This paper provides an estimate of the total costs of health services in Kenya and its distribution across sector providers as well as levels of care. Compared with other studies from Sub-Saharan African countries (see State-of-the-Art) these costs are rather high, but Kenya has also higher gross national product per capita and higher salaries than neighbouring countries. For instance, in 2006 (mid-term of the study) the gross national product of Kenya was 527 US$ p.c. (not PPP-adjusted), whereas Tanzania (358 US$), Uganda (276) and Somalia (136 US$) had much lower GNPs p.c. Merely Sudan had a higher income per capita (643 U$), but this figure does not reflect Sudan's reality. It is skewed due to military aid and oil income. Generally, Kenya is the richest country in Eastern Africa, even if the average does not reflect regional and social disparities in this country (see Background).
The costing study reported in this paper was designed to inform policy makers about the total costs of health care services, where costs arise across the health sector and what the differences are in costs between the different types of providers and levels of care. Consequently, policy makers, politicians and donor agencies can utilize this data to base the Kenya health care reforms on costing evidence instead of guesses. Before the Kenyan Health Sector Costing Model existed only a very limited set of small-scale studies and budget reports existed which were neither representative nor reliable.
We suggest that the data presented in this study can be utilized in the Kenya Health Sector Reform process in the following areas:
• Budget impact: The actual costs of health care services in Kenya in 2006/07 were approximately 63 billion Ksh or 690 million Euros. However, with this amount we could cover merely some estimated 25% of the Kenya Essential Programme of Health for the entire population. Government decision-makers and donor agencies have to be aware of the fact that health care is expensive and that covering the entire population will be even more costly. However, investments in health care are usually regarded to be highly effective in a macro-economic perspective [66
]. The Kenyan Government has strongly expressed its will to cover the entire population with health care services. Based on the assumption that 80% healthcare coverage is realistic, additional resources at the value of 431 million Euros would be required annually for services covered under the Kenyan Essential Package for Care (KEPH).
• Productivity: The figures indicate that Government facilities have generally lower costs per service unit than Faith Based Organisations, other Nongovernmental Organisations and private-for-profit organisations, i.e., without consideration of quality, Government facilities have a higher productivity than institutions of other trustees. This could have at least two reasons. Firstly, a poverty level of 46% [68
] indicates that comparably cheap or free-of-charge services have a higher demand and therefore induce a higher utilization of services with correspondingly low costs per service unit. Indeed, a majority of the population seeks low-cost care due to financial constraints [69
]. Secondly, the low unit costs of Government facilities might indicate a low quality of services. Indeed, literature and observations by the researchers reported widely on the frequency of drug stock-outs in public facilities in Kenya [68
], an important indicator of quality. Higher utilization and lower quality of Government health care services can explain at least partly the comparably low unit costs of Government facilities.
The results of the Kenyan Health Sector Costing Model clearly indicate that the costs per service unit are generally lower at lower levels of the health care pyramid. Consequently, it is economically wise to strengthen the referral system, i.e., patient who can be treated in dispensaries should not be accepted by hospitals. There are many reasons why the referral system does not work, but based on this costing data the Kenya health care reform has to re-address the issue of self-referral.
• Spread of outpatient costs: The costs per service unit deviate strongly. For outpatient services the spread of costs is largest for private-for-profit facilities, signifying that either the productivity of privately run outpatient services is not homogeneous, or that quality varies widely within the sub-sector. This underlines the need to consider a variation in quality within the private subsector until further more conclusive studies are undertaken [70
]. In Kenya it is definitely not true that the private-for-profit sector is only serving the rich with high-quality health care. Instead, the private-for-profit is also addressing the poorer strata of the society with affordable care (and most likely with a lower quality). This calls for a strengthening of all national efforts of quality assurance and regulation of the private sector to ensure consumer safety in the private health care sector. Thus, the Kenya health care reform has to stress the nationwide implementation of the Kenya Quality Model (KQM) in all health care facilities and the Ministry of Public Health and Sanitation as well as the Ministry of Medial Services have to accept their role as regulators of the health care market.
• Spread of inpatient costs: The average costs of public inpatient services are similar to those of private facilities. However, the range is quite high indicating that there are no homogenous inpatient services of private health care institutions in Kenya. Instead, the private health care sector is segmented into private hospitals for the richer strata of the society and private-for-profit hospitals for the poorer. In the political discussion in Kenya it is still assumed that private-for-profit hospitals are luxurious disease palaces for the super-rich. But this is not the case. There is a strong need to study the private health sector in more details. It is the impression of the researchers that we know by far too little about low-cost private health care services.
• Utilization: The generalised unit costs were found to be less in public facilities than in the private sub-sector, but the differences can be strongly reduced by increasing the utilization of private facilities. If, for instance, Kenya would cover 80% of the population with the Kenya Essential Package of Health (KEPH), we would either require a strong increase of the capacity of public facilities or utilize the private institutions to a much higher extent. As a majority of public facilities operates at full capacity and building new institutions is very expensive, efforts should be made to use the existing facilities and competences in the private sector. Not everybody in the Ministries of Health will readily accept the idea to utilize Faith Based and in particular private-for-profit organisations to a higher extent to cover the population with basic health care services. There is still an invisible rift between the public and the private sector. Some argue that private facilities are too expensive so that they are not suitable for the Kenya Essential Programme of Health. However, the health sector reform of Kenya focuses on Public-Private-Partnership and gives an explicit role to the private sector in providing health care services. Our study demonstrates that the cost per service unit (e.g. outpatient visit, hospital admission) of private-for-profit facilities are rather high in comparison to the institutions of other trustees. Our data also proves that the low utilization (e.g. number of outpatients, bed occupancy rate) of these private-for-profit institutions is a main reason for these high unit costs. Assuming normal price elasticity we can conclude, that the high unit costs in these institutions could be reduced if the Government of Kenya decided to pay for essential health care services irrespective of the owner of the health care institution.
• Staffing: The decreasing marginal unit cost with increasing utilization is based on the assumption that health care institutions could either meet the demand within their given labour capacity or acquire sufficient additional staff. However, hiring professional staff in rural health care institutions and in particular doctors for remote hospitals is quite difficult in Kenya. Professionals tend to work in cities (in particular Nairobi) and in high-level health care facilities. Our study results indicate that rural health care facilities are - on average - less staff intensive than urban facilities, and private-for-profit institutions attract more professional staff per service unit than government or faith-based/NGO institutions. The regulating bodies of Kenya must invest thought and effort to convince more professionals to work in rural places.
• Health insurance: The Vision 2030 and the Health Financing Strategy of Kenya have the objective to cover the entire population with essential health care services irrespective of an individual's income and wealth. The documents argue that this will in the long run be achieved by the introduction of a health insurance system. Some pilot projects are on the way (e.g. HAKI: Health for All Kenyans Through Innovations) to determine the prospects and rules of a possible health insurance system for Kenya. The Kenyan Health Sector Costing Model contributes to this development in several aspects. Firstly, it give a first insight into possible daily flat rate (e.g. for hospitals) and capitation (e.g. for dispensaries) as a starting point for the pilot districts of this new financing scheme. Secondly, it demonstrates that the same payments could be applied to health care institutions of all trustees if we control for quality. Insurance will reduce the individual financial burden and will allow patients to choose their provider so that we can anticipate that private health care institutions will attract more clients so that their unit costs will decrease. Consequently, this model calls for a rebate scheme where the same service (in quantity and quality) produces the same income for the provider irrespective of his ownership.
• Future KEPH: It is obvious that Kenya is in the epidemiological transition where chronic-degenerative diseases become more and more dominant. However, the current KEPH concentrates mainly on mother and child health care as well as infectious diseases. Therefore, KEPH will have to be adjusted regularly to allow for the new disease panorama of Kenya. The economic consequences are broadly unknown. The Kenyan Health Sector Costing Model gives at least some insights on the expected costs by showing reliable average cost per service unit (e.g. per patient day). This is a necessary - but not sufficient - condition of calculating the costs of new diagnoses to be included into KEPH. Other cost items, such as diagnosis-specific drugs, will have to be scrutinized additionally.
• Coverage: A coverage of some 25% of theoretical health care needs is quite dissatisfactory. Many patients do not seek professional health care due to long distances, high prices, poor quality and cultural reasons [64
]. Our projections show that a mild increase of coverage has hardly any cost consequences as the direct costs of KEPH conditions are very low, and even strong increases in demand will not result in proportional growth of health care costs. Thus, health care reform must focus on instruments to reduce the barriers. Consequently, the Kenya Quality Model (KQM), the Health for All Kenyans through Innovations (HAKI) and the Mapping Study under the leadership of the Ministry of Medical Services and the Ministry of Public Health and Sanitation in cooperation with the German Development Cooperation (GIZ) are of high importance for an improved coverage. Their success will increase the health care expenditure in Kenya - but it is obvious that this increase will be moderate.
The Kenyan Health Sector Costing Model is based on a much higher sample of health care institutions than any of the studies references in section 3. It was scientifically supervised by international scholars and professionally implemented by the German Development Cooperation (GIZ) and the Ministry of Health of Kenya. Consequently, the quality of data is likely to be quite reliable in comparison with other studies on the costs of health care services in developing countries. However, the authors are aware of a number of shortcomings that limit the validity and representativeness of the data presented in this paper. Firstly, the model tried to cover also the cost of level 1 (community services). However, the wide diversity of community services, such as Aids-Control-Programmes, health education, nutrition programmes, gardening, road safety etc., made it very difficult to come up with reliable results. Secondly, we costed a large number of facilities in comparison to other studies. However, variability of costs, especially in the private sector may have warranted a larger sample in order to draw national policy conclusions from the study. Thirdly, facilities and patients were subjected to the costing exercise over a period of two months, which may under certain circumstances not be representative of the national average of costs, given that disease and consultation patterns are contingent on seasonal or other external variations. Finally, Nairobi based facilities were under-represented in the sample. Consequently, the results will correctly represent the situation in the rest of the country, but might under-estimate the total costs for the entire country as - at comparable levels of care - healthcare costs generated in Nairobi tend to be higher than healthcare costs generated in rural facilities.