IDEAS home Printed from
   My bibliography  Save this paper

Technical Efficiency of Provincial Public Healthcare in South Africa


  • Victor Ngobeni

    () (Department of Economics, University of Pretoria. Address: University of Pretoria. Lynnwood Rd, Hatfield, Pretoria, 0002)

  • Marthinus C. Breitenbach

    (Department of Economics, University of Pretoria. Address: University of Pretoria. Lynnwood Rd, Hatfield, Pretoria, 0002)

  • Goodness C. Aye

    (Department of Economics, University of Pretoria. Address: University of Pretoria. Lynnwood Rd, Hatfield, Pretoria, 0002)


Forty-nine million people or 83 per cent of the entire population of 59 million rely on the public healthcare system in South Africa. Coupled with a shortage of medical professionals, high migration, inequality and unemployment; healthcare provision is under extreme pressure. Due to negligence by the health professionals, provincial health departments had medical-legal claims estimated at R80 billion in 2017/18. In the same period, provincial health spending accounted for 33 per cent of total provincial expenditure of R570.3 billion or 6 per cent of South Africa’s Gross Domestic Product. Despite this, healthcare outcomes are poor and provinces are inefficient in the use of the allocated funds. This warrants a scientific investigation into the technical efficiency of the public health system. The study uses Data Envelopment Analysis (DEA) to assess the technical efficiency of the nine South African provinces in the provision of healthcare. This is achieved by determining, assessing and comparing ways that individual provinces can benchmark their performance against peers to improve efficiency scores. DEA compares firms operating in homogenous conditions in the usage of multiple inputs to produce multiple outputs. Therefore, DEA is ideal for measuring the technical efficiency of provinces in the provision of public healthcare. In DEA methodology, the firms with scores of 100 per cent are technically efficient and those with scores lower than 100 per cent are technically inefficient. This study considers six DEA models using the 2017/18 total health spending and health staff as inputs and the infant mortality rate as an output. The first three models assume the constant returns to scale (CRS) while the last three use the variable return to scale (VRS) both with an input-minimisation objective. The study found the mean technical efficiency scores ranging from 35.7 to 87.2 per cent between the Health Models 1 and 6. Therefore, inefficient provinces could improve the use of inputs within a range of 64.3 and 20.8 per cent. The Gauteng province defines the technical efficiency frontiers in all the six models. The second-best performing province is the North West province. Other provinces like KwaZulu-Natal, Limpopo and the Eastern Cape only perform well under the VRS. The other three provinces are inefficient. Based on the VRS Models 4 to 6, the study presents three policy options. Policy option 1 (Model 4): the efficiency gains from addressing health expenditure wastage in four inefficient provinces amounts to R17 billion. Policy option 2 (Model 5): the potential savings from the same provinces could be obtained from reducing 17 000 health personnel, advisably, in non-core areas. In terms of Policy option 3 (Model 6), three inefficient provinces should reduce 6 940 health workers while the same provinces, inclusive of KwaZulu-Natal could realise health expenditure savings of R61 million. The potential resource savings from improving the efficiency of the inefficient provinces could be used to refurbish and build more hospitals to alleviate pressure on the public health system. This could also reduce the per capita numbers per public hospital and perhaps their performance as overcrowding is reportedly negatively affecting their performance and health outcomes. The potential savings could also be used to appoint and train medical practitioners, specialists and researchers to reduce the alarming numbers of medical legal claims. Given the existing challenges, South Africa is not ready to implement the National Health Insurance (NHI) Scheme, as it requires additional financial and human resources. Instead, huge improvements in public healthcare provision could be achieved by re-allocating the resources ‘saved’ through efficiency measures by increasing the quality of public healthcare and extending healthcare to more recipients.

Suggested Citation

  • Victor Ngobeni & Marthinus C. Breitenbach & Goodness C. Aye, 2020. "Technical Efficiency of Provincial Public Healthcare in South Africa," Working Papers 202013, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:202013

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    2. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    3. Asandului, Laura & Roman, Monica & Fatulescu, Puiu, 2013. "The Efficiency of Healthcare Systems in Europe: a Data Envelopment Analysis Approach," MPRA Paper 58954, University Library of Munich, Germany, revised Apr 2014.
    4. Brenda Gannon, 2005. "Testing for Variation in Technical Efficiency of Hospitals in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 36(3), pages 273-294.
    5. H. Chowdhury & V. Zelenyuk & W. Wodchis & A. Laporte, 2010. "Efficiency and Technological Change in Health Care Services in Ontario," CEPA Working Papers Series WP082010, School of Economics, University of Queensland, Australia.
    6. Livia Baciu & Alina Botezat, 2014. "A Comparative Analysis of the Public Spending Efficiency of the New EU Member States: A DEA Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(S4), pages 31-46.
    7. Varabyova, Yauheniya & Schreyögg, Jonas, 2013. "International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches," Health Policy, Elsevier, vol. 112(1), pages 70-79.
    8. Aristovnik, Aleksander, 2012. "The impact of ICT on educational performance and its efficiency in selected EU and OECD countries: a non-parametric analysis," MPRA Paper 39805, University Library of Munich, Germany.
    9. Eric Wang & Eskander Alvi, 2011. "Relative Efficiency of Government Spending and Its Determinants: Evidence from East Asian Countries," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 1(1), pages 3-28, June.
    10. Lavado, Rouselle & Domingo, Gabriel Angelo, 2015. "Public Service Spending: Efficiency and Distributional Impact—Lessons from Asia," ADB Economics Working Paper Series 435, Asian Development Bank.
    11. Andrés Ramírez Hassan, 2008. "Consequences of omitting relevant inputs on the quality of the data envelopment analysis under different input correlation structures," Documentos de Trabajo CIEF 010627, Universidad EAFIT.
    12. Anton Sorin Gabriel, 2013. "Technical Efficiency in the Use of Health Care Resources: A Cross-Country Analysis," Scientific Annals of Economics and Business, Sciendo, vol. 60(1), pages 1-12, July.
    13. Gabriel Angelo Domingo & Rouselle F. Lavado, 2015. "Public Service Spending: Efficiency and Distributional Impact—Lessons from Asia," Working Papers id:7108, eSocialSciences.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Expenditure; Data Envelopment Analysis; Healthcare; Inefficiency; Technical Efficiency;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D2 - Microeconomics - - Production and Organizations
    • I1 - Health, Education, and Welfare - - Health


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:202013. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rangan Gupta). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.