Background: In 2012, the National Department of Health in South Africa started contracting of private medical practitioners (MPs) as part of the first phase of National Health Insurance (NHI) in 11 pilot districts to improve access to healthcare. Aim: The aim of this study was to describe the effect of contracting private MPs on the utilisation of primary healthcare (PHC) services in public healthcare facilities. Setting: A National Health Insurance pilot district compared to a non-pilot district. Methods: A quasi-experimental ecological study design was used to compare selected PHC utilisation indicators in the District Health Management Information System from June 2010 to May 2014 between a pilot and a non-pilot district. Both single and controlled interrupted time series analyses were used for comparing before and after implementation of the intervention. Findings: Single interrupted time series analysis showed an increase in adults remaining on anti-retroviral therapy, clients seen by a nurse practitioner and clients 5 years of age and older in both districts. However, controlled interrupted time series analysis found no difference in all parametres. Despite a decrease in total headcounts in both districts using single interrupted time series analysis, controlled interrupted time series analysis found no differences in all parameters before and after the intervention. Conclusions: The increase in utilisation of PHC services in the pilot district may not be attributable to the implementation of contracting private MPs, but likely the result of other healthcare reforms and transitions taking place in both districts around the same time.
We adopted a quasi-experimental ecological study to investigate the causal effect of private MPs contracting on utilisation of PHC services of the NHI pilot programme in a pilot NHI district by comparing utilisation of PHC services with a non-NHI pilot district. The study was conducted in one of the NHI pilot districts of South Africa, which has a population of 2 921 488 people, receiving PHC services from 68 facilities (PHC facility ratio of 1:36 980). The estimated medical scheme coverage in the district at the time of the study was 33.2%, and the Department of Health (DoH) expenditure on PHC was 56.7%.21 It is also the most diverse district in terms of socio-economic status of the population. The findings were compared with those in a non-NHI district with a population of 3 178 470 people accessing 90 PHC facilities (PHC facility ratio of 1:42 421). The estimated medical scheme coverage was 25.5% and DoH expenditure on PHC services was 83.1%.21 Selection of comparison district was not only based on proximity of the two districts but also on similarities in demographic profiles, being under the same provincial government and uniformity in the implementation of health programmes. The districts also have a similar burden of disease profile as measured by death by broad cause, namely, injuries, non-communicable diseases, HIV, TB and communicable diseases.22 We studied the population of children above 5 years old and adults utilising public PHC facilities in an NHI pilot and a non-NHI district from June 2010 to May 2014. However, PHC clients utilising services less likely to be affected by the presence of MPs at the community clinics (nurse-driven services), such as maternal, child health and reproductive services, were excluded from the study.23 In this study, we used routinely collected secondary data. District Health Management Information System monthly reports from June 2010 to May 2014 for the two districts were collated. Each PHC facility in the district collected data and sent them to a DHMIS officer, who created electronic formats (in Microsoft Excel). Data in DHMIS were deemed complete for the selected variables as the values for the elements were reported monthly for the period of the study. We used PHC headcounts because PHC is the focus of the implementation of the first phase of the NHI pilot programme. The complete list of variables, definitions, use, impact model and mechanism of the impact model is shown in Table 1. Definitions and impact model of primary healthcare data elements and indicators in District Health Management Information System. PHC, primary healthcare; ART, anti-retroviral therapy; MP, medical practitioner. The use of a comparison district was done to control for time varying confounders. Interrupted time series analysis (ITSA) compared selected PHC data elements across time within the single population of an NHI pilot district accounting for underlying trends in the outcomes, which avoids between-group differences such as selection bias of unmeasured confounders. However, this did not exclude confounders, which do not form part of the underlying trend, such as interventions or events occurring around the time of the NHI pilot project. To limit these threats, we selected a control district of a non-NHI pilot district to control for other examples of time varying co-interventions implemented in both districts that could affect the outcomes. The selection of variables and time points was based on requirements of analysis using both single and controlled ITSA.24 We measured and compared selected monthly PHC headcounts in the two districts, which met the criteria of ability to change relatively quickly after the implementation of MPs contracting or after a clearly defined lag.24,25 The unit measure for selected data points was months as per DHMIS reporting. A total of 48 time periods, with 24 before (June 2010 to May 2012) and 24 after (June 2012 to May 2014) implementation of contracting MPs, were selected. The minimum required for ITSA is 10 before and 10 after implementation of a programme to have at least 80% power. The selection can detect a change level of at least 5 standard deviations of the pre-data if the autocorrelation is > 0.4.26
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