IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v268y2021ics027795362030770x.html
   My bibliography  Save this article

Pay-for-performance reduces bypassing of health facilities: Evidence from Tanzania

Author

Listed:
  • Bezu, Sosina
  • Binyaruka, Peter
  • Mæstad, Ottar
  • Somville, Vincent

Abstract

Many patients and expectant mothers in low-income countries bypass local health facilities in search of better-quality services. This study examines the impact of a payment-for-performance (P4P) scheme on bypassing practices among expectant women in Tanzania. We expect the P4P intervention to reduce incidences of bypassing by improving the quality of services in local health facilities, thereby reducing the incentive to migrate. We used a difference-in-difference regression model to assess the impact of P4P on bypassing after one year and after three years. In addition, we implemented a machine learning approach to identify factors that predict bypassing. Overall, 38% of women bypassed their local health service provider to deliver in another facility. Our analysis shows that the P4P scheme significantly reduced bypassing. On average, P4P reduced bypassing in the study area by 17% (8 percentage points) over three years. We also identified two main predictors of bypassing - facility type and the distance to the closest hospital. Women are more likely to bypass if their local facility is a dispensary instead of a hospital or a health center. Women are less likely to bypass if they live close to a hospital.

Suggested Citation

  • Bezu, Sosina & Binyaruka, Peter & Mæstad, Ottar & Somville, Vincent, 2021. "Pay-for-performance reduces bypassing of health facilities: Evidence from Tanzania," Social Science & Medicine, Elsevier, vol. 268(C).
  • Handle: RePEc:eee:socmed:v:268:y:2021:i:c:s027795362030770x
    DOI: 10.1016/j.socscimed.2020.113551
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S027795362030770X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.socscimed.2020.113551?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    2. Gauthier, Bernard & Wane, Waly, 2011. "Bypassing health providers: The quest for better price and quality of health care in Chad," Social Science & Medicine, Elsevier, vol. 73(4), pages 540-549, August.
    3. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    4. Kenneth L. Leonard & Gilbert R. Mliga & Damen Haile Mariam, 2002. "Bypassing Health Centres in Tanzania: Revealed Preferences for Quality," Journal of African Economies, Centre for the Study of African Economies, vol. 11(4), pages 441-471, December.
    5. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
    6. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    7. Rao, Krishna D. & Sheffel, Ashley, 2018. "Quality of clinical care and bypassing of primary health centers in India," Social Science & Medicine, Elsevier, vol. 207(C), pages 80-88.
    8. Peter Binyaruka & Edith Patouillard & Timothy Powell-Jackson & Giulia Greco & Ottar Maestad & Josephine Borghi, 2015. "Effect of Paying for Performance on Utilisation, Quality, and User Costs of Health Services in Tanzania: A Controlled Before and After Study," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-16, August.
    9. James G. MacKinnon & Matthew D. Webb, 2019. "Wild Bootstrap Randomization Inference for Few Treated Clusters," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 61-85, Emerald Group Publishing Limited.
    10. Kruk, M.E. & Paczkowski, M. & Mbaruku, G. & De Pinho, H. & Galea, S., 2009. "Women's preferences for place of delivery in rural Tanzania: A population-based discrete choice experiment," American Journal of Public Health, American Public Health Association, vol. 99(9), pages 1666-1672.
    11. 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, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thorsen, Maggie L. & Harris, Sean & Palacios, Janelle F. & McGarvey, Ronald G. & Thorsen, Andreas, 2023. "American Indians travel great distances for obstetrical care: Examining rural and racial disparities," Social Science & Medicine, Elsevier, vol. 325(C).

    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. Damian Clarke & Kathya Tapia-Schythe, 2021. "Implementing the panel event study," Stata Journal, StataCorp LP, vol. 21(4), pages 853-884, December.
    2. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    3. Dorner, Matthias & Görlitz, Katja, 2020. "Training, wages and a missing school graduation cohort," IAB-Discussion Paper 202028, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Testing for the appropriate level of clustering in linear regression models," Journal of Econometrics, Elsevier, vol. 235(2), pages 2027-2056.
    5. Ban, Radu & Gilligan, Michael J. & Rieger, Matthias, 2020. "Self-help groups, savings and social capital: Evidence from a field experiment in Cambodia," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 174-200.
    6. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Wild Bootstrap and Asymptotic Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 505-519, March.
    7. Buenstorf, Guido & Koenig, Johannes, 2020. "Interrelated funding streams in a multi-funder university system: Evidence from the German Exzellenzinitiative," Research Policy, Elsevier, vol. 49(3).
    8. Jalil, Andrew J. & Tasoff, Joshua & Bustamante, Arturo Vargas, 2020. "Eating to save the planet: Evidence from a randomized controlled trial using individual-level food purchase data," Food Policy, Elsevier, vol. 95(C).
    9. Blake Shaffer, 2019. "Location matters: Daylight saving time and electricity demand," Canadian Journal of Economics, Canadian Economics Association, vol. 52(4), pages 1374-1400, November.
    10. Carpenter, Christopher S. & Gonzales, Gilbert & McKay, Tara & Sansone, Dario, 2020. "Effects of the Affordable Care Act Dependent Coverage Mandate on Health Insurance Coverage for Individuals in Same-Sex Couples," IZA Discussion Papers 13119, Institute of Labor Economics (IZA).
    11. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
    12. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.
    13. Arrieta Vidal, Johar & Florián Hoyle, David & López Vargas, Kristian & Morales Vásquez, Valeria, 2022. "Policies for transactional de-dollarization: A laboratory study," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 31-54.
    14. MacKinnon, James G., 2023. "Fast cluster bootstrap methods for linear regression models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 52-71.
    15. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    16. García-Ramos, Aixa, 2021. "Divorce laws and intimate partner violence: Evidence from Mexico," Journal of Development Economics, Elsevier, vol. 150(C).
    17. Lauren E. Jones & Kevin Milligan & Mark Stabile, 2019. "Child cash benefits and family expenditures: Evidence from the National Child Benefit," Canadian Journal of Economics, Canadian Economics Association, vol. 52(4), pages 1433-1463, November.
    18. Obergruber, Natalie & Zierow, Larissa, 2020. "Students’ behavioural responses to a fallback option - Evidence from introducing interim degrees in german schools," Economics of Education Review, Elsevier, vol. 75(C).
    19. Jan Stede & Nils May, 2020. "Way Off: The Effect of Minimum Distance Regulation on the Deployment of Wind Power," Discussion Papers of DIW Berlin 1867, DIW Berlin, German Institute for Economic Research.
    20. Ozturk, Orgul D. & Frongillo, Edward A. & Blake, Christine E. & McInnes, Melayne M. & Turner-McGrievy, Gabrielle, 2020. "Before the lunch line: Effectiveness of behavioral economic interventions for pre-commitment on elementary school children's food choices," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 597-618.

    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:eee:socmed:v:268:y:2021:i:c:s027795362030770x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.