James Cook University ISSN 1445-6354
Background: 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 which affect performance. A mixed methods study was undertaken to understand the contextual factors that affect health service performance.
Methods: 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 where 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.
Results: 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.
Conclusion: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.