Using a utility maximization approach as developed by Grossman, the results revealed that health expenditure does not affect health outcomes in Kenya. The factors that affect health outcomes include: distance to nearest health facility (5km or more) and other household income. This implies that increasing public health expenditure does not lead to reduced maternal mortality rates.
Since the other determinants (access to medical facility and other household income) significantly affect the health outcomes, the government needs to put measures in place to ensure that women can easily access health facilities and sensitize them to ensure that they deliver in health facilities and attend antenatal care.
This study did not include some important variables that affect maternal mortality rates like the impact of cultural practices such as female genital mutilation (FGM), preference of certain types of health care providers (including traditional and herbal medicine) and earlier marriages. Therefore we suggest that in future, studies in this field should give attention to these variables.
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CHAPTER ONE: INTRODUCTION
1.1 Background information
Health is the extent to which an individual or group is able to cope with the interpersonal, social, biological, and physical environments (World Bank, 2004). Health is therefore a resource for everyday life, not the objective of living. It is a positive concept embracing social and personal resources as well as physical and psychological capacities. Health financing is a key input in the provision of quality healthcare.
Governments have always had a prominent role in overcoming public health risks and this is a major area of concern in less developed countries like Kenya (Scott, 2001). The provision of good health satisfies one of the basic human needs and contributes significantly to maintaining and enhancing the productivity of the people (Owino, 1997). Public expenditure on health services therefore is a key investment in human capital and plays a catalytic role in the growth of the economy by enabling people to achieve their full potential and lead productive lives. In recognition of the importance of human health, one of the Kenya government’s major goals since independence has been to achieve adequate and good-quality health care for all citizens (GOK, 1965).
To address health outcomes in developing countries such as Kenya, UNICEF advocates for increased public expenditure on health (UNICEF, 2006). Therefore, many countries in developing countries have increased their health expenditure over time. For example, to achieve better health outcomes, Kenya has increased its health expenditure from Kshs. 11.9 billion in 2000 to Kshs. 20 billion in 2004 representing a 30% increase as shown in Figure 1.1 (GOK, 2007). But more resources alone may not necessarily lead to better health outcomes because health care expenditure is only one of the many factors that contribute to health outcomes, considering the fact that these resources may be channeled to various projects that may not directly influence health outcomes. The link between government health expenditures and health outcomes may therefore not necessarily be present. First, an increase in public health expenditures may result in a decrease in private health expenditures; a household may divert its funds towards other uses once the government increases its provision of basic health care. Second, the incremental government expenditures may be employed on the intensive rather than the extensive margin. An example of intensive expenditures would be if expensive and low productivity inputs are bought with marginal funds in which case the impact of these expenditures on health outcomes may be small. Third, even if extra funds are applied extensively to health care (e.g. more staff at hospitals, adequate stocking of medications), but complementary services, both inside and outside the health sector, are not there (e.g. lack of roads or transportation to hospitals and clinics, subsidized prices for medication, etc.) the impact of extra government health expenditures may be little or none (Wagstaff, 2002a).
In addition to health expenditure, Kenya also joined hands with other one hundred and eighty eight countries in a global effort to improve health outcome and reaffirmed its commitment to the united Nations Millennium Development goals (MDGs). Three of these millennium development goals are directly related to health. These are to (i) reduce child mortality, (ii) Improve maternal health and (iii) combat HIV/AIDS, malaria and other diseases.
Despite these global and local interventions in health, performance of Kenya’s health sector in terms of maternal mortality has remained as high as four hundred and eighty eight maternal deaths per 100,000 live births in 2008/9, an increase from four hundred and fourteen per 100,000 live births in 2003, five hundred and ninety per 100,000 in 1998 (KDHS, 2008-09). Figure 1.2. Most maternal deaths are due to causes directly related to pregnancy and childbirth, unsafe abortion and obstetric complications such as severe bleeding, infection, hypertensive disorders, and obstructed labor (KDHS, 2008-09). Improving maternal health being one of the eight Millennium Development Goals (MDGs) adopted at the 2000 Millennium Summit, and with only three years left until the 2015 deadline to achieve the MDGs, closer examination of maternal mortality levels is needed to inform planning of reproductive health programmes and to guide advocacy efforts and research at the national level. These estimates are also needed at the international level, to inform decision-making concerning funding support for the achievement of this goal.
Therefore this study focuses on the relationship between health expenditure and health outcomes in Kenya more particularly, how public health expenditure impacts on maternal mortality rates and other determinants of health outcomes.
Figure 1.1 Public Health expenditure trends in Kenya
Source: Kenya Demographic Health Survey 2008/09
Figure 1.2 Trends in maternal mortality: 1990-2008
Source: Kenya Demographic Health Survey 2008/09
1.1.2 Public Health expenditure in Kenya
Adequate resources are critical to sustainable provision of health services. The government remains the major financier of health care, meeting nearly half of the national health recurrent expenditure. The Kenya policy framework of 1994 identified several methods of health services financing, including taxation, user fees, donor funds, and health insurance. These methods have evolved into important mechanisms for funding health services in the country.
The GOK funds the health sector through budgetary allocations to the MOH. However, tax revenues are unreliable sources of health finance, because of macroeconomic conditions such as poor growth, national debt, and inflation, which often affect health allocations. The government therefore works closely with development partners to raise money for the health sector. Donor contributions to the health sector have been on the increase, rising from eight percent of the health budget in 1994-95 to sixteen percent in the fiscal 2001/2002. In some years, donor contributions accounted for over ninety percent of the development budget of the MOH (Ministry of Health, 2006).
According to the 2001-2002 national health accounts (NHA), as cited by Wamai (2009) Kenya spends 5.1% of its GDP on health. He cited that the health budget had grown significantly from Ksh15.2 billion in Fiscal 2001/02 to Ksh34.4 billion in Fiscal 2008/09. He added that the proportion of overall government expenditure that the government spent on health declined over the same period from 9% to 7.9% in Fiscal 2006/07.
In 1992 a cost-sharing system was introduced to leverage more resources for health services (Collins et al, 1996). Revenue from the cost-sharing system increased exponentially from Ksh60 million in Fiscal 1992/93 to over Ksh1, 468 million in Fiscal 2005/06. However, the revenue’s overall share of total health expenditure for Fiscal 2005/06 was just 6.4% of the MOH’s total spending (MOH, 2007).
Figure 1.3: Overview of Kenya’s health budget, FY2002 – 2008 ( US$ million)
Source: Health Policy Initiative analysis of Ministry of medical services, 2008
Figure 1.4: Absolute value of Total Health Expenditure (THE) by financing source 2001-2010
Source: Kenya National Health Accounts 2009/10
Reviews of public expenditures and budgets in Kenya show that total health spending constitutes about eight percent of the total government expenditure and that recurrent expenditures have been consistently higher than the development expenditures, both in absolute terms, and as a percentage of the GDP.
Government financing of health expenditure is about sixty percent of what is required to provide minimum health services, implying that healthcare delivery in Kenya is under-funded (KHDR, 1999). This is accentuated by inefficiency of the system, including lack of cost-effectiveness in service delivery. However, preliminary information from Kenya’s national health accounts shows that the financial contributions of households (out of pocket expenses) exceed those of the government. (Collins et al. 1996)
The per capita expenditure therefore falls short of the Government of Kenya’s commitment to spend fifteen percent of its total budget on health, as agreed in the Abuja Declaration. The under-financing of the health sector has thus reduced its ability to ensure an adequate level of service provision to the population (Collins et al. 1996). The national health concern therefore is the extent to which additional health expenditure on specific care programmes like maternal health will promote /increase benefits of the patients through improved outcomes in health (decline in maternal mortality rates).
1.1.3 Maternal healthcare in Kenya
Improving maternal health is one of the eight Millennium Development Goals (MDGs) adopted at the 2000 Millennium Summit. The two targets for assessing progress in improving maternal health are reducing the maternal mortality ratio (MMR) by three quarters between 1990 and 2015, and achieving universal access to reproductive health by 2015. With only three years left until the 2015 deadline to achieve the MDGs, closer examination of maternal mortality levels is needed to inform planning of reproductive health programmes and to guide advocacy efforts and research at the national level. These estimates are also needed at the international level, to inform decision-making concerning funding support for the achievement of this goal.
Good maternal health is crucial for the welfare of the whole household, especially children who are dependent on their mothers to provide food and care. Prevention of the death of a mother is the single most important intervention for the health of a child.
Women are intensely vulnerable to the effects of costs incurred during childbirth. User fees can be especially high for emergency or technological procedures such as caesarean section, sometimes reaching catastrophic amounts, which push families into poverty (Graham and Newell, 1999). Many women often leave the hospital before they are well enough for discharge because they cannot pay for the care they have received. User charges add to the costs of transport and companion time, which can be substantial for those living far from facilities. The time spent looking for cash can also delay access to emergency life-saving care in facilities (Kunst and Houweling, 2001).
In sub-Saharan Africa, one in sixteen women die in pregnancy or childbirth (WHO, 2001). An estimated ten to twenty million women develop physical or mental disabilities every year as a result of complications or poor management (Ashford, 2006). The long-term consequences are not only physical, but are also psychological, social, and economic. Despite the commitment expressed with the Millennium initiative, maternal health has not been given financial priority internationally. Safe motherhood programmes compete for funding with other priorities such as tuberculosis, malaria and HIV/AIDS.
1.2 Statement of the problem
In Kenya, as in most Sub-Saharan African countries, health care expenditure has steadily increased over time, therefore making its containment a major issue for successive governments. The existence of a large public deficit and the need to reduce it drastically
to comply with the requirements of the AU has added importance to controlling health care expenditure.
Financing health care has remained a challenge to the Government of Kenya for a long time. There seems to be very low investment in health by the government, and inappropriate allocation of resources within the government health budget. In Kenya, health is a basic human right and therefore the health situation in Kenya remains a significant concern for the policy makers. The cost of health care, especially maternal health is a heavy burden on households. While health financing has undergone numerous reforms, more changes are needed to ease the burden of maternal health care costs on households in a bid to increase utilization and subsequently improve the health status of the population.
In Kenya, like in most developing countries, maternal health care program encompass a medical condition that is regularly associated with death. The maternal mortality rates are very high. The major concern in this study is therefore the change in patient improvement due to additional expenditure on maternal health care (reduced maternal mortality rates). It analyzes whether increasing health care expenditure towards maternal health care program will reduce the maternal mortality rates.
1.3 Objectives of the study
The broad objective of this study is to analyze the relationship between health care expenditure and maternal health outcomes in Kenya. The specific objectives of this study are:
To identify the determinants of maternal health in Kenya.
To investigate the relationship between government expenditure on maternal health care and maternal health outcomes
To make policy recommendations based on study findings
1.4 Significance of the study
A key factor that has contributed to the declining health outcomes has been the decline in annual real per capita government budget to the health sector. As noted earlier, the actual expenditures fall below budgetary allocations. With respect to this, policy makers are highly interested in the relationship between expenditure on public health and the resultant health outcomes/benefits. The issue is whether extra spending on maternal health leads to better maternal health outcomes.
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From a policy perspective, this study can help set priorities on resource allocations across specific program of care. For instance it can help the government to know whether additional expenditure on maternal health care will reduce maternal mortality rates in the country. The government is able to set its priorities right whether to invest more on these specific care programme or to reduce its expenditure given the severe budgetary constraints. It also gives policy makers some guidance on appropriate cost containment measures that will help improve health system performance in Kenya. It is also very useful at the international level, to inform decision-making concerning funding support for the achievement of the fifth millennium development goal.
This study also adds to the existing literature on the relationship between health care expenditure and health outcomes, determinants of health outcomes and how health outcomes can be improved.
CHAPTER TWO: LITERATURE REVIEW
2.1 THEORETICAL FRAMEWORK
Healthcare is an intermediate good that has no intrinsic value in itself but has value in its contribution (along with other inputs such as environmental and social factors) towards production of health itself. Health, or in general, health status, refers to measures of the physical and emotional well-being of an individual or a defined population. The quantity of healthcare ‘product’ produced by a healthcare ‘firm’ is referred to as its output. The ultimate output of the health sector is health. Healthcare therefore can be viewed as any other good or service in which each individual maximizes utility subject to a budget constraint.
The basic economic theory of production provides a basis on the linkage of health expenditure and health outcomes. The theory suggests that there are many ways inputs can be used in various proportions to produce outputs (Wolfe, 2002). Inputs refer to the resources needed to carry out a process or provide a service. Inputs required in healthcare are usually financial, physical structures such as buildings, supplies and equipment, personnel, and clients while output refers to the direct result of the interaction of inputs and processes in the system; the types and quantities of goods and services produced by an activity, project or program. The use of inputs in healthcare leads to outcomes. (Cremieux et al. 1999).
Health production theory highlights the manner in which health care as an input is related to health as an output. In this theory, health is the output measured in terms of improved health status such as reduced mortality, morbidity or achieving health related millennium development goals while inputs consist of the number of trained health professionals, the number of school years completed, residential place, the proportion of GDP spent on health and the government health expenditure in the health sector (Desai, 1998).
Health production theory utilizes the health production function which is the change in health status affected as an approximate matter by changes in the consumption of various health services effective in improving health. The production function summarizes the relationship between inputs and outputs with health status being the dependent variable (function of healthcare) dependent on population’s social and environmental factors, policy variables and country specific effects inclusive of biological endowment, and lifestyle.
Many studies on this subject have adopted Grossman’s (1972) model of health production which views each individual as both a producer and a consumer of health. It regards health as a commodity which the individual will wish to consume and maximize, subject to his/her budget constraints, in conjunction with a number of endogenous and exogenous variables which have an impact on individual’s health. Within this model, income and educational level play an important role as explanatory variables.
In Grossman’s model, he regards health care as both a consumption good that provides direct satisfaction and utility, and as an investment good, it provides satisfaction to individuals indirectly through reduction in sick days, increased wages and increased productivity. In this case, health can be viewed as a stock which degrades over time if there are no investments in the individual health, and that health is taken as a sort of capital. Investing in health may seem costly as individuals must trade off resources and time that may be devoted to health, unlike other goals. These factors are also used in determining the optimal level of health that is needed by an individual. The model therefore makes predictions on the likely effects of health care price changes and other goods, outcomes in labor market such as technological changes, wages and employment.
In the Grossman model, at the optimal level, health investment occurs where the marginal cost of health capital is equal to the marginal benefit. Over time, health is likely to depreciate at a certain rate which may be denoted by Î´. The consumer faces an interest rate which may also be denoted by r. By adding these variables, the health capital marginal cost can be calculated as under:
In this case the health capital marginal benefit is the rate of return from this capital in both non market and market sectors. In this model, the health stock at optimal level can be caused by factors such as education, wages and age. The theory further advocates that investing in health should be combined with other factors which are crucial in order to produce new health, which in the long run may offset the process of deterioration in the stock of health.
Medical scientists could argue that only effective medical care should be universally available (OHE, 1979). The government therefore may resort to explicit rationing which is not only to set limits on total expenditure for care, but also to develop mechanisms to arrive at more rational decisions as to relative investments in different disease specific programmes, and the establishment of certain minimal uniform standards. This rationing does not guarantee mothers to equal access to appropriate maternal/medical care. Treatment is still within the postulate that the doctor will do his best with the resources available to him but there is no such constraint on those resources as government decides (OHE, 1979).
This study looks at maternal health as the “output” of an aggregate production which utilizes variables such as public health expenditure, access to government medical services and household incomes as the “inputs”. The assumption is that for reasons associated with diminishing returns and the adverse effects of certain variables after an initial positive outcome, the relationship is expected to be nonlinear (Nixon and Ulman, 2006).
2.2 EMPIRICAL LITERATURE
Health status are commonly measured using four major indicators, maternal mortality, mortality rate in infants, mortality rate for under five and life expectancy at birth (Akinkugbe et al. 2009); (Gupta et al. 1999); (Wang,2002); (Imam et al. 2003). Other measures of health outcomes/status used include preference of cancer or circulatory diseases, disability adjusted life years, quality adjusted life years, fertility indicators and achievement of other health related millennium development goals. Similarly, government health expenditure, GDP per capita, female literacy, number of physicians, immunization coverage, urbanization and calorie intake among others are some of the most used explanatory variables (Wolfe, 1986); (Wang, 2002); (Or, 2000b); (Caldwell, 1990) and (Filmer et al. 1999).
Most studies have used cross-sectional analysis (Bokhari et al.2007); (Imam et al. 2003); (Anyanwu et al. 2008); (Gani et al. 2009); (Wang, 2002); (Nixon and Ulman, 2006) and (Martin et al. 2009). Some have used panel data (Gupta et al. 1999) and (Or, 2000b), while Akinkugbe et al. (2009) used time series analysis to estimate the relationship between the public health expenditure and health outcomes. To solve the problem of autocorrelation in cross sectional analysis, heteroskedasticity test was done, corrected standard errors for panel data analysis while augmented Dickey Fuller tests were used to test for stationarity in all studies using time series data.
All studies reviewed used health expenditure as one of the explanatory variables except Wang, (2002) who looked at it in a different perspective. According to him, demand for electricity, access to piped water and sanitation and female education increases health expenditure but it does not increase public health expenditure in improving health outcomes.
Most studies indicated that public spending contributes significantly to health status improvements (Filmer et al. 1999); (Abel Smith, 1963); (Kiymaz et al. 2006); (Ester et al. 2011); (Gakunju, 2003); (Bokhari et al.2006); (Anyanwu et al. 2005); (Cremieux et al. 1999); (Nixon and Ulman, 2006) and (Blendon et al. 2006). For example, Filmer et al. (1999) used data from the early 1990s and estimated multivariate regression model of child mortality on per capita income, government health expenditure and other controls. They found that there was significant correlation between child mortality and income per capita.
Some studies however indicated that public health expenditure alone as a determinant of health is inadequate (Ogbu and Gallagher, 1992); (Castrol-leal et al. 1999); (Gupta et al. 2003); (Anderson and Frogner, 2005); (Hitris and Posnet, 1992); (Caldwell, 1986); (Dor et al. 2007) and (Cochrane et al. 1978).
In estimations, different methods were used by different authors. Generally two main methods were used: generalized least squares and the ordinary least squares. However, other methods have also been used. For example, Bokhari et al. (2006) and Gupta et al. (1999) used two stage least squares because of the instrumental variables used to address the problem of reverse causality and measurement errors in the variables. Anyanwu et al. (2005) used Robust Ordinary Least Squares as the baseline specification and robust two stage least squares to control for endogeneity and reverse causality. Bhalotra (2007) used the linear probability model.
Particularly, Flippi et al (2006) took a broader perspective on maternal health and drew attention to the economic and social vulnerability of pregnant women. They called for action to reduce maternal mortality rates by channeling more resources towards maternal healthcare, improving on human resources and information. They used maternal mortality ratio (by cause) as the major indicator and recommended that research is needed on how to finance health services and ensure equitable access to generate more evidence.
While examining the association of the socio-demographic characteristics of women and the unobserved hospital factors in Kenya, Magadi et al. (2001) used multilevel logistic regression. The results showed that the probability of maternal mortality depends on both observed factors that are associated with a particular woman and unobserved factors peculiar to the admitting hospital. The individual characteristics observed to have a significant association with maternal mortality include maternal age, antenatal clinic attendance and educational attainment. The hospital variation was observed to be stronger for women with least favorable socio-demographic characteristics. For example, the risk of maternal death at high-risk hospitals for women aged thirty five years and above, who had low levels of education, and did not attend antenatal care is about two hundred and eighty deaths per a thousand admissions. The risk for similar women at low-risk hospitals is about four deaths per a thousand admissions.
In a study carried out on health care services and sources of revenue in six countries from Western Europe and North America, Abel Smith (1963) found that health care expenditure was associated with reduced life expectancy and increased mortality rates. In a similar study carried out in the year 1967 involving twenty nine countries he found that the level of national income was associated with improved health status and that the demand for healthcare increased in countries with declining mortality. Abel Smith’s studies laid down foundation for the development of methodologies for tracking health expenditures in both private and public sectors.
While investigating the factors that are associated with infant mortality in Sub-Saharan Africa, Ester et al. (2011) carried out an ecological multi-group study using a bi-variate and multi-variate analysis with infant mortality rate as the dependent variable. They used a linear regression model between infant mortality rate and the correlated indicators (social security expenditure and government expenditure per-capita on health). This study revealed, in the multi-variate analysis, three factors associated with the IMR: a higher social security expenditure on health as a percentage of the general government expenditure on health, a higher per-capita government expenditure on health and a higher number of children under five years of age with diarrhea receiving oral dehydration therapy indicated a lower IMR.
During the examination of the effectiveness of public social spending on education and health care in several African countries, Castro-Leal et al. (1999) reviewed the benefit incidence of government spending in Cote d’ivoire, Guinea, Kenya, Madagascar, South Africa and Tanzania. Their study found that public expenditures on health were not sufficient especially on the poor to reduce mortality rates. On the other hand, Gupta et al. (2003) used cross-country data for over seventy developing countries to assess the relationship between public spending on health care and the health status of the poor. Their findings confirmed that the poor have significantly worse health status than the rich. The results however suggested that increased public spending alone will not be sufficient to significantly improve health status.
Another study carried out on the health effects of per capita income and public expenditure on social services in Kenya, proved that per capita income had been very influential in determining health status. The study found that expenditures on education and health care improved health status at a great margin. It further established that per capita income was significantly linked to the levels of mortalities, and that some of the negative trends in health status could have been attributed to unfavorable growth and insufficient social spending on health (Manyala, 2000). In his findings income elasticities were all statistically significant, current income had the expected effect on life expectancy but not on infant mortality. He further found that if mothers are malnourished and are in poor state of health, their infant will inherit part of this poor health, and therefore will be at greater risk of mortality relative to infants of healthy mother.
A comparative study by Wagstaff (2002a) that focused on forty two developing countries used child mortality due to malnutrition and diarrhea as the health outcomes/indicators. Wagstaff (2002b) treated government health expenditure as an exogenous variable and found that it did have a statistically significant (negative) coefficient. The study used a simple stylized theoretical model rationalizing the health-income relationship and found that public spending on health care had a larger impact on child mortality among the poor than among the non-poor population.
In his study on health and schooling investments in Africa, Schultz (1999) found that health status rose with increased public spending on health services. He also argued that the health status will tend to decline with a rise in relative prices of health inputs such as salaries of medical personnel, cost of drugs and other medical supplies, relative to prices of nutrients that help fight infections and disease. He also found that levels of education were correlated with lower mortality rates. The relationship between mothers’ education and mortality rate was stronger than the fathers’. He recommended that an additional year of schooling to the mother especially in low-income countries was associated with a five to ten percent reduction in mortality rates.
On his analysis of the factors determining health status in Kenya, Gakunju (2003) found that government expenditure on public health was noteworthy in shaping individual health status. He also found that government health expenditure influences health status with over a long time. This actually implies that the government investment and spending in the health sector have had a major effect on the health of the people. He also acknowledged a number of factors as being important in resolving the health problem Kenya such as: Per capita income, individual access to doctors, HIV/AIDs prevalence, literacy level for women, Child immunization coverage and spending/investment by the government in the health sector. His study majorly used the central government e
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