Reproductive health financing in Kenya: an analysis of national commitments, donor assistance, and the resources tracking process

Abstract

Understanding the flow of resources at the country level to reproductive health is essential for effective financing of this key component of health. This paper gives a comprehensive picture of the allocation of resources for reproductive health in Kenya and the challenges faced in the resource-tracking process. Data are drawn from Kenyan budget estimates, reproductive health accounts, and the Resource Flows Project database and compare budgets and spending in 2005-06 with 2009-10. Despite policies and programmes in place since 1994, services for family planning, maternity care and infant and child health face serious challenges. As regards health financing, the government spends less than the average in sub-Saharan Africa, while donor assistance and out-of-pocket expenditure for health are high. Donor assistance to Kenya has increased over the years, but the percentage of funds devoted to reproductive health is lower than it was in 2005. We recommend an increase in the budget and spending for reproductive health in order to achieve MDG targets on maternal mortality and universal access to reproductive health in Kenya. Safety nets for the poor are also needed to reduce the burden of spending by households. Lastly, we recommend the generation of more comprehensive reproductive health accounts on a regular basis.

Strengthening accountability for improved maternal and newborn health: A mapping of studies in Sub‐Saharan Africa

“…• The Reproductive Health Tool of WHO is available to support tracking of reproductive health subaccounts. [49,50]. • Budget tracking of allocations and expenditures through national health subaccount, and specifically RMNCH subaccounts allows ministries and civil society to track promised budget allocations and expenditures.…”

“…Two articles focused on national health subaccounts and resource allocation by governments and donors and expenditures in Kenya [49] and Namibia [50]. The need for (aggregated) data of higher quality in Kenya was reported [49], whereas the request to examine critically the efficiency in the allocation and use of reproductive health expenditures was raised in Namibia [50]. One article recommended the inclusion of NGOs and development partners into national health account teams [49].…”

Changing Face of Family Planning Funding in Kenya: A Cross-Sectional Survey of Two Urban Counties

“…These tools should be designed to ensure a feasible breakdown of RH expenditures, including FP, and if possible, to capture data starting from the health facility level 12 . The findings of this study will support efforts to advocate for more resources and improved tracking, and to estimate the financial gap for FP services to inform resource mobilization and allocation.…”

“…For the Government of Kenya to reach its goal of reducing unmet need for FP and increasing contraceptive use 3 , it is necessary to focus on quality and equity in delivery of health services 9 and using new approaches to scale up FP delivery 10,11 . An understanding of the funding landscape will be a key part of this process 12 . Globally, government health spending as a share of total government spending is significantly associated with greater equity in the use of modern contraceptive methods 13 .…”

Transformation of potential medical demand in China: A system dynamics simulation model

“…Therefore, it is necessary to ana- 83 lyze the reasons behind the growth of PMD and to seek reasonable 84 health policies by which PMD can be transformed. At the same 85 time, we need to highlight the factors that influence the two- 86 week medical consultation rate, two-week untreated rate, annual 87 rate of hospitalization, and the percentage of patients not being 88 hospitalized; in urban areas, these are the provision of health 89 insurance, family income [31], quality of care, and accessibility to 90 medical care [72,64]. The factors that influence the four indexes 91 in rural areas are the provision of health insurance [91], family 92 income [98], medical costs, health status, socioeconomic status 93 [60], and race [70].…”