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Assessing primary care performance in Indonesia: An application of frontier analysis techniques


  • Firdaus Hafidz

    () (Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)

  • Tim Ensor

    (Leeds Institute of Health Sciences, University of Leeds)

  • Sandy Tubeuf

    (Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)


Despite increased national health expenditure in health facilities in Indonesia, health outcomes remain low. The aim of our study is to examine the factors determining the relative efficiency of public primary care facilities. Using linked national data sources from facility-, households, and village-based surveys, we measure the efficiency of 185 primary care facilities across fifteen provinces in Indonesia with output oriented data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Inputs include the number of doctors, midwife and nurses, and other staff while outputs are the number of outpatients and maternal child health patients. We run truncated regression in second stage DEA and one stage SFA analysis to assess contextual characteristics influencing health facilities performance. Our results indicate a wide variation in efficiency between health facilities. High-performing primary care facilities are in affluent areas. Primary care facilities located in urban areas, in Java and Bali Island, with high coverage of insurance scheme for the poor perform better than other geographical location.We find an inconclusive impact of quality of care, patient mix, and availability of inpatient services on efficiency. This paper concludes by highlighting the characteristics of primary care facilities that have the potential to increase efficiency.

Suggested Citation

  • Firdaus Hafidz & Tim Ensor & Sandy Tubeuf, 2017. "Assessing primary care performance in Indonesia: An application of frontier analysis techniques," Working Papers 1703, Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds.
  • Handle: RePEc:lee:wpaper:1703

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    More about this item


    Efficiency; Primary care facilities; frontier analysis; data envelopment analysis; stochastic frontier analysis; Indonesia;

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General

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