IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0211262.html
   My bibliography  Save this article

Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia

Author

Listed:
  • Dhruv Grover
  • Sebastian Bauhoff
  • Jed Friedman

Abstract

Independent verification is a critical component of performance-based financing (PBF) in health care, in which facilities are offered incentives to increase the volume of specific services but the same incentives may lead them to over-report. We examine alternative strategies for targeted sampling of health clinics for independent verification. Specifically, we empirically compare several methods of random sampling and predictive modeling on data from a Zambian PBF pilot that contains reported and verified performance for quantity indicators of 140 clinics. Our results indicate that machine learning methods, particularly Random Forest, outperform other approaches and can increase the cost-effectiveness of verification activities.

Suggested Citation

  • Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2019. "Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0211262
    DOI: 10.1371/journal.pone.0211262
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211262
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0211262&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0211262?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Adrien Renaud, 2013. "Verification of Performance in Result-Based Financing (RBF): The Case of Burundi," Health, Nutrition and Population (HNP) Discussion Paper Series 86190, The World Bank.
    2. Gerard La Forgia & Somil Nagpal, 2012. "Government-Sponsored Health Insurance in India : Are You Covered?," World Bank Publications - Books, The World Bank Group, number 11957.
    3. Petra Vergeer & Anna Heard & Erik Josephson & Lisa Fleisher, 2016. "Verification in results-based financing for health," Health, Nutrition and Population (HNP) Discussion Paper Series 112342, The World Bank.
    4. György Bèla Fritsche & Robert Soeters & Bruno Meessen, 2014. "Performance-Based Financing Toolkit [Boîte à outils : Financement basé sur la performance]," World Bank Publications - Books, The World Bank Group, number 17194.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dayashankar Maurya, 2019. "Understanding public health insurance in India: A design perspective," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(4), pages 1633-1650, October.
    2. Lannes, Laurence, 2015. "Improving health worker performance: The patient-perspective from a PBF program in Rwanda," Social Science & Medicine, Elsevier, vol. 138(C), pages 1-11.
    3. Manuela De Allegri & Swati Srivastava & Christoph Strupat & Stephan Brenner & Divya Parmar & Diletta Parisi & Caitlin Walsh & Sahil Mahajan & Rupak Neogi & Susanne Ziegler & Sharmishtha Basu & Nishant, 2020. "Mixed and Multi-Methods Protocol to Evaluate Implementation Processes and Early Effects of the Pradhan Mantri Jan Arogya Yojana Scheme in Seven Indian States," IJERPH, MDPI, vol. 17(21), pages 1-15, October.
    4. Lohmann, Julia & Houlfort, Nathalie & De Allegri, Manuela, 2016. "Crowding out or no crowding out? A Self-Determination Theory approach to health worker motivation in performance-based financing," Social Science & Medicine, Elsevier, vol. 169(C), pages 1-8.
    5. Indrani Gupta, 2015. "Financing for Health Coverage in India: Issues and Concerns," Working Papers id:7008, eSocialSciences.
    6. Chatterjee, Chirantan & Kubo, Kensuke & Pingali, Viswanath, 2015. "The consumer welfare implications of governmental policies and firm strategy in markets for medicines," Journal of Health Economics, Elsevier, vol. 44(C), pages 255-273.
    7. Carmen Carpio & Natalia Santiago Bench, 2015. "The Health Workforce in Latin America and the Caribbean," World Bank Publications - Books, The World Bank Group, number 22027.
    8. Eelco Jacobs & Maria Paola Bertone & Jurrien Toonen & Ngozi Akwataghibe & Sophie Witter, 2020. "Performance-Based Financing, Basic Packages of Health Services and User-Fee Exemption Mechanisms: An Analysis of Health-Financing Policy Integration in Three Fragile and Conflict-Affected Settings," Applied Health Economics and Health Policy, Springer, vol. 18(6), pages 801-810, December.
    9. Navneet Manchanda & Dil Bahadur Rahut, 2021. "Inpatient Healthcare Financing Strategies: Evidence from India," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 33(6), pages 1729-1767, December.
    10. Rajat Deb & Tapash Paul & Jaharlal Debbarma & Kiran Sankar Chakraborty, 2020. "Breaking the Stigma of Health Insurance," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 45(1), pages 54-84, February.
    11. Barnes, Kayleigh & Mukherji, Arnab & Mullen, Patrick & Sood, Neeraj, 2017. "Financial risk protection from social health insurance," Journal of Health Economics, Elsevier, vol. 55(C), pages 14-29.
    12. Bonfrer, Igna & Van de Poel, Ellen & Van Doorslaer, Eddy, 2014. "The effects of performance incentives on the utilization and quality of maternal and child care in Burundi," Social Science & Medicine, Elsevier, vol. 123(C), pages 96-104.
    13. Malani, Anup & Holtzman, Phoebe & Imai, Kosuke & Kinnan, Cynthia & Miller, Morgen & Swaminathan, Shailender & Voena, Alessandra & Woda, Bartek & Conti, Gabriella, 2021. "Effect of Health Insurance in India: A Randomized Controlled Trial," IZA Discussion Papers 14913, Institute of Labor Economics (IZA).
    14. Lohmann, Julia & Muula, Adamson S. & Houlfort, Nathalie & De Allegri, Manuela, 2018. "How does performance-based financing affect health workers' intrinsic motivation? A Self-Determination Theory-based mixed-methods study in Malawi," Social Science & Medicine, Elsevier, vol. 208(C), pages 1-8.
    15. Sulakshana Nandi & Helen Schneider & Priyanka Dixit, 2017. "Hospital utilization and out of pocket expenditure in public and private sectors under the universal government health insurance scheme in Chhattisgarh State, India: Lessons for universal health cover," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-18, November.
    16. Julia Ngozi Chukwuma, 2023. "Implementing Health Policy in Nigeria: The Basic Health Care Provision Fund as a Catalyst for Achieving Universal Health Coverage?," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1480-1503, November.
    17. Saleema Razvi & Amir Ullah Khan, 2015. "Health Financing in South Asia—The Role of Public–Private Partnerships," South Asian Survey, , vol. 22(1), pages 15-36, March.
    18. Arindam Nandi & Ashvin Ashok & Ramanan Laxminarayan, 2013. "The Socioeconomic and Institutional Determinants of Participation in India’s Health Insurance Scheme for the Poor," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-13, June.
    19. Azam, Mehtabul, 2018. "Does Social Health Insurance Reduce Financial Burden? Panel Data Evidence from India," World Development, Elsevier, vol. 102(C), pages 1-17.
    20. Ryoko Sato & Yoshito Takasaki, 2019. "Psychic vs. Economic Barriers to Vaccine Take-Up: Evidence from a Field Experiment in Nigeria," The World Bank Economic Review, World Bank, vol. 33(3), pages 622-642.

    More about this item

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    Statistics

    Access and download statistics

    Corrections

    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:plo:pone00:0211262. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.