效。通过关键信息提供者访谈对绩效进行解读，为影响卫生服务提供绩效的先前未记录的背景因素提供了有用的见解。这种顺序解释性混合方法设计可应用于类似背景下其他卫生服务提供项目的评估。
