The health of the people is fundamental to the attainment of peace and security and is dependent upon the fullest co-operation of individuals and the state. Human health therefore has a major role to play in a Country’s Economic Development. There is a direct relationship between the health status of a population and its productivity as demonstrated by industrialized countries, which are now benefiting from years of investment in health services. The provision of good health satisfies one of the basic human needs and contributes significantly towards maintaining and enhancing the productivity of the people.
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The health sector is pluralistic where health services are provided by many players in the field including the public sector through the Government of Kenya (GOK) and parastatal organizations, the private sector comprising the Faith Based Organizations (FBOs) Non-Governmental Organizations (NGOs) and the Private for-profit facilities. The public sector is the largest provider and financier of health services and operates health care facilities throughout the country accounting for about 52% of all facilities.
In the Vision 2030 Master Plan, several structural changes are envisaged to improve and expand the existing health sector in both public and private spheres to address the challenges.
In Kenya, total health spending stands at about US$6.2 per capita, far short of the World Health Organization’s (WHO) recommended level of US$34 per capita. Life expectancy is also on the decline. According to the World Health statistics 2008, life-expectancy among Kenyan males in 2006 was 57.49 and for women was 58.24 years. This puts Kenya at 188th in the world rankings. HIV/AIDS, Malaria, Rabies, food and water-borne diseases has been a scourge of Kenya, and therefore pose continual challenges to health care providers in Kenya. The infant mortality rate (under 1) was 68 in 1990 and 81 in 2008 per 1,000 live births (UNICEF-Kenya statistics).
Over the years, the Government has had difficulty in allocating “adequate” funds to the Ministry of Health. Per capita expenditure on health has been fluctuating but slowly increasing from KShs 395.50 in 2001/2002 to KShs 983.0 in 2007/08. In terms of US dollar, this is from $6.28 to $13.8 respectively, way below the WHO recommended figure of US$ 37 per capita. Ministry of Health expenditure as a percentage of GDP has been equally low. The challenge is not limited to the amount of funds available for health expenditure but the allocation of the limited financial resources for different uses within the health sector has not been optimal and remained a challenge.
The under-financing of the health sector has reduced its ability to ensure an adequate level of healthcare for the population. Thus, the provision of health and medical care services in Kenya is partly dependent on donors. In 2002, more than 16% of the total expenditure on healthcare originated from donors. There are also other factors inhibiting Kenya’s ability to provide adequate healthcare for its citizens. These include: inefficient utilisation of resources, the increasing burden of diseases and the rapid population growth. Among those Kenyans who are ill and do not choose to seek care, 44% are hindered by cost. Currently, there is a deliberate effort by the government to shift towards decentralization of health care provision. The Ministry of Health (MoH) has embarked on developing the legal and regulatory framework and capacity building to devolve the entire authority for planning and financial management to districts.
The health sector is however at the crossroads. Health statistics shows tremendous decline in the performance of the health indicators over the last ten years despite the increased allocation in health expenditure. This implies therefore that the increased government spending may not necessarily lead to improvement in health status as would be expected.
1.2 STATEMENT OF THE PROBLEM
A central issue in health policy concerns the extent to which additional healthcare expenditure yields patient benefits in the form of improved health outcomes. Over the last couple of decades it has been very fashionable to argue for the power of health care expenditure in improving public health in developing countries. At the same time, additional expenditure on medical care has been discredited as having little or no impact on the overall level of health in society. Evidence however confirms steady trends for improved health outcomes with increasing health expenditure.
Government Expenditure in the period 2005/06 was KShs 401,518,324,607 while Total Health Expenditure (THE) in the same period was KShs 70,807,957,722. With a population of approximately 37,000,000 then, THE per capita was KShs 1,987 (approximately US$ 27), and THE as a percent of total Government Expenditure was 5.2%. Kenya’s healthcare spending is therefore below the WHO recommendation by about US$ 7 per head. The challenge therefore remains how to bridge this resource gap, how to allocate the limited resources more efficiently and how to raise more domestic resources for investing in the health sector. It should be noted that in 2001/02, government spending on health was 8% of total government expenditure, 5.2% was therefore a reduction.
Health care financing studies in Kenya have tended to focus on single modes of financing at a time, such as user fees, insurance, government budget, donor funding, or on financing related issues such as equity and quality of care. Relatively few studies have been conducted to analyze total national health financing or expenditures from all sources and to relate them to their various uses and outcomes. It has been noted that actual expenditures fall below budgetary allocations. 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. In some relatively disadvantaged provinces, such as Nyanza and Western provinces, the current resource formula is resulting in allocations which are below their current spending levels.
Financing healthcare has remained a challenge to the Government of Kenya for a long time. Key challenges in financing healthcare include, Large out of pocket expenditure which cannot be budgeted or programmed for, low investment in health by government, inappropriate allocation of financial resources within the government health budget, low public awareness on the need for health insurance. With respect to resources, infrastructure challenges range from shortage of some critical infrastructure; lack of maintenance systems to ensure serviceability and functionality of existing infrastructure; and shortage of skilled personnel to use and maintain the infrastructure. The human resource has been negatively affected by staff shortage and sub-optimal distribution of available staff. Regarding availability of commodities, the current practice whereby public facilities are required to only source their supplies from Kenya Medical Supplies Agency (KEMSA) has created a monopoly whose effectiveness and efficiency are lacking. KEMSA has adopted the “push” system and thereby forcing the facilities to receive medicines which they have no immediate use for. This leads to lack of drugs in government hospitals.
However, the challenges facing the healthcare service delivery and the health sector as a whole cannot just be addressed by merely pumping more money into the sector. The bottlenecks affecting efficiency, effectiveness and capacity utilization must first be tackled for increased spending to bring about desired results.
Sustainable provision of health care requires a carefully thought out method for financial resources mobilization. In Kenya, a policy framework for financing health care was developed in 1994. This policy framework identified several methods through which the required financial resources could be mobilized and these included; taxation, user fees, donors and health insurance. The methods for financial resources mobilization should particularly pay attention to the socio-economic status of the population it intends to serve. There are two sides to service provision; the cost of service delivery and the ability of the population to pay for it whether as insurance premium or as user fees.
It appears that health has consistently been under financed by the public sector. Per capita health expenditure ranged from as low as KShs 395.49 (US$ 5.05) in 2000/01, to KShs 488.44 in 2001/02 to KShs 1,987 (US$ 27) the highest, in 2005/6. Total Government Expenditure has always been below 2% of the GDP.
1.3 OBJECTIVES OF THE STUDY
The general objective of this study is to carry out an empirical analysis of the relationship between health care expenditure and health outcomes in Kenya. The specific objectives of this study are:
To establish the relationship between government expenditure on training & development of nurses and health outcomes
To establish the relationship between government expenditure on tuberculosis Drugs and health outcomes
To establish the relationship between government expenditure on child immunization and health outcomes
1.4 SIGNIFICANCE OF THE STUDY
The relationship between health care expenditure and health outcomes is of interest to policy makers in the light of steady increases in health care spending for most countries. In Kenya, relatively few studies have been successful in finding a link between health care expenditure and health outcomes, as other factors affecting health outcomes such as diet, life-style and environment are often taken to be the principal factors affecting health outcomes, and particularly life expectancy.
However, establishing causal relationships has always been complex because, firstly, health care expenditure is only one of many quantitative and qualitative factors that contribute to health outcomes, and, secondly, measurement of health status is an imperfect process. Areas or countries with relatively high health needs and poor outcomes may tend (other things being equal) to direct high levels of spending to healthcare. For policy-makers the issue is whether – after adjusting for need – extra spending leads to better health outcomes. From a policy perspective, this study can help set priorities by informing resource allocation across programmes of care. It can also help health technology agencies decide whether their cost-effectiveness thresholds for accepting new technologies are set at the right level.
Healthcare can be viewed as any other good or service. This contributes to the theory of supply and market structure and behavior. 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.
The investment model of demand deals with a theoretical and empirical investigation of the demand for the commodity ‘good health’. The model essentially regards health as a capital good that is inherited and depreciates or deteriorates over time. The theory posits that investment in health is a process in which medical care is combined with other relevant factors to produce new health, which, in part, offsets the process of deterioration in health stock.
The health belief model explains and predicts health behaviors by focusing on individuals’ attitudes and beliefs. It relates a socio-psychologic theory of decision making to individual health-related behaviors in which it identifies six determinants that facilitate healthy behaviors: Perceived susceptibility, or the perception of getting a condition; Perceived severity, or the perception of the seriousness of a condition and its consequences; Perceived benefits, or the perception of receiving tangible and psychological benefits by performing the advised action to reduce risk or seriousness of impact; Perceived barriers, or the perception of having to pay tangible and psychological costs of the advised action; Self-efficacy, or the conviction of being able to successfully execute the healthy behavior to achieve the desired outcome and lastly, Cues to action, or strategies to activate readiness (Glanz and Rimer, 2005; Janz and Becker, 1984; Rosenstock et al., 1994). According to this model the government tries to increase or cut expenditure after weighing the perceived severity of a certain disease and perceived benefits to its citizens.
Michael Grossman’s 1972 model of health production has been extremely influential in this field of study and has several unique elements that make it notable. Grossman’s model views each individual as both a producer and a consumer of health. Health is treated as a stock which degrades over time in the absence of “investments” in health, so that health is viewed as a sort of capital. The model acknowledges that health care is both a consumption good that yields direct satisfaction and utility, and an investment good, which yields satisfaction to consumers indirectly through increased productivity, fewer sick days, and higher wages. Investment in health is costly as consumers must trade off time and resources devoted to health, against other goals. These factors are used to determine the optimal level of health that an individual will demand. The model makes predictions over the effects of changes in prices of health care and other goods, labour market outcomes such as employment and wages, and technological changes. In Grossman’s model, the optimal level of investment in health occurs where the marginal cost of health capital is equal to the marginal benefit.
The framework for Arrow’s theorem assumes that we need to extract a preference order on a given set of options (outcomes). Each individual in the society (or equivalently, each decision criterion) gives a particular order of preferences on the set of outcomes while searching for a preferential voting system, called a social welfare function (preference aggregation rule), which transforms the set of preferences (profile of preferences) into a single global societal preference order. Arrow’s impossibility theorem demonstrates formally that it is impossible to obtain a social welfare function that satisfies all conditions especially collective decisions pertaining to politics and policy. So the government while making expenditure decisions on health, it is not possible to satisfy every individual healthcare needs in the country but it establishes a majority rule for constructing social preferences from ordinal individual health preferences.
There is a considerable literature on the relationship between healthcare expenditure on some measure of healthcare outcomes. However, empirical evidence has hitherto been inconclusive about the strength of the link between health care spending and health outcomes.
On his analysis of the factors determining health status in Kenya, Gakunju E. M. (2003) found that government health expenditure was significant in determining health status of the households. He also found that government health expenditure also influences health status with a lag. This implies that the current and past government (investment and spending) spending in the health sector have significant effect on the health of the population. He also identified several factors as being significant in determination of health status in Kenya. These include income per capita, female literacy level, government spending in health sector, immunization coverage, and access to doctors by households as well as the HIV/AIDs prevalence. His study utilized only the central government health expenditures to explain health status of the population.
Lloyd A. A (2009) evaluated the impact of government health expenditures on the poor in Nigeria. From the descriptive analysis the study found that the health status of the average citizen and the condition of health infrastructure has not improved appreciably despite government spending (though with little fluctuations) on this sector. Thus, he concluded that there is the need for the public sector to, not only, improve its health care expenditure but also put into productive use the available funds in the health sector. Also, the result suggested that public spending on health had a consistent and significant influence on child mortality and therefore government health care spending should be made more productive and accessible. This should not solely be on increasing the number of health care facilities, as this does not necessarily translate to increase in the health status of the populace, emphasis should be on the various ways of improving health care facilities, as these will enhance both the scope and quality of health care services. Furthermore, government resources need to be reallocated towards health intervention designed to respond primarily to the health needs of the poor. Government should also ensure that health interventions reach their intended beneficiaries.
A study by Cremieux et al (1999) sought to overcome data heterogeneity problems by examining the relationship between expenditure and outcomes across 10 Canadian provinces over the 15-year period 1978-1992. They found that lower healthcare spending was associated with a significant increase in infant mortality and a decrease in life expectancy. Their estimated regression equation consisted of a mixture of potentially endogenous variables (such as the number of physicians, health spending, alcohol and tobacco consumption, and expenditure on meat and fat) and exogenous variables (such as income and population density).
Or’s (2001) study of the determinants of variations in mortality rates across 21 OECD (Organisation for Economic Co-operation and Development) countries between 1970 and 1995 found that the contribution of the number of doctors to reducing mortality in OECD countries was substantial, but her estimation technique assumed that the number of doctors was exogenous to the health system.
Using macro-level data Nixon and Ulmann (2006) provided a detailed review of the relationship between healthcare inputs and health outcomes. They undertook their own study using data for 15 EU countries over the period 1980-1995. They employed three health outcomes measures – life expectancy at birth for males and females, and the infant mortality rate – and everal explanatory variables including per capita health expenditure, number of physicians (per 10,000 head of population), number of hospital beds (per 1,000 head of population), the average length of stay in hospital, the inpatient admission rate, alcohol and tobacco consumption, nutritional characteristics and environmental pollution indicators. Nixon and Ulmann concluded that, although health expenditure and the number of physicians have made a significant contribution to improvements in infant mortality, ‘healthcare expenditure has made a relatively marginal contribution to the improvements in life expectancy in the EU countries over the period of the analysis.
Martin s, Rice N and Smitth P.C (2009) had shown that healthcare expenditure has a demonstrably positive effect on outcomes in five of the care programmes that they investigated (that is, for cancer, circulation problems, respiratory problems, gastro-intestinal problems and diabetes). Their lack of success with five other categories – neurology, trauma and injuries, infectious diseases, genito-urinary problems and neonatal care – probably reflects the fact that their outcome indicator (death) is not a common outcome for these categories and/or that the specialty coverage of the mortality data failed to match closely enough the coverage of the budgeting data. No outcome indicator was available for another five categories, although they obtained plausible expenditure results in line with our model’s expectations. In this study they have used budgeting data for 2006/07 and mortality data for the period 2004-06.Our estimates confirm that the marginal cost of a life year saved is quite low and that this finding is not confined to cancer and circulation problem. It provides evidence that expenditure on the various disease categories yields quite consistent benefits in terms of life years saved. Furthermore, it is quite likely that the variations observed between the costs in the different programmes can be explained by two factors. The first is interventions, such as cancer palliative care, that yield benefits that cannot be measured to any great extent in increased life expectancy. The second is differences in the extent to which the specialty coverage of the mortality data corresponds to the coverage of the budgeting data. The dramatic change in inference that arises when moving from the misspecified OLS models to the well-specified 2SLS models illustrates why proper econometric modelling is needed if the nature of the relationship between expenditure and outcome is to be investigated correctly. In particular, they suggest a far more marked influence of healthcare spending on health outcomes than is often indicated by more conventional analysis.
OVERVIEW OF LITERATURE
As demonstrated in the above literature, issues of healthcare expenditure have been an interesting field of study for decades. On examining the countries studied, it can be seen that the vast majority studied various combinations of developed countries. In terms of modeling techniques, all studies utilized some form of multivariate regression analysis, with some incorporating lagged variables for data affected by temporal factors. In some cases the modeling incorporated shift dummies to account for fixed effects within the sample, for example, in investigating heterogeneity due to country-specific effects or the impact of health care system or social insurance.
The principal results showed that health expenditure was a significant explanatory variable for most health outcomes examined. Other studies found that income was a significant explanatory variable while others did not find health expenditure to be significant when controlling for income. It is interesting to note that all studies that included pharmaceutical expenditure found this aspect of health expenditure to be significant and positive for health outcomes.
From the review of the literature, No conclusive evidence appears to exist regarding the contribution of healthcare expenditure on health outcomes. This may be due to country-specific characteristics.
The studies reviewed have used different methodologies and variables to establish the link between healthcare expenditure and health outcomes. Healthcare expenditure in Kenya has been of interest, considering the fact that there have been rapid increases in healthcare spending in recent times. But few or no studies are available regarding this subject. This study will attempt to arouse more interest in this area
This study reviews key findings and methodological approaches in this field and reports the empirical results in Kenya.
The study will adopt an approach that considers health as a production function so that health can be viewed as an ‘output’, of a health care system, which is influenced by the ‘inputs’ to that system. The analysis examines life expectancy and infant mortality as the ‘output’ of the health care system and health care expenditures on nurse training, child immunization and tuberculosis drugs as ‘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 and non-monotonic. For example, the effects of rising income on health status are assumed to be initially beneficial, but after a certain threshold of income level they may reverse to become negative, giving rise to a U-shaped function. Moreover, in empirical research it is often virtually impossible to take account of the effects of latent variables, associated with improved nutrition and better hygiene, which are most important in the determination of health outcomes.
Taking account of these restrictions, the study will undertake econometric analysis of the dependent variables associated with health outcomes: life expectancy and infant mortality. The chosen explanatory variables are: health care expenditures on nurse training and development, child immunization and tuberculosis drugs.
3.1 EMPIRICAL MODEL
Life expectancy and infant mortality rate are the dependent variables being a function of health care expenditure on nurse training and development, child immunization and tuberculosis drugs. This is set out as below:
Le =Nt, Ci, Td, ) â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦..(i)
IMr = Nt, Ci, Td,)â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦(ii)
Where Le is the life expectancy, IMr is the infant mortality rate, Nt is the health expenditure on nurse training and development, Ci is the health expenditure on child immunization, Td is the health expenditure on tuberculosis drugs and is an error term representing the other factors not explicitly captured in the model.
The model specification
The model can therefore be specified as:
Le =+Nt + Ci + Td +â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦..(iii)
IMr =-Nt – Ci – Td +â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦â€¦..(iv)
is the constant term or the intercept
, and are the respective coefficients
Le is the life expectancy
IMr is the infant mortality rate
Nt is the health expenditure on nurse training and development
Ci is the health expenditure on child immunization
Td is the health expenditure on tuberculosis drugs
is the random error term or stochastic disturbance term that captures biases in estimation, it also captures the effects on the other variables unestimated in this model.
The hypotheses are formulated as follows:
Null hypothesis H0: ,, =0, Infant mortality rate and life expectancy are not related to the explanatory variables.
Alternative hypothesis H1: ,, Infant mortality rate and life expectancy are dependent on the explanatory variables.
The linear regression analysis will be applied on the time series data. Life expectancy (Le) and infant mortality rate (IMr) will be taken as dependent variables, while health expenditure on nurse training and development (Nt), health expenditure on child immunization (Ci) and health expenditure on tuberculosis drugs (Td) are the independent variables. The econometric package that will be used is stata. In the analysis, all the independent variables are regressed on the dependent variables to study the relationships.
DATA SOURCES, TYPES AND TESTS
This study uses yearly secondary data covering the period 2000-2010 from various issues of finance publications, World health statistics reports, UNICEF- Kenya statistics and the Ministry of Health (MOH). The study period has been chosen due to data availability. Great care will be exercised in ensuring that only relevant data will be used.
Univariate Data Analysis
This test will be carried out to ensure that the data follows a normal distribution and identify data points that are potentially difficult.
Unit Root Analysis
To avoid spurious regression as would arise with non stationary variables, unit root analysis will be carried out on all the variables to ensure that they are stationary. The unit root tests that will be used are the Dickey Fuller test and the Augmented Dickey Fuller test.
Co integration Analysis
This test is necessary against the loss of information relating to possible long-term relationship in a model specified in first differences. This will involve using the Engle-Granger (1987) two step procedure due to its simplicity. The model will be subjected to Co integration analysis to ensure that there is a stable long-term relationship between the explained variables and the regressors. The long run relationship among vthe level of variables will be restated through the Error Correction Mechanism. The Error Correction Mechanism will be necessary to ensure a systematic disequilibrium adjustment processes through which the dependent and explanatory variables are prevented from shifting away from their mean values.
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The research is expected to confirm that there is a relationship between healthcare expenditure and health outcomes. Increased expenditure on nurse training and development is expected to lower infant mortality rate and raise the life expectancy. Increased expenditure on tuberculosis drugs is also expected to lower infant mortality rate and raise the life expectancy. Increased expenditure on child immunization is as well expected to lower infant mortality rate and raise the life expectancy. On the other hand the researcher expects things to take a different turn or the possibility of having a slight deviation from the expected results.
Descriptions of the variables used
Life expectancy (Le): This is the average number of years a newborn is expected to live with current mortality patterns remaining the same. It is an important indicator of the health status of a country/ community.
Infant mortality rate (IMr): This is the number of infants dying before reaching one year of age, per 1,000 live births. It is generally computed as the ratio of infant deaths (i.e. the deaths of children under one year of age) in a given year to the total number of live births in the same year. Infant mortality rate (IMR) is an important sensitive indicator of the socioeconomic and health status of a community.
Health expenditure on nurse training and development (Nt): This is the expenditure on in-service training programmes that are aimed at upgrading nursing skills. This programme allows working nurses to learn and apply new skills needed to improve the management and quality of patient care.
Health expenditure on child immunization (Ci): This is the expenditure on vaccinations given to children between the ages of nine months and five years against measles, polio and vitamin A supplements.
Health expenditure on tuberculosis drugs (Td): This is the government expenditure in the provision of enough anti-TB drugs. This includes strengthening the TB drug provision focusing on forecasting and distributing TB drugs.
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