Research Article: The impact of family physician supply on district health system performance, clinical processes and clinical outcomes in the Western Cape Province, South Africa (2011–2014)

Date Published: April 19, 2018

Publisher: AOSIS

Author(s): Rekai L. Chinhoyi, Moleen Zunza, Klaus B. von Pressentin.

http://doi.org/10.4102/phcfm.v10i1.1442

Abstract

A revised family physician (FP) training programme was introduced in South Africa in 2007. A baseline assessment (2011) of the impact of FP supply on district health system performance was performed within the Western Cape Province, South Africa. The impact of an increased FP supply within this province required re-evaluation.

To assess the impact of FP supply on indicators of district health system performance, clinical processes and clinical outcomes in the Western Cape Province. The objectives were to determine the impact of FPs, nurses, medical officers (MOs) and other specialists.

The study sample included all five rural districts and eight urban subdistricts of the Western Cape Province.

A secondary analysis was performed on routinely collected data from the Western Cape Department of Health from 01 March 2011 until 30 April 2014.

The FP supply did not significantly impact the indicators analysed. The supply of nurses and MOs had an impact on some of the indicators analysed.

This study did not replicate the positive associations between an increase in FP supply and improved health indicators, as described previously for high-income country settings. The impact of FP supply on clinical processes, health system performance and outcome indicators in the Western Cape Province was not statistically significant. Future re-evaluation is recommended to allow for more time and an increase in FP supply.

Partial Text

The World Health Organization (WHO) defines primary health care (PHC) as ‘essential health care’ that is based on scientifically sound and socially acceptable methods and technology. Primary health care is an aspect of health care that facilitates population access to health services through universal health care coverage of individuals, families and communities.1

All 13 districts and subdistricts of the Western Cape were included as the units of analysis for this study. The total populations and dependent populations of these districts are described in Table 1. The full-time equivalent distribution of FPs and other health care categories per district or subdistrict is summarised in the appendix as Table 2-A1. Bivariate analysis was used to assess the impact of time on each health care indicator or outcome (2011–2014) and to adjust for within district or subdistrict clustering (Table 4). Outcome variables that significantly changed over the reporting period (p < 0.1) underwent further bivariate analysis with each predictor variable whilst the effects of time were held constant (Table 5). The primary objective of this study was to determine the impact of FPs on designated PHC indicators in the district health system of the Western Cape. Bivariate analysis of the impact of FPs, the primary objective, indicated that FPs did not have a significant impact on the indicators assessed in this study. This may be explained by the fact that the FP supply is still too low to have made a significant impact on these health indicators, even though it has doubled over the past 4 years.12 The strengths of this study included finite sampling which ensured that all Western Cape districts were included and represented in the study, thereby reducing the potential for selection bias.25 The high response rate (100%) ensured that sampling had no impact on the validity of the inferences made. Moreover, the study procedures, inclusion and exclusion criteria were uniform across districts and sub-districts, thereby reducing systematic selection bias or differential misclassification of districts. Furthermore, the study outcomes were clearly defined and objectively measured using data from DHIS. The use of generalised linear models using multivariate binomial and negative binomial regression ensured that potential confounders such as the supply of other health care categories (i.e. nurses, MOs and specialists) were adjusted for during the analysis. Because of the fact that there were only four data points measured for the dependent variables in the available data set, no district by district analysis could be performed. Furthermore, some outcomes specified in the original study protocol and baseline study by Dyers et al., such as TB cure, diabetes score, hypertension score, hospital expenditure and chronic care team coordination, could not be measured.8 The cause-and-effect relationship between FP supply and DHS could not be determined in terms of temporality. A follow-up study at 10 years or more when the newly trained FPs have matured in their role and their numbers have increased is recommended.26 In addition, a nationwide study including more districts and more FPs may increase the sample size and thereby increase the power of the study. This study did not replicate the positive associations between an increase in FP supply and improved health indicators, as described by Starfield and others in studies conducted across 19 countries, which revealed that a one unit increase in primary care physician supply resulted in improvements in all health outcomes.26,27,28 In this study, the supply of FP had no statistically significant impact on the indicators used to measure health system performance and clinical outcomes. This discrepancy may be attributed to the low supply and relatively shorter duration of FP supply within this South African province. The ongoing analysis of the impact of FPs on district health outcomes is recommended to allow for more time and an increase in FP supply.   Source: http://doi.org/10.4102/phcfm.v10i1.1442

 

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