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Can a Circular Payment Card Format Effectively Elicit Preferences? Evidence From a Survey on a Mandatory Health Insurance Scheme in Tunisia

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Abstract

Background

The choice of elicitation format is a crucial but tricky aspect of stated preferences surveys. It affects not only the quantity and quality of the information collected on respondents’ willingness to pay (WTP) but also the potential errors/biases that prevent their true WTP from being observed.

Objectives

We propose a new elicitation mechanism, the circular payment card (CPC), and show that it helps overcome the drawbacks of the standard payment card (PC) format. It uses a visual pie chart representation without start or end points: respondents spin the circular card in any direction until they find the section that best matches their true WTP.

Methods

We performed a contingent valuation survey regarding a mandatory health insurance scheme in Tunisia, a middle-income country. Respondents were randomly allocated into one of three subgroups and their WTP was elicited using one of three formats: open-ended (OE), standard PC and the new CPC. We compared the elicited WTP.

Results

We found significant differences in unconditional and conditional analyses. Our empirical results consistently indicated that the OE and standard PC formats led to significantly lower WTP than the CPC format.

Conclusion

Overall, our results are encouraging and suggest CPC could be an effective alternative format to elicit ‘true’ WTP.

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Acknowledgements

This work was carried out thanks to the support of the A*MIDEX Grant (No ANR-11-IDEX-0001-02) funded by the French Government ‘Investissements d’Avenir’ programme. We thank two anonymous reviewers, the editor, Dominique Ami, Ana Bobinac, Brett Day and Pierre-Alexandre Mahieu for relevant comments and suggestions that helped improve the paper, and Marjorie Sweetko for her thorough re-reading of the English. We are also grateful to all the respondents who answered our questionnaires, and to the interviewers.

Author contributions

Olivier Chanel worked on the design of the study, plus the econometric estimation and interpretation of results, and the writing, editing, review and final approval of the manuscript. Khaled Makhloufi worked on the design, preparation and conduct of the study, plus data analysis, and the writing, editing and final approval of the manuscript. Mohammad Abu-Zaineh worked on the design and preparation of the study, plus data analysis, and the writing, editing and final approval of the manuscript. Olivier Chanel acts as overall guarantor.

Author information

Authors and Affiliations

  1. Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESS, GREQAM and IDEP, 2 rue de la Charité, 13236, Marseille Cedex 02, France

    Olivier Chanel & Mohammad Abu-Zaineh

  2. Faculty of Medicine, Aix-Marseille Univ, INSERM, IRD, UMR 912 (SESSTIM), 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France

    Khaled Makhloufi & Mohammad Abu-Zaineh

Authors
  1. Olivier Chanel
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  2. Khaled Makhloufi
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  3. Mohammad Abu-Zaineh
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Corresponding author

Correspondence to Olivier Chanel.

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Conflict of interest

Olivier Chanel, Khaled Makhloufi and Mohammad Abu-Zaineh have no conflicts of interest.

Funding

This research benefited from the support of the A*MIDEX (Aix-Marseille Initiatives d’Excellence) Grant (No ANR-11-IDEX-0001-02) funded by the French Government ‘Investissements d’Avenir’ program, managed by the French National Research Agency (ANR). The funding sources had no role in the writing of the manuscript or in the decision to submit it for publication.

Approval and informed consent

The manuscript does not describe any new clinical studies or patient data collection, and CV data were fully anonymous. No approval by an institutional and/or national research ethics committee was necessary. Informed consent was not required, since the respondents freely agreed to answer the CV survey.

Appendices

Appendix 1: Hypothetical scenario

Appendix 2: WTP elicitation questions

Fig. 3
figure 3

Circular payment card (translated into English)

Full size image

Appendix 3: Descriptive statistics (n = 426)

Variable definition

Mean (SD)

Dependent variables

 WTP = WTP for VHIS (quarterly, TND)

42.583 (25.338)a

Respondent characteristics

 Male = 1 if male, 0 if female

0.669 (0 .471)

 Age = individual’s age (in years)

35.385 (10.395)

 Household size = number of household members

2.599 (2.012)

 Child = 1 if at least one child aged <5 years in the household, 0 otherwise

0.134 (0.341)

 Elderly = 1 if one person aged >65 years in the household, 0 otherwise

0.052 (0.222)

 Married = 1 if married, 0 otherwise

0.417 (0.493)

 Illiterate = 1 no schooling, 0 otherwise

0.023 (0.151)

 Elementary = 1 primary school, 0 otherwise

0.213 (0.410)

 Secondary = 1 secondary education, 0 otherwise

0.516 (0.500)

 High school = 1 higher education, 0 otherwise

0.246 (0.431)

 Income = monthly household income (in TND)

558.11 (464.15)

 Equivalised incomeb = monthly income / (household size)0.5 (TND)

425.80 (425.72)

 Work = 1 if employed/self-employed, 0 otherwise

0.789 (0.409)

 Rural = 1 living in rural area, 0 otherwise

0.197 (0.398)

 Disadvantaged_gov.c = 1 living in disadvantaged governorate, 0 otherwise

0.443 (0.497)

Other variables

 NonDeclared = 1 uninsured due to no declared work, 0 otherwise

0.490 (0.500)

 Administration = 1 uninsured due to administrative procedures, 0 otherwise

0.340 (0.474)

 NoNeed = 1 uninsured due to no need, 0 otherwise

0.663 (0.198)

 RiskAverse = 1 if risk averse, 0 otherwised

0.885 (0.319)

Respondent-specific health variables

 Self-reported health status = 1 if self-reported health status is good, 0 otherwise

0.835 (0.371)

 Outpatient respondent = 1 if at least one outpatient care during the last 3 months, 0 otherwise

0.380 (0.486)

 Inpatient respondent = 1 if at least one hospitalization during the last 8 months, 0 otherwise

0.093 (0.292)

 Chronic condition = 1 if respondent reports a chronic condition, 0 otherwise

0.124 (0.330)

 Financial Health = 1 if can afford health services, 0 otherwise

0.370 (0.483)

 Smoker = 1 if consuming tobacco products, 0 otherwise

0.460 (0.498)

Health variables specific to the family members of the respondent

 Outpatient member = 1 if at least one outpatient care in household during the last 3 months, 0 otherwise

0.5 (0.500)

 Inpatient member = 1 if at least one hospitalization in household during the last 8 months, 0 otherwise

0.140 (0.348)

 Chronic condition = 1 if one household member reports a chronic condition, 0 otherwise

0.185 (0.389)

Survey-specific variables

 PublicSquare = 1 if sample point is a public square, 0 if informal market

0.420 (0.494)

 Interviewer#1–5 = Dummy variables for each of the five interviewers

–

 Time taken to answer the survey (minutes)

20.427 (3.000)

 Proportion that declares difficulties in answering WTP (%)

0.4137 (.4932)

  1. OECD Organization for Economic Co-operation and Development, SD standard deviation, TND Tunisian Dinar, VHIS voluntary pre-payment health insurance scheme, WTP willingness to pay
  2. a90 respondents refused to give a WTP
  3. bEquivalised income is computed based on the OECD equivalence scale by dividing household income by the square root of household size [59]
  4. cAccording to decree no 2008-387 of 11 February 2008
  5. dBased on six modalities generated according to the method of Barsky et al. [60]

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Chanel, O., Makhloufi, K. & Abu-Zaineh, M. Can a Circular Payment Card Format Effectively Elicit Preferences? Evidence From a Survey on a Mandatory Health Insurance Scheme in Tunisia. Appl Health Econ Health Policy 15, 385–398 (2017). https://doi.org/10.1007/s40258-016-0287-5

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