Re-aligning Incentives to Address Informal Payments in Tanzania Public Health Facilities: A Discrete Choice Experiment

Document Type : Original Article


1 Department of Health System, Impact Evaluation and Policy, Ifakara Health Institute, Dar es Salaam, Tanzania

2 Department of Economics, SOAS University of London, London, UK

3 South African Research Chair in Industrial Development, University of Johannesburg, Johannesburg, South Africa

4 Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK

5 The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia


Informal payments for healthcare are typically regressive and limit access to quality healthcare while increasing risk of catastrophic health expenditure, especially in developing countries. Different responses have been proposed, but little is known about how they influence the incentives driving this behaviour. We therefore identified providers’ preferences for policy interventions to overcome informal payments in Tanzania.

We undertook a discrete choice experiment (DCE) to elicit preferences over various policy options with 432 health providers in 42 public health facilities in Pwani and Dar es Salaam region. DCE attributes were derived from a multi-stage process including a literature review, qualitative interviews with key informants, a workshop with health stakeholders, expert opinions, and a pilot test. Each respondent received 12 unlabelled choice sets describing two hypothetical job-settings that varied across 6-attributes: mode of payment, supervision at facility, opportunity for private practice, awareness and monitoring, measures against informal payments, and incentive payments to encourage noninfraction. Mixed multinomial logit (MMNL) models were used for estimation.

All attributes, apart from supervision at facility, significantly influenced providers’ choices (P < .001). Health providers strongly and significantly preferred incentive payments for non-infraction and opportunities for private practice, but significantly disliked disciplinary measures at district level. Preferences varied across the sample, although all groups significantly preferred the opportunity to practice privately and cashless payment. Disciplinary measures at district level were significantly disliked by unit in-charges, those who never engaged in informal payments, and who were not absent from work for official trip. 10% salary top-up were preferred incentive by all, except those who engaged in informal payments and absent from work for official trip.

Better working conditions, with improved earnings and career paths, were strongly preferred by all, different respondents groups had distinct preferences according to their characteristics, suggesting the need for adoption of tailored packages of interventions.


  1. Lewis M. Informal payments and the financing of health care in developing and transition countries. Health Aff (Millwood). 2007;26(4):984-997. doi:1377/hlthaff.26.4.984
  2. Gaal P, Belli PC, McKee M, Szócska M. Informal payments for health care: definitions, distinctions, and dilemmas. J Health Polit Policy Law. 2006;31(2):251-293. doi:1215/03616878-31-2-251
  3. Savedoff WD. Transparency and Corruption in the Health Sector: A Conceptual Framework and Ideas for Action in Latin American and the Caribbean. Washington, DC: Inter-American Development Bank; 2007.
  4. Vian T. Review of corruption in the health sector: theory, methods and interventions. Health Policy Plan. 2008;23(2):83-94. doi:1093/heapol/czm048
  5. Ensor T, Witter S. Health economics in low income countries: adapting to the reality of the unofficial economy. Health Policy. 2001;57(1):1-13. doi:1016/s0168-8510(01)00125-7
  6. Hutchinson E, Balabanova D, McKee M. We need to talk about corruption in health systems. Int J Health Policy Manag. 2019;8(4):191-194. doi:15171/ijhpm.2018.123
  7. O'Donnell O. Access to health care in developing countries: breaking down demand side barriers. Cad Saude Publica. 2007;23(12):2820-2834. doi:1590/s0102-311x2007001200003
  8. Ensor T, Cooper S. Overcoming barriers to health service access: influencing the demand side. Health Policy Plan. 2004;19(2):69-79. doi:1093/heapol/czh009
  9. World Health Organization (WHO). The World Health Report: Health Systems Financing: The Path to Universal Coverage. Geneva, Switzerland: WHO; 2010.
  10. Hutchinson E, Naher N, Roy P, et al. Targeting anticorruption interventions at the front line: developmental governance in health systems. BMJ Glob Health. 2020;5(12):e003092. doi:1136/bmjgh-2020-003092
  11. Gaitonde R, Oxman AD, Okebukola PO, Rada G. Interventions to reduce corruption in the health sector. Cochrane Database Syst Rev. 2016(8):CD008856. doi:1002/14651858.CD008856.pub2
  12. Onwujekwe O, Orjiakor CT, Hutchinson E, et al. Where do we start? Building consensus on drivers of health sector corruption in Nigeria and ways to address it. Int J Health Policy Manag. 2020;9(7):286-296. doi:15171/ijhpm.2019.128
  13. Khan M, Andreoni A, Roy P. Anti-Corruption in Adverse Contexts: Strategies for Improving Implementation. Working Paper 013. London: SOAS University of London; 2019.
  14. Khan M. Political settlements and the analysis of institutions. Afr Aff (Lond). 2018;117(469):636-655. doi:1093/afraf/adx044
  15. Khan M. Beyond good governance: an agenda for developmental governance. In: Sundaram JK, Chowdhury A, eds. Is Good Governance Good for Development? London: Bloomsbury Academic; 2012:151-182.
  16. Behuria P, Buur L, Gray H. Studying political settlements in Africa. Afr Aff (Lond). 2017;116(464):508-525. doi:1093/afraf/adx019
  17. Andreoni A. Anti-Corruption in Tanzania: A Political Settlements Analysis. Working Paper 001. London: SOAS University of London; 2017.
  18. Ramesh M, Binyaruka P, Mamdani M, Balabanova D, Andreoni A, Hutchinson E. Exploring Informal Payments in Tanzania Health Sector: A Qualitative Study. In Press-SOAS Working Paper. London: SOAS University of London; 2021.
  19. Mangham LJ, Hanson K, McPake B. How to do (or not to do) ... Designing a discrete choice experiment for application in a low-income country. Health Policy Plan. 2009;24(2):151-158. doi:1093/heapol/czn047
  20. Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy. 2003;2(1):55-64.
  21. Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user's guide. Pharmacoeconomics. 2008;26(8):661-677. doi:2165/00019053-200826080-00004
  22. Clark MD, Determann D, Petrou S, Moro D, de Bekker-Grob EW. Discrete choice experiments in health economics: a review of the literature. Pharmacoeconomics. 2014;32(9):883-902. doi:1007/s40273-014-0170-x
  23. de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21(2):145-172. doi:1002/hec.1697
  24. Lagarde M, Blaauw D. A review of the application and contribution of discrete choice experiments to inform human resources policy interventions. Hum Resour Health. 2009;7:62. doi:1186/1478-4491-7-62
  25. Obadha M, Chuma J, Kazungu J, Abiiro GA, Beck MJ, Barasa E. Preferences of healthcare providers for capitation payment in Kenya: a discrete choice experiment. Health Policy Plan. 2020;35(7):842-854. doi:1093/heapol/czaa016
  26. Binyaruka P. Understanding public health providers’ preferences for interventions against informal payment in Tanzania: a discrete choice experiment. Eur J Public Health. 2020;30(Suppl 5):ckaa165-939. doi:1093/eurpub/ckaa165.939
  27. National Bureau of Statistics (NBS). Tanzania Population and Housing Census: Population Distribution by Administrative Areas 2012. Dar es Salaam: NBS; 2013.
  28. Ministry of Health and Social Welfare (MoHSW). Tanzania Health Sector Strategic Plan (HSSP IV) 2015-2020. Dar es Salaam: MoHSW; 2015.
  29. Wales J, Tobias J, Malangalila E, Swai G, Wild L. Stock-Outs of Essential Medicines in Tanzania: A Political Economy Approach to Analysing Problems and Identifying Solutions. Twaweza ni sisi; 2014.
  30. Afnan-Holmes H, Magoma M, John T, et al. Tanzania's countdown to 2015: an analysis of two decades of progress and gaps for reproductive, maternal, newborn, and child health, to inform priorities for post-2015. Lancet Glob Health. 2015;3(7):e396-409. doi:1016/s2214-109x(15)00059-5
  31. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC). Mid Term Review of the Health Sector Strategic Plan IV 2015-2020: Health Finance Technical Report. Tanzania: MoHCDGEC; 2019.
  32. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC). National Health Accounts (NHA) for Financial Years 2013/14, 2014/15 and 2015/16. Tanzania: MoHCDGEC; 2019.
  33. Maluka SO. Why are pro-poor exemption policies in Tanzania better implemented in some districts than in others? Int J Equity Health. 2013;12:80. doi:1186/1475-9276-12-80
  34. Kruk ME, Mbaruku G, Rockers PC, Galea S. User fee exemptions are not enough: out-of-pocket payments for 'free' delivery services in rural Tanzania. Trop Med Int Health. 2008;13(12):1442-1451. doi:1111/j.1365-3156.2008.02173.x
  35. Mæstad O, Mwisongo A. Informal payments and the quality of health care: mechanisms revealed by Tanzanian health workers. Health Policy. 2011;99(2):107-115. doi:1016/j.healthpol.2010.07.011
  36. Stringhini S, Thomas S, Bidwell P, Mtui T, Mwisongo A. Understanding informal payments in health care: motivation of health workers in Tanzania. Hum Resour Health. 2009;7:53. doi:1186/1478-4491-7-53
  37. Binyaruka P, Balabanova D, McKee M, et al. Supply-side factors influencing informal payment for healthcare services in Tanzania. Health Policy Plan. 2021;36(7):1036-1044. doi:1093/heapol/czab034
  38. Mamdani M, Kweka H, Binyaruka P, et al. Strengthening Accountability for Better Health Outcomes Through Understanding Health-System Bottlenecks: Insights from Tanzania. Working Paper 008. London: SOAS University of London; 2018.
  39. Ryan M, Kolstad JR, Rockers PC, Dolea C. How to Conduct a Discrete Choice Experiment for Health Workforce Recruitment and Retention in Remote and Rural Areas: A User Guide with Case Studies. Washington, DC: World Bank; 2012.
  40. Hensher DA, Rose JM, Greene WH. Applied Choice Analysis: A Primer. Cambridge: Cambridge University Press; 2005.
  41. de Bekker-Grob EW, Donkers B, Jonker MF, Stolk EA. Sample size requirements for discrete-choice experiments in healthcare: a practical guide. Patient. 2015;8(5):373-384. doi:1007/s40271-015-0118-z
  42. Orme B. Sample Size Issues for Conjoint Analysis. In: Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research. Madison, WI: Research Publishers LLC; 2006.
  43. Orme B. Sample Size Issues for Conjoint Analysis Studies. Sawtooth Software Research Paper Series. Sequim: Sawtooth Software; 1998.
  44. Blaauw D, Erasmus E, Pagaiya N, et al. Policy interventions that attract nurses to rural areas: a multicountry discrete choice experiment. Bull World Health Organ. 2010;88(5):350-356. doi:2471/blt.09.072918
  45. Louviere JJ, Hensher DA, Swait JD. Stated Choice Methods: Analysis and Applications. Cambridge: Cambridge University Press; 2000.
  46. Verbeek M. A Guide to Modern Econometrics. John Wiley & Sons; 2008.
  47. McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P, ed. Frontiers in Econometrics. Academic Press; 1974:105-142.
  48. Lancsar E, Fiebig DG, Hole AR. Discrete choice experiments: a guide to model specification, estimation and software. Pharmacoeconomics. 2017;35(7):697-716. doi:1007/s40273-017-0506-4
  49. Hole AR. Fitting mixed logit models by using maximum simulated likelihood. Stata J. 2007;7(3):388-401. doi:1177/1536867x0700700306
  50. Lancsar E, Louviere J, Flynn T. Several methods to investigate relative attribute impact in stated preference experiments. Soc Sci Med. 2007;64(8):1738-1753. doi:1016/j.socscimed.2006.12.007
  51. Hole AR. Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment. J Health Econ. 2008;27(4):1078-1094. doi:1016/j.jhealeco.2007.11.006
  52. Honda A, Vio F. Incentives for non-physician health professionals to work in the rural and remote areas of Mozambique--a discrete choice experiment for eliciting job preferences. Hum Resour Health. 2015;13:23. doi:1186/s12960-015-0015-5
  53. Hanson K, Jack W. Health Worker Preferences for Job Attributes in Ethiopia: Results from a Discrete Choice Experiment. Washington, DC: World Bank Group; 2007.
  54. Ferrinho P, Van Lerberghe W, Fronteira I, Hipólito F, Biscaia A. Dual practice in the health sector: review of the evidence. Hum Resour Health. 2004;2(1):14. doi:1186/1478-4491-2-14
  55. Bertone MP, Lagarde M, Witter S. Performance-based financing in the context of the complex remuneration of health workers: findings from a mixed-method study in rural Sierra Leone. BMC Health Serv Res. 2016;16:286. doi:1186/s12913-016-1546-8
  56. Maini R, Hotchkiss DR, Borghi J. A cross-sectional study of the income sources of primary care health workers in the Democratic Republic of Congo. Hum Resour Health. 2017;15(1):17. doi:1186/s12960-017-0185-4
  57. Jahangiri R, Aryankhesal A. Factors influencing on informal payments in healthcare systems: a systematic review. Med Ethics J. 2017;11(40):73-92. [Persian].
  58. Belli P, Shahriari H. Qualitative Study on Informal Payments for Health Services in Georgia. Washington, DC: World Bank; 2002.
  59. Vian T, Gryboski K, Sinoimeri Z, Hall R. Informal payments in government health facilities in Albania: results of a qualitative study. Soc Sci Med. 2006;62(4):877-887. doi:1016/j.socscimed.2005.07.005
  60. Balabanova D, McKee M. Understanding informal payments for health care: the example of Bulgaria. Health Policy. 2002;62(3):243-273. doi:1016/s0168-8510(02)00035-0
  61. Kankeu HT, Boyer S, Fodjo Toukam R, Abu-Zaineh M. How do supply-side factors influence informal payments for healthcare? The case of HIV patients in Cameroon. Int J Health Plann Manage. 2016;31(1):E41-57. doi:1002/hpm.2266
  62. Dabalen A, Wane W. Informal Payments and Moonlighting in Tajikistan's Health Sector. Washington, DC: World Bank; 2008.
  63. Kolstad JR. How to make rural jobs more attractive to health workers. Findings from a discrete choice experiment in Tanzania. Health Econ. 2011;20(2):196-211. doi:1002/hec.1581
  64. Kruk ME, Johnson JC, Gyakobo M, et al. Rural practice preferences among medical students in Ghana: a discrete choice experiment. Bull World Health Organ. 2010;88(5):333-341. doi:2471/blt.09.072892
  65. Paul E, Albert L, Bisala BN, et al. Performance-based financing in low-income and middle-income countries: isn't it time for a rethink? BMJ Glob Health. 2018;3(1):e000664. doi:1136/bmjgh-2017-000664
  66. Borghi J, Little R, Binyaruka P, Patouillard E, Kuwawenaruwa A. In Tanzania, the many costs of pay-for-performance leave open to debate whether the strategy is cost-effective. Health Aff (Millwood). 2015;34(3):406-414. doi:1377/hlthaff.2014.0608
  67. Hipgrave DB, Hort K. Dual practice by doctors working in South and East Asia: a review of its origins, scope and impact, and the options for regulation. Health Policy Plan. 2014;29(6):703-716. doi:1093/heapol/czt053
  68. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC). Tanzania Health Financing Strategy (2016-2026): Path Towards Universal Health Coverage (FINAL DRAFT). Tanzania: MoHCDGEC; 2018.

Articles in Press, Corrected Proof
Available Online from 30 October 2022
  • Receive Date: 21 October 2021
  • Revise Date: 24 August 2022
  • Accept Date: 24 October 2022
  • First Publish Date: 30 October 2022