Disabled n (%) |
Non-disabled n (%) |
P-value* |
|
Sex |
0.17 |
||
Male |
111 (52) |
111 (52) |
|
Female |
102 (48) |
102 (48) |
|
Marital status |
|||
Single |
83 (39) |
58 (27) |
0.00* |
Married |
177(61) |
155(73) |
|
Age categories |
|||
18-29 |
171 (41) |
86 (40) |
|
30-39 |
148 (35) |
77 (37) |
0.11 |
40-49 |
62 (15) |
33 (15) |
|
50> |
40 (9) |
17 (8) |
|
Location (%) |
0.02* |
||
Urban |
58 (27) |
77 (36) |
|
Rural |
155 (73) |
137 (64) |
|
Formal education (%) |
|||
No formal education |
77 (36) |
58 (27) |
|
Primary education |
70 (33) |
60 (28) |
0.02* |
Secondary education |
51 (24) |
60 (28) |
|
Tertiary education |
15 (7) |
36 (17) |
|
Employment (%) |
|||
Employed |
124 (58) |
177 (83) |
0.01* |
Unemployed |
89 (42) |
36 (17) |
|
SES |
|||
Poorest |
104 (49) |
77 (36) |
|
Least poor |
66 (31) |
94 (44) |
0.00* |
Rich |
43 (20) |
38 (18) |
|
Income (NN) |
|||
Less than 10,000 |
143 (67) |
117 (55) |
|
More than 10,000 |
70 (23) |
96 (45) |
0.00* |
Self-rated health (%) |
|||
Good |
53 (28) |
89 (42) |
|
Moderate |
75 (35) |
70 (33) |
0.00* |
Poor |
79 (37) |
53 (25) |
|
Distance travelled |
|||
Less than 4km |
89 (42) |
137 (64) |
0.00* |
More than 4km |
124 (58) |
77 (36) |
|
Healthcare (%) |
|||
Public PHC |
34 (16) |
51 (24) |
|
Public Hospital |
49 (23) |
43 (20) |
|
Private clinic |
15(7) |
36 (17) |
0.00* |
OTP |
45 (21) |
38 (18) |
|
Traditional/home remedy |
70 (33) |
45 (21) |
*Significant at p?0.05, NN- Nigerian Naira (local currency), PHC-Primary healthcare
The trend over time in the measures of expenditures across the study period by disability status
Table 2 shows the levels and changes over time in the measures of expenditures across the study period by disability status. At the post-harvest period, median total OOP spending was estimated at NN5346 ($27) for those without disabilities, and NN9900 ($50) for people with disabilities, and average healthcare expenditure were NN2178 ($11) and NN3654 ($18) for those without disabilities and people with disabilities respectively. The median burden of OOP on household expenditure was 4.8% for people without disabilities but 9.4% for people with disabilities. This provides the first support to the first hypothesis that people with disabilities have substantially higher total OOP spending, health expenditures, and OOP burden compared to those without disabilities. Over the study period, the gaps in mean and median expenditures across disability status remained stable. As shown in the ratio column, the median OOP spending for people with disabilities was 1.8 times higher than those without disabilities in the post-planting period but 2.0 times higher at post-harvest. Healthcare expenditure has increased for both groups between the two periods but increased more for people with disabilities. Median healthcare expenditure grew by 27% for people with disabilities and by 14% for those without disabilities. The median OOP burden has decreased by 33% from 8.8 to 5.9 for those with a disability and increased by 20% from 9.8 to 7.8 for those without disabilities. This result supports our second hypothesis that health expenditures have disproportionately increased for persons with disabilities.
Regression analysis of expenditure differences across the study period by disability status
The result of the unadjusted and models 1 and 2 that adjusted for demographic and socioeconomic factors, healthcare-seeking, and access to healthcare respectively is shown in table 3. The first column of the table presents the result of the three outcomes in an unadjusted model with only time, disability, and the interaction term of disability and time as independent variables. The estimated parameters of the time and disability variables are positive in models of OOP spending and healthcare expenditures, indicating that they have increased between the two periods and that there are significant differences in OOP spending and health expenditures across disability status. The estimated parameters of the model with OOP burden are negative indicating that burden decreased between the two periods and that there are significant differences in OOP burden over time across disability status. The coefficient of the disability time interaction term is positive and significantly different from zero in the regression of health expenditures and burden but imprecisely estimated for OOP. This suggests that healthcare expenditures and OOP burden may have disproportionately increased for persons with disabilities compared to those without a disability. In the second and third columns of Table 3, demographic and socioeconomic characteristics, and health and access to healthcare factors were controlled. After the introduction of health and access to healthcare, the regression coefficient of the disability binary variable is reduced but remains positive and significantly different from zero for health expenditures (from 1.721 to 0.938), OOP healthcare (from 1.121 to 0.682) and OOP
Table 2. Trends in OOP spending, healthcare expenditure, and OOP burden
Mean |
Median |
|||||
Disabled |
Not Disabled |
Ratio |
Disabled |
Not Disabled |
Ratio |
|
Total OOP spending (NN) |
||||||
Post-planting |
3561 ($18) |
1940 ($10) |
1.8* |
5700($29) |
3200($16) |
1.8* |
Post-harvest |
5185 ($26) |
2980 ($15) |
1.7* |
9900($50) |
5400($27) |
1.8* |
Healthcare expenditure (NN) |
||||||
Post planting |
2350 ($12) |
1580($8) |
1.5* |
3200($16) |
2150($11) |
1.9* |
Post-harvest |
2870 ($15) |
1940($10) |
1.5* |
3650($18) |
2310($12) |
2.0* |
OOP burden |
||||||
Post-planting |
8.8 |
4.1 |
2.1* |
13.4 |
5.4 |
2.5* |
Post-harvest |
5.9 |
3.1 |
1.9* |
9.4 |
4.8 |
1.9* |
Significant at p?0.05, NN-Nigerian Naira (local currency), 1$=198NN (Central Bank of Nigeria, 2016
burden (from 1.633 to 0.899). These results provide support to our first hypothesis that people with physical disabilities have higher total health expenditures, OOPs, and burden. In Models 1 and 2, the disability time interaction terms were insignificant for the three outcomes after the covariates are uncontrolled. This shows that disability is not associated with differences in the outcomes between the two periods.
Discussion
At each and the two study periods, people with disabilities had greater total OOP spending, healthcare expenditures, and OOP burden compared to their counterparts without a disability. At the post-harvest period, average healthcare expenditures were NN2310 ($11) and NN3650 ($18) for those without disabilities and people with disabilities respectively. The healthcare expenditure for people without disabilities is almost similar to estimates from the general population where the average total household health expenditure per month was N2354 ($12) (28). However, this disparity is even though people with disabilities used more traditional and home remedies and less private facility consultations. The higher healthcare expenditure among people with disabilities could be due to the higher utilization of hospital services, which has been documented to be high and a determinant of healthcare expenditure among people with disabilities (4,29,30). This has been attributed to the fact that people with disabilities are more likely to utilize hospital facilities due to a higher need for specialist services and emergency care. The high hospital healthcare-seeking pattern among people with disabilities can be attributed to delay in receiving appropriate health care until conditions become poor or worsened leading to critical health conditions that require urgent care, ultimately generating higher medical costs (31). For example, the rate of hospitalization for people with disabilities was found to be particularly high at about five times that of people without disability in India (32).
Table 3: Unadjusted and Adjusted Trends in Total and Out-of-Pocket Expenditures and Burden by disability Status
Unadjusted |
Model 1 |
Model 2 |
|||||||
Beta |
SE |
Beta |
SE |
Beta |
SE |
||||
OOP spending |
|||||||||
Intercept |
3.512 |
0.021* |
1.888 |
0.027* |
0.660 |
0.033* |
|||
Time |
0.124 |
0.008* |
0.263 |
0.005* |
0.101 |
0.011* |
|||
Disabled |
3.721 |
0.061* |
1.721 |
0.023* |
0.938 |
0.059* |
|||
Disabled* Time |
0.143 |
0.018 |
0.012 |
0.009 |
0.003 |
0.000 |
|||
Healthcare expenditure |
|||||||||
Intercept |
1.031 |
0.026* |
0.682 |
0.032* |
0.046 |
0.030* |
|||
Time |
0.097 |
0.009* |
0.006 |
0.010* |
0.64 |
0.042* |
|||
Disabled |
0.416 |
0.058* |
1.121 |
0.062* |
0.682 |
0.029* |
|||
Disabled* Time |
0.371 |
0.037* |
0.001 |
0.004 |
0.001 |
0.000 |
|||
OOP burden |
|||||||||
Intercept |
1.031 |
0.021* |
0.691 |
0.029* |
0.991 |
0.072* |
|||
Time |
0.026 |
0.019* |
0.42 |
0.035* |
0.033 |
0.012* |
|||
Disabled |
0.411 |
0.580* |
0.633 |
0.029* |
0.899 |
0.036* |
|||
Disabled* Time |
0.307 |
0.301* |
0.001 |
0.000 |
0.002 |
0.001 |
The adjusted trend is based on ordinary least squares regression on logged out-of-pocket spending, healthcare expenditures for total and out of pocket burden. Model 1 adjusted for gender, age, marital status, location residence, education, employment, SES, and income. Model 2 additionally included controls for health status, healthcare utilization and access to healthcare. * p< 0.05
Another finding in Korea showed that people with disabilities had a twofold or more increase in the odds of using inpatient hospital services (33). The location of hospital facilities is also another factor that could add to the expenditure. Studies conducted showed extra charges were incurred in instances where an individual using a wheelchair was required to pay double the fare and also the fee of the caregiver, as the individual needed need assistance in going to the hospital (34,35). These expenses could place extra demands on household budgets, which in this study can rise to as high as 13.4% of total household expenses, can prevent or delay seeking health care or when care is sought results in significant financial consequences (1). The consequences of which may result when households took drastic decisions in financing urgent care, such as selling assets, taking out loans or reducing consumption of other necessary household items (36,37). These decisions, while often the only option, nonetheless depletes households of resources that could be used to invest in family enterprises, education and other productive avenues, which push households into further impoverishment, a consequence of catastrophic healthcare expenditure (38,39). Although this study did not estimate the extent to which health-related expenditures contributes to poverty among people with disabilities, there is cyclically re-enforcing relationship between disability and poverty where deprivations such as lack of access to health care, water and sanitation and education, poor nutritional status and poor living conditions, increase the risk of disability (40,41). This situation has implications for researchers and policymakers to appreciate and highlights the need for innovative health financing policies based on economic principles with overall aim to reduce out of pocket and offers financial protection to improve health outcomes as well as social and economic benefits (42,43). This can be achieved in several health system financing options that include mix services across a range of promotion, prevention, treatment, and rehabilitation services (44,45). In advertently, financial protection is central to the achievement of universal health coverage (UHC) and the implementation of appropriate social protection systems as part of the Sustainable Development Goals (46).The concept of UHC has become central to the promotion of the belief that financial and risk pooling offers the best guarantee for protecting the most vulnerable including people with disabilities from financial hardship as well as providing cost-effective expenditure(47). The concept of universal health coverage is relatively new in the majority of African countries, including Nigeria (48–50). The objective of the health insurance policy in Nigeria seeks to provide financial risk protection and access to quality healthcare for vulnerable population populations including people with disabilities by creating adequate pooling of risk (51,52). Regrettably, evidence reveals that wide gaps still exist in achieving the objectives of the health insurance program in the country (51,53) and the disparity disproportionately affects the poorest and vulnerable individuals (14,15). This study has several limitations. It does not provide any direct evidence on the effects of the states’ policy on healthcare or responsiveness to the plights of the people with disabilities. It is important to look into the situation to assess the specific impact of policy initiatives on OOP and generally on access to healthcare among people with disabilities. Another limitation is that this study does not cover other groups of people with disabilities (such as sensory or intellectual) and neither included an institutionalized population with disabilities and is therefore not representative of all populations with disabilities. Time and resource constraints prevented a larger sample size, which could have more rigorous results, especially on issues at hand.
At the macro-level, a structural change in the sharing of responsibilities for health care among the three tiers of government, which poses a serious challenge for significantly extending social insurance to uncovered groups, should be leveraged to accelerate the process by supporting the states to establish and manage their insurance funds while encouraging integration with the National Health Insurance Scheme (NHIS) (52,54). Specifically for people with disabilities, the WHO recommended a reform in health laws and policies by including people with disabilities in health financing and plans inconsistency with the principles of the Convention on the Rights of Persons with Disabilities (WHO, 2013). This includes involving and engaging people with disabilities who know best what their needs are in decision-making at all levels to improve their awareness and knowledge of the scheme and its benefits. Another recommendation is to target people with disabilities with social protection schemes including an exemption to enable them to access routine services and extend to rehabilitation services. Consider non-medical costs by providing support to meet the costs associated with accessing health care, such as transport or consumables to lower costs associated with seeking health care services.
Conclusions
This study contributes to an important knowledge gap of equity in health expenditure and burden associated with healthcare-seeking across disability status. The study finds that substantial differences in health-related out of pocket spending, healthcare expenditures, and OOP burden are associated with disability. These differences after controlling for demographic, socio-economic, access and health status, in all three healthcare costs were found to continue to be disproportionately higher for individuals with a disability than their counterparts without a disability. Further research is needed on specific policy initiatives to reduce OOP and burden on persons with disabilities. This study has implications for researchers and policymakers by highlighting the need for innovative health financing policies based on economic principles that aim to reduce out of pocket and offers financial protection to improve health outcomes as well as social and economic benefits. This can be achieved in several health system financing options that include mix services across a range of promotion, prevention, treatment, and rehabilitation services. Another implication is that the government should involve and engage people with disabilities who know best their needs are in decision-making at all levels.
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