Development of a composite indicator of maternal and child health performance among districts in South Africa

Abstract

Introduction: South Africa has performed poorly in maternal and child health, even though it has greater resources available for health care than many other developing countries. A functioning district health system is essential if South Africa is to improve maternal and child health and to achieve its goal of “A Long and Healthy Life for All South Africans”. Currently district health performance data are presented by the District Health Barometer (DHB) on 46 individual health related indicators. Because district performance varies for different indicators it is difficult in this analysis to assess overall district performance and to clearly distinguish better-functioning districts from those that are under-performing. This study explored the development of a composite index from the DHB indicators to compare district performance in maternal and child health. The association of this composite measure of performance with district level financing and deprivation was also explored. Materials and methods: This was a secondary data analysis study using 18 maternal and child indicators from the DHB for all 52 districts of South Africa for the three year period from 2011/12 to 2013/14. Variation was explored across districts, across time and across provinces for the district indicators using summary statistics and graphs. Principal component analysis (PCA) was then used to develop a composite index of performance and the districts were ranked according to this index. Finally, linear regression was used to evaluate the relationship between the composite performance index, and indicators of district deprivation and public health financing. Results: We found significant variation between districts, between provinces and over time. The variation however was inconsistent, with districts performing well on some indicators and poorly on others. The PCA identified five components with eigenvalues greater than one, explaining 72% of the total variation. The factor loadings of the first component were used to create the composite index. Districts were ranked according to the composite principal component (PC) score. The regression analysis found a significant relationship with the PC score and the deprivation and DHS per capita expenditure indicators. Discussion: This study found that multivariate statistical methods may be useful in summarising and evaluating health system performance across a range of maternal and child health indicators. The PCA analysis reduced the number of variables from 18 indicators to one PC score, and allowed us to rank districts by performance. However, the principal component extracted did not identify clear constructs related to maternal and child health performance. Limitations of this study include the uncertain quality of the primary data, and the limited variables available in the DHB to assess performance. Conclusion: Methods for creating composite indices to summarise performance across a range of health indicators require more attention. Future research could explore alternative methods using the DHB dataset. Frontier analyses, such as data envelopment analysis, which evaluate performance relative to the inputs used, may be more appropriate if relevant inputs can be identified and measured.