2nd Conference of the African Health Economics and Policy Association (AfHEA)Saly – Senegal, 15th - 17th March 2011

Willingness to pay for Voluntary Health Insurance in Tanzania

August J. Kuwawenaruwa

Increasingly moves are being made to expand health insurance cover in Africa as a means of reducing out of pocket payments as well as improving access to formal health care

However, fragmentation of insurance schemes in many settings, along with limited regulation of the health insurance sector, has hampered expansion efforts in many countries.

How to expand coverage among the informal sector which constitute a large proportion of the population

How to finance and sustain the expansion of health insurance, and

To what extent mandatory insurance contributions from the formal sector can be used to cross-subsidise contributions from informal sector groups.

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Highly fragmented system of health insurance.

National coverage is low around 13% (Humba September, 2010). The aim being to reach 45 % by 2015 (Humba September, 2010)

The National Health Insurance (NHIF) is financed through mandatory payroll contributions amounting to 3% of salaries from the employee which is matched by the employer.

CHF is based on voluntary contribution per annum per household

TIKA recently introduced in urban areas 4

Insurance Scheme Who is eligible Contribution rate Benefit Package

National Health Insurance Fund (NHIF)

Mandatory for public servants and up to 5 dependents.

6% of gross salary, split between employer and employee

Inpatient & outpatient care from public and accredited faith based & private facilities & pharmacies.

Community Health Fund (CHF)

Rural – voluntary, for a couple and children under 18 years.

Between Tsh 5,000-15,000 per year/household

Primary level public facilities. Limited referral care in some districts

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There is a huge discrepancy between the benefit package offered to NHIF members compared with CHF members, as well as the amount of revenue generated by each scheme.

While there is cross-subsidization across NHIF members, there is no cross-subsidization across the schemes. Nor is there cross-subsidisation across districts/councils for the CHF.

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To elicit household’s willingness to join (WTJ) and willingness to pay (WTP) for voluntary health insurance

To assess how WTJ/WTP varies according to benefit package offered, and

To examine households willingness to cross-subsidise poorer groups in the community

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1,163 uninsured and 1,061 insured household heads were interviewed in 2008 from 3 urban councils and 4 rural districts.

Rural districts were selected such that they had a minimal level of CHF coverage (at least 10%), and to offer some geographical variation.

Uninsured household heads were asked about their WTJ and WTP for health insurance

Scenarios: First reflecting the current design of the CHF with premium Tsh 5,000, the second offering expanded benefits

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Willingness to cross-subsidize questions were addressed to insured household heads.

They were asked: “Would you be willing to contribute to any health insurance scheme or to the council any amount of money so that the very poorest in your community can benefit from free care when they are sick?”.

Those who said “Yes”, were asked to state how much they would be willing to pay per annum to protect the poor

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Bivariate analysis was done to assess the level of association between WTJ, WTP for insurance and willingness to cross-subsidise and a range of individual variables.

Pearson chi-square and t-test test statistics were used for binary explanatory variables and mann-whitney test for continuous explanatory variables to test the significance of the results.

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A logit model was constructed to assess the determinants of WTJ community health insurance and willingness to cross-subsidize the poor.

An OLS log linear model was constructed to assess the determinants of the amounts people were WTP as well as willing to cross-subsidise.

Examination of theoretical validity was done

It was hypothesized that willingness to pay would be affected by socio-demographic variables

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Variables Insured N=1,162 %

UninsuredN=1,060 %

p-value

Gender = Male 73.1 76.5 0.275Occupation=Formal 69.7 4.7 0.001 Health Poor (SAH) 4.8 8.0 0.130

Health Average (SAH) 25.6 26.5 0.393Health Good (SAH) 69.15 64.82 0.956

Education=Completed primary and above

93.7 79.2 0.001

Region =urban 19.2 25.5 0.001

Exemption eligibility 7.9 18.7 0.001

Outpatient visit to formal providers in previous month

23.5 13.2 0.001

Age 41 [12.2] 44.38 (14.4) 0.325

Household size5.22 (2.9) 5.18 [2.6]

0.001

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Respondents were more willing to join health insurance in urban than rural areas at the proposed rate of Tsh 5,000 (93% compared to 74%)

Proposed benefit package had a significant effect on people’s willingness to join in rural areas,

78% were willing to join in Mbulu and Singida districts where inpatient care was covered compared to 72% in Kigoma and Kilosa districts where only primary care was covered

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Expansion of the benefit package in Kigoma and Kilosa, will increase the probability of joining from 72% to 79%.

In urban areas, the benefit package had little effect on people’s WTJ.

Further, there was very limited willingness to pay more than Tsh 5,000, even with an expanded benefit package

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Variable Logit model Coefficient (SE)

Logit model Marginal effect (SE)

Coefficient (SE)

Gender 0.844 (0.27)** 0.139 (0.05)** 0.152 (0.09)*

Occupation -0.553 (0.53) -0.092 (0.10) -0.086 (0.08)

Education 0.438 (0.28)* 0.068 (0.05)* 0.098 (0.11)

Exemption Eligibility -0.400 (0.48) -0.062 (0.08) -0.070 (0.12)

Outpatient visit to formal providers in previous month

0.270 (0.32) 0.036 (0.04) -0.058 (0.08)

Age -0.004 (0.01) -0.001 (0.00) 0.006 (0.00)*

Income 0.083 (0.05) * 0.012 (0.01) * 0.054 (0.01)***

Household Size -0.046 (0.04) -0.007 (0.01) -0.010 (0.01)

Above 59 years 0.124 (0.23) 0.017 (0.03) -0.042 (0.07)

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There was a greater willingness to cross-subsidize the poor among rural compared to urban households (46.0% vs 41.2%)

The actual average amounts stated were lower in rural compared to urban areas (mean Tsh 6,620 vs Tsh 13,940).

39% of NHIF members were willing to cross-subsidize compared to 53% CHF member,

However, NHIF members stated higher average amounts than CHF members (mean Tsh 13,690 vs Tsh 4,790).

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Results from logit showed that household being male headed it increased the probability of willingness to cross-subsidise by 10.5 percentage points.

Having outpatient visit to formal providers increases the probability of willing to cross-subsidise by 7.4 percentage points.

Richer households, and those working in the formal sector were willing to pay more for the poor and those who had recently sought care were less willing to pay for the poor.

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People are willing to join health insurance if they are made aware of the principles of insurance and properly understand the concept of risk pooling. However, willingness to pay remains limited.

The greater willingness to join insurance in urban compared to rural areas suggests that cross subsidisation should also be promoted between urban and rural districts for the CHF.

At present, funds are pooled at the district level, but there is no pooling of funds across districts

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NHIF members are willing to cross-subsidise the poor, and would potentially be willing to cross-subsidise CHF

The amounts that could be generated by NHIF members in cross-subsidises would be Tsh 3, 765, 874,000 per annum (=mean amount x 316,460 [NHIF principal members in 2008]).

This means that additional 753,175 CHF members will

be enrolled per annum at a premium of Tsh 5,000.

Its equivalent to 11% of the households in Tanzania using 2000 census data. This could have a dramatic effect on national insurance coverage 19

Households are willing to pay for voluntary health insurance and are willing to cross-subsidise poorer groups within society

In setting the premium policy makers need to consider the variation in the household's socio-economic characteristics.

To achieve the targeted 45% insurance coverage in Tanzania fragmentation of health insurance schemes should be addressed and the size of the risk poor must be maximized.

Maintenance of membership goes parallel with improvement in health care and availability of drugs within the accredited facilities. 20

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Health Insurance for the benefit of all (Financial protection)