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Table of Contents
Year : 2022  |  Volume : 27  |  Issue : 3  |  Page : 313-317

Willingness to Pay (WTP) for Community-based Health Insurance Scheme (CBHIS) in a Nigerian State

1 Department of Community Medicine, College of Medicine, University of Nigeria, Enugu, Nigeria
2 University of Nigeria Teaching Hospital, Enugu, Nigeria

Date of Submission02-Oct-2021
Date of Decision15-Jan-2022
Date of Acceptance30-Jan-2022
Date of Web Publication2-Jun-2022

Correspondence Address:
Chinedu A Idoko
Department of Community Medicine, College of Medicine, University of Nigeria, Enugu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijmh.IJMH_42_21

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Background: Since the turn of the millennium, efforts across the world have been aimed at promoting good living and reducing poverty. This has resulted in countries taking necessary steps to ensure increased access to affordable health care by promoting Universal Health Coverage. Nigeria is not an exemption especially as private health spending has its own substantial impoverishing effects on households. Objective: The objective of this study was to study willingness to pay (WTP) for Community-based Health Insurance Scheme in a Nigerian State. Materials and Methods: The study sample was purposively selected to cover the three senatorial zones of Enugu State, Nigeria. A questionnaire was used to collect data from the respondents that were randomly selected. Focus group discussions were held to collect qualitative data. Key variables which included WTP for in- and outpatient care for the different stated amount of of money in naira and dollar: ₦400 ($1.0), ₦500 ($1.25), ₦1000 ($2.5) or more) were compared across socio-economic status (SES) groups using “asset holding and level of WTP” with the groups classified into SES quartiles. Results: Most respondents were neither WTP a minimum of ₦400 ($1.0) nor a maximum of ₦1000 ($2.5) for inpatient or outpatient care. The overall maximum amount to pay by the groups was ₦500 ($1.25), whereas the minimum amount across the communities was ₦50 ($0.125). Conclusion: There was a ceiling of maximum/minimum willing amounts to pay across the different socio-economic strata and these ceilings were observed to be low.

Keywords: Community-based Health Insurance Scheme, Nigerian State, willingness to pay

How to cite this article:
Idoko CA, Obienu C. Willingness to Pay (WTP) for Community-based Health Insurance Scheme (CBHIS) in a Nigerian State. Int J Med Health Dev 2022;27:313-7

How to cite this URL:
Idoko CA, Obienu C. Willingness to Pay (WTP) for Community-based Health Insurance Scheme (CBHIS) in a Nigerian State. Int J Med Health Dev [serial online] 2022 [cited 2022 Aug 12];27:313-7. Available from: https://www.ijmhdev.com/text.asp?2022/27/3/313/346436

  Introduction Top

Out-of-pocket payments have been identified as a major source of financing for health care, especially in low and middle income countries (LMICs).[1],[2],[3] The question however remained if this is sustainable and reflecting equity especially for the poor.

Since the turn of the millennium, efforts across the world have been aimed at promoting good living and reducing poverty. This has resulted in countries taking necessary steps to ensure increased access to affordable health care by promoting Universal Health Coverage.[4] Different types of community-based healthcare financing have been alluded to in studies carried out, part of which is community provider-based health insurance in which a provider serving a particular community collects the prepayments himself or herself from the subscribers and provides the needed health care to the subscribers.[5],[6]

It is noted by the World Health Organization (WHO) that public spending on health accounts for 20–30% of total health expenditure. Enugu State, as is the case in almost all other states in Nigeria, spend less than 15% (recommended by Abuja Declaration) of their total budget on health.[7],[8],[9],[10]

Evidence in Nigeria indicates that private health spending accounts for about 70% of total health expenditure and could be more than $23 per capita.[11],[12],[13] The evidence highlights the impoverishing effects of healthcare payments on households. On an average, about 4% of households are estimated to spend more than half of their total household expenditures on health care and 12% of them are estimated to spend more than a quarter.[5] Furthermore, the process of looking for avenues to borrow money from relatives and neighbors substantially results in the treatment delay causing in most cases deterioration of the illness or even death.

Universal Health Coverage, a major goal of the WHO and thus a priority for many countries, therefore seeks to ensure that every individual irrespective of socio-economic, political, demographic, and gender differences, has equal “access to key promotive, preventive, curative, and rehabilitative health services of good quality at an affordable cost.”[3],[5] This study is essentially to throw light on the different aspects that encourage the Community-based Health Insurance Scheme (CBHIS). These aspects highlighted remain the big determinants of whether a health cover is technically feasible, financially viable, and supported by all stakeholders.[14],[15]

The aim of the study was to conduct feasibility on willingness to pay (WTP) for the CBHIS in Enugu State.

By increasing the likelihood of success of a planned project/program, it is good to conduct feasibility to find out the practicality of embarking on such programs. These pilot studies provide good insight into the planning, implementation, and evaluation of such projects. This study examines the WTP for the CBHIS by respondents in the three senatorial zones of the Enugu State. This is especially important as it would ensure buy-in of the expected target for the scheme in the event of actual implementation.

  Materials and Methods Top

The study was conducted in Enugu State, Nigeria. The Enugu State has a population of 3,257,298 within a total area of 7,618 sq.km. It is a well-developed coal mining, commercial, financial, and industrial center, with booming economy and vast investment opportunities.[9],[10] This was a cross-sectional study. The study area was for convenience selected to cover the three senatorial zones of the State (Enugu North, East, and West).

Sample size determination

Sample size was determined using the population proportion formula.[16],[17],[18] In order to achieve a confidence interval of 95% and a power of 80% and to be able to detect a margin of error of 5%, assuming a non-response of 5%, a required minimum total of 690 respondents were studied.

Sampling technique

The multistage sampling technique was applied in selecting households/respondents for the study. One community/senatorial zone was studied to capture acceptability spread across the state. A list of households in the selected study area was obtained; the first household was identified by simple random sampling after which subsequent households were identified applying systemic sampling technique until the required sample size was achieved. Respondents who were the heads of households had pre-tested questionnaires administered by the interviewer.

Focus group discussion

In the study sites in the three senatorial zones, focus discussion groups were created and divided into three: men of childbearing age, women of childbearing age, and opinion leaders (mixed group). This selection was conveniently done to be representative of relevant sections of the communities.

Statistical analysis

Key variables were compared across socio-economic status (SES) groups using asset holding and level of WTP. The occupation groups were classified into SES quartiles (least poor, poor, very poor, and most poor). Generalized least square (GLS) was used for determining the validity of elicited WTP. Mean WTP was the dependent variable in the GLS analysis, whereas independent variables were derived from hypotheses which represented the SES and demographic status of respondents and their households. The χ2 was also calculated and P-value was determined.

Ethical considerations

Permission was obtained from the Ethical Review Committee of the Enugu State Ministry of Health. Verbal consent of participants was also sought before the onset of the study.

  Results Top

[Table 1] shows the level of WTP for inpatient and outpatient care through CBHIS premium. It shows that most respondents are neither WTP a minimum of ₦400 ($1.0) nor a maximum of ₦1000 ($2.5) for inpatient or outpatient care. Maximum WTP for inpatient and outpatient care across the socio-economic quartile is ₦203 (($0.51), ₦198 (($0.50), ₦231 (($0.58), and ₦5226 (($0.57) for quartiles 1, 2, 3, and 4, respectively. Table 1 also reflects the determined χ2 of the different payment groups for the four quartiles. The χ2 test result and the P-value determined for the individual quartiles were 4.44 (0.62), 2.85 (0.42), and 5.76 (0.5), respectively, whereas the total mean standard deviation for the maximum WTP quartile was 215 (203).
Table 1: Willingness to pay for inpatient and outpatient care

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[Table 2] shows the analysis of focus group discussion (FGD) on WTP for CBHIS in the selected communities. It considers men of childbearing age, opinion leaders (mixed group), and women of childbearing age. The overall maximum amount to pay by groups is ₦500 ($1.25), whereas the minimum amount across the communities was ₦50 ($0.125).
Table 2: Ranges of monthly premiums suggested by FGDs

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  Discussion Top

In CBHIS, members pool funds to attend to cost of health care, which are usually voluntary. This usually occurs within a community or group of people who share common characteristics such as geographical location, occupation, etc., who decide to pay a flat rate premium independent of individual health risks. In this study, most respondents were neither willing to pay a minimum of ₦400 ($1.0) nor a maximum of ₦1000 ($2.5) for inpatient or outpatient care. The respondents preferred lower cost insurance packages, though expecting high grade services as surgical services to be part of what is covered. This finding on preference for lower cost insurance packages is similar to that in a study conducted in 2018.[1],[17] It is however worthy of note that the generally preferred benefit package may not be feasible for the fact that available services would only be based on actual financial resources available to run the scheme, which is further dependent on the enrolled number of participants and premium paid by them. The eventually provided services should be reflecting the commonly prevalent and endemic diseases within the target population as this ensures that those in need derive optimal benefit from health services and receive value for the money spent for these services.[18],[19],[20],[21]

Inpatient services package had the least preference among the respondents. This is attributable to the fact that outpatient services may be seen only as the common healthcare need of most households. This view is supported by a previous study which revealed most patients never took it seriously that they could get so sick and may be needing inpatient services with its vital essence only dawning on them when realized self in a situation of critical ill-health.[22] For the focus group discussants in this study, overall maximum amount to pay by groups is ₦500 ($1.25), whereas the minimum amount across the communities was ₦50 ($0.125). It would be relevant to note that while this response corresponds to that in a study in Lagos[23],[24] in the South West and North Western Nigeria, respectively, there is still need for extreme caution in making decisions as respondents’ actual willingness may phase out by the time actual implementation commences (and time to pay premium sets in) when they do take cognizance of their actual financial abilities relative to their monthly earnings/salaries.

Studies in Asia indicate that the best financial protection is provided by widespread risk pooling, minimal user fees, and benefit packages that cover hospitalization.[25],[26] It remains a work in progress to continually seek best options of CBHIS as this study pursues.

  Limitations Top

There was a bit of a challenge making the respondents understand the linkage of the different monthly premiums to the actual benefit packages because of the mix of socio-economic strata and the accompanying implications, but eventually all the respondents were made to understand that not only were the benefit packages tied to the premiums but also the more compound the package, the higher premium it attracted.

  Conclusion Top

There was always a ceiling of maximum/minimum willing amounts to pay across the different socio-economic strata.

  Recommendation Top

The decision-making systems for eventual package to be selected must be centered on the intended beneficiaries as insurance schemes have been known to have repeatedly reviewed benefit packages and premiums upon receiving opinions of their beneficiaries.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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Fairbank A Sources of financial instability of community-based health insurance schemes: How could social re-insurance help? Technical Report No. 024 bt Associates Partners for Health Reformplus (PHRplus). Bethseda, MD; 2003.  Back to cited text no. 18
Agunwa CC, Obi IE, Ndu AC, Omotowo IB, Idoko CA, Umeobieri AK, et al. Determinants of patterns of maternal and child health service utilization in a rural community in South Eastern Nigeria. BMC Health Serv Res 2017;17:715.  Back to cited text no. 19
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Vončina L, Rubil I Can People Afford to Pay for Health Care? New Evidence on Financial Protection in Croatia. Copenhagen: WHO Regional Office for Europe; 2018. Available from: http://www.euro.who.int/en/health-topics/Health-systems/health-systems-financing/publications/2018/can-peopleafford-to-pay-for-health-care-new-evidence-on-financial-protection-incroatia-2018.  Back to cited text no. 22
Agbo I, Onajole A, Ogunnowo B, Emechebe A Community based health insurance as a viable option for health financing. An assessment of household willingness to pay in Lagos, Nigeria. J Public Health Epidemiol 2019;11:49-57. Available from: https://bit.ly/2NWmGDT.  Back to cited text no. 23
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  [Table 1], [Table 2]


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