Evaluating the Quality of National Mortality Statistics from Civil Registration in South Africa, 1997–2007

Abstract

BackgroundTwo World Health Organization comparative assessments rated the quality of South Africa’s 1996 mortality data as low. Since then, focussed initiatives were introduced to improve civil registration and vital statistics. Furthermore, South African cause-of-death data are widely used by research and international development agencies as the basis for making estimates of cause-specific mortality in many African countries. It is hence important to assess the quality of more recent South African data.MethodsWe employed nine criteria to evaluate the quality of civil registration mortality data. Four criteria were assessed by analysing 5.38 million deaths that occurred nationally from 1997–2007. For the remaining five criteria, we reviewed relevant legislation, data repositories, and reports to highlight developments which shaped the current status of these criteria.FindingsNational mortality statistics from civil registration were rated satisfactory for coverage and completeness of death registration, temporal consistency, age/sex classification, timeliness, and sub-national availability. Epidemiological consistency could not be assessed conclusively as the model lacks the discriminatory power to enable an assessment for South Africa. Selected studies and the extent of ill-defined/non-specific codes suggest substantial shortcomings with single-cause data. The latter criterion and content validity were rated unsatisfactory.ConclusionIn a region marred by mortality data absences and deficiencies, this analysis signifies optimism by revealing considerable progress from a dysfunctional mortality data system to one that offers all-cause mortality data that can be adjusted for demographic and health analysis. Additionally, timely and disaggregated single-cause data are available, certified and coded according to international standards. However, without skillfully estimating adjustments for biases, a considerable confidence gap remains for single-cause data to inform local health planning, or to fill gaps in sparse-data countries on the continent. Improving the accuracy of single-cause data will be a critical contribution to the epidemiologic and population health evidence base in Africa.

Child mortality in South Africa: Fewer deaths, but better data are needed

“…However, levels of completeness in children are uncertain. [11] Provides only national estimates (not disaggregated to sub-national level).…”

“…However, the levels of completeness for children are uncertain. [11] Demographic and Health Survey (DHS) [13] National household survey to identify demographic characteristics and define key health indicators. [19] The infant mortality rate followed a similar pattern as the under-5 mortality rate, with the UN reporting an infant mortality rate of 33.6 per 1 000 live births in 2015, while the RMS reported a figure of 27 per 1 000 live births.…”

“…They are then sent to StatsSA where the data are captured, collated, analysed and published annually. [11] Data for reported deaths may be incomplete. Delay of ~2 years before data are published.…”

“…There were also large differences in KwaZulu-Natal and Mpumalanga, which, like the Eastern Cape, have large underserved rural populations where incomplete VR would be expected. [11,23] Deaths inside and outside of the health system Just over half (50.9%) of all under-5 deaths in the VR system were reported to have occurred within health facilities in 2015 (Table 4). The lowest proportion was reported in the Eastern Cape (43.5%) and the highest proportion in the Northern Cape (67.7%).…”

Medical certification of death in South Africa – moving forward

“…[2,3] In a recent evaluation, Joubert et al [4] found that the extent to which certification and coding of conditions accurately reflected causes of death was unsatisfactory. Despite the high prevalence of HIV (estimated to be 12.2% in 2012), [5] according to official statistics, HIV only accounted for 3.4% of deaths nationally in 2010, [6] indicating gross under-reporting.…”