Keywords
Family planning, Financing, budget study, allocations, young people
This article is included in the International Conference on Family Planning gateway.
Family planning, Financing, budget study, allocations, young people
The United Nations projects that the world population will grow exponentially and will reach 10 billion by the year 2055. It is estimated that more than 95% of this growth will happen in low- and middle-income countries (AFIDEP, 2018). A large increase in population will have adverse effects on society, including pressure on the environment and congestion in classrooms, resulting in poor quality of education and food scarcity (UNFPA, 2012). For this reason, there is global and national momentum to increase access to family planning (FP) services. The International Conference on Population and Development (ICPD) plan of action urged governments to make reproductive health (RH) services, including FP services, accessible and affordable to young people (UNFPA, 2014). Elsewhere, the Abuja Declaration committed African Union countries to allocating at least 15% of their budget ‘to improve the health sector’, as a way of translating commitments into results (WHO, 2011).
Uganda’s population was estimated to be 34.6 million in 2014. The annual population growth rate of 3% (UBOS, 2016a) implies that Uganda’s population increases by more than one million people every year. The Government of Uganda intends to lower unmet need for FP to 10% by 2020 and increase the contraceptive prevalence rate to 50%. To achieve this, Uganda developed a Family Planning Costed Implementation Plan (FP-CIP) for 2015–2020, which provides national guidance on increasing knowledge of and access to FP interventions (Ministry of Health, 2016). The decentralized system of governance in Uganda has ensured the transfer of powers, functions and services from central government to local councils. These actions have resulted in improved access to basic services and have increased citizen participation in decision-making processes. During the 2012 London summit, the Ugandan government committed to increasing its annual budget allocation for FP supplies from $3.3 million to $5 million and to mobilise an additional $5 million yearly from donors (FP2020, 2017). The Uganda FP-CIP 2015–2020 has projected financial resource needs of $234.6 million for FP until 2020.
Kenya’s population trends show a gradual increase in population size. In 2009, Kenya’s population size was 38.6 million, with 2016 figures showing a population of 47.7 million, and 2020 projections estimating a population of 52.2 million (Kenya National Bureau of Statistics, 2014). A large proportion of Kenya’s population is youthful, with over half (53.5%) aged 0–24 years (Ministry of Health, 2017). The devolved system of governance has ensured the transfer of functions, resources and power to counties. The constitution is explicit on the requirement for every citizen to enjoy economic and social rights, as well as the Government’s responsibility for ensuring that these rights are protected (The Government of Kenya, 2010). The Government of Kenya has committed to invest $30 million annually in Linda-Mama (a programme that provides a package of basic health services accessed by all in the targeted population on the basis of need and not ability to pay) and to maintain domestic financing for FP commodities at $7 million for two years from 2017 and then double it thereafter (FP2020, 2017).
In both countries, Deutsche Stiftung Weltbevoelkerung (DSW) has empowered its youth champions1 to advocate for increased budgetary allocations to FP. Consequently, DSW has been undertaking annual budget studies in Kenya and Uganda to track financial allocation for FP. This paper presents the status of the budgetary allocations to FP programmes at the national and sub-national level in Kenya and Uganda.
In Uganda, the study was carried out between the months of May and September 2017 and it involved budget analysis of general health and FP funding at national and sub-national level. The study covered the fiscal year (FY) 2017/18. However, for comparison purposes, FY 2015/16 and FY 2016/17 were included in the analysis. Research assistants collected copies of approved budgets and work-plans from the Ministry of Health, Regional Referral Hospitals and the four districts of study. At the national level, data was collected from institutional records from the Ministry of Health, National Medical Stores and Regional Referral Hospitals and recurrent (wage & non-wage) and development (domestic & external) approved, released and spent figures were retrieved. At the sub-national level, copies of approved budgets and work-plans from which FP data was extrapolated were collected from four districts: Kamuli, Tororo, Mityana and Mukono. These four districts were selected because they are the locations of focus for DSW’s budget advocacy work in Uganda. Only approved documents with FP-related information, domestic allocations and government loans were included in the analysis. Documents that were not approved and those without family planning specific information and grants from donors were excluded from the analysis. The variables for which data was sought include domestic allocations, service delivery, capacity building, community mobilization and outreach and percentages of reproductive, new-born, maternal and child health) allocations.
In Kenya, the study was carried out between the months of June and October 2017. The budget study was implemented at the national level and in eleven counties of Kilifi, Mombasa, Nyandarua, Meru, Laikipia, Nakuru, Uasin Gishu, Trans-Nzoia, West-Pokot, Bungoma and Nandi. These counties were selected because they are DSW’s counties of focus in Kenya for FP budget advocacy. The indirect allocation by County Governments was estimated for each county, based on workload statistics from the District Health Information System (DHIS-2) and subjected to county allocation to health.
In Uganda, the DSW FP budget analysis tool provided the basis for data extraction. The DSW budget analysis tool, which is in Microsoft Excel format, provided data analysis at the district level, regional referral hospitals and at the national level. It contains sections for entering sources of funding (domestic or grants/donor) and components e.g. service delivery, capacity building, community mobilization and outreach and others. It also provides percentages that have been discussed and agreed with government officials for FP in situations where FP allocations are included in reproductive, maternal, newborn, child and adolescent health (RMNCAH) and exact FP allocations are not provided. The tool is programmed such that it updates itself once data has been inserted.
In Kenya, workload statistics obtained from the DHIS were subjected to the allocation for health for estimated allocation for family planning. This was done by calculating the percentage of FP service utilization from the total workload. All workloads were converted to the equivalent number of outpatient visits. For the conversion, one inpatient day or one bed-day was estimated to be equal to three outpatient visits. All the bed-days encompassing inpatient and maternity services were converted into outpatient visits and were added to all outpatient visits recorded to obtain the total workload equivalent. The FP percentage was then obtained by dividing total FP visits by total workload equivalent visits. This was done for every county for the FY 2015/16 and FY 2016/17. For FY 2017/18, an average budget increase/decrease over the previous two financial years (FY2015/16 & FY2016/17) were used to provide an estimate of the approximate increase/decrease in FY2017/2018, with the assumption that the same trend would continue. This was used to generate the FP utilization proportions for every county, since no workload statistics were available for this period. The proportions were then used to derive the allocations to FP services in each county using the percentage of FP workload in the total workload in the county. The workload data for each county was obtained from the DHIS-2. The county allocation to health was obtained from approved county government programme-based budgets. The health allocation was multiplied by the percentage of FP visits against all visits to get an estimate of county government allocation to FP for all the financial years under study. Microsoft Excel was used to calculate the allocations for health.
In Uganda, during the 2017/18 FY, the government allocated 0.73% ($3.7 million) of its health sector budget ($506.7 million) to FP (Table 1), of which 98.8% ($3.6 million) was allocated to National Medical Stores (NMS), mainly for the supply of reproductive health commodities (Ongwae, 2019). Analysis of the four districts shows that only 0.5% ($7,966), 0.8% ($10,046), 0.9% ($9,663) and 1.9% ($35,395) of the health sector budget was allocated to FP in Kamuli, Mityana, Mukono and Tororo, respectively, during FY 2017/18. During FY 2016/17, Kamuli, Mityana, Mukono, and Tororo allocated $2,272, $3,175, $3,421 and $12,729, respectively, of their health sector budgets towards FP.
Kenya. In Kenya, the FP budget allocation at the national level reduced from $6.05 million 2015/16 to $2.93 million in 2017/18 (Table 2). The decrease in FP budget allocation at the national level is partly attributed to devolution, which has resulted in more resources being allocated to the counties. At the subnational level in Kenya, there was a combined increase in the estimated sub-national FP budget allocations in all eleven counties of 21.8% ($2.1 million), from $9.8 million (FY 2016/17) to $12 million (FY 2017/2018) (Ongwae, 2019).
The findings indicate an overall increase in FP budget allocations over the last three years in the two countries of study. In Uganda, the 2015 gap analysis by Zlatunich & Couture (2015) identified a financial funding gap of $113 million US dollars for all six years of the FP-CIP. Therefore, the government needs to mobilise additional resources for FP to realize the full implementation of the FP-CIP. Funding for FP at the national and local government level remains very low, at less than 1% of the health sector budget in FY 2017/18. Due to advocacy efforts by DSW and partners, most health facilities have developed detailed work-plans that indicate the amount and FP thematic areas they will spend on FP. Moreover, the government allocation of more funds to health facilities would enable them to conduct a wide range of health promotion activities.
In Kenya, the health sector’s allocation has remained below the 15% committed to health under the Abuja declaration. In addition, despite the increases in FP budget allocations at the sub-national level, these funds are still short of the funds committed to fully implement the FP-CIP (2017 – 2020), which requires an estimated $305 million to be fully implemented.
Additionally, it would be beneficial for counties to initiate and implement capacity building programmes targeting human resources, institutions, legal framework and technical support development, in order to improve budget preparation capabilities. The devolved system of government, which requires citizen participation, has provided advocacy groups with opportunities to advocate for improved allocation for FP programmes. One conclusion of this study is that budget tracking promotes transparency and provides evidence for advocacy. Furthermore, advocacy personnel should be educated about the budget making process, as it provides an excellent platform for advocating for budgetary increases. A separate study to track FP expenditure will provide more insights on the actual FP spending. That said, the benefits of increased budgetary allocations for health cannot be overstated. More budgetary allocations, if well-handled and accounted for, can lead to: greater availability of contraceptives and human resources for health at the health facility level; construction and equipping of youth friendly centres; and improved monitoring of FP service provision.
For the Ugandan budget analysis, all source documents used are indicated in the data file and can be downloaded from the Ugandan Ministry of Finance, Planning and Economic Development budget website. For the Kenyan budget analysis, source data comprised of Kenyan county allocations to health from county Programme Based Budgets (PBB), which are supposed to be publicly available on the counties’ websites. Unfortunately, not all counties have made this information available online. Website links to counties whose data are available online for financial years 2016/17 and 2017/18 have been provided in the summarized workload statistics data file. For the counties whose data are not currently available online, links are provided to the counties' websites where contact information can be retrieved for the county finance department, who can facilitate access to the source documents.
Open Science Framework: Family planning financing: tracking domestic family planning budget allocations at national and sub-national level in Kenya and Uganda http://www.doi.org/10.17605/OSF.IO/DRN2H (Ongwae, 2019)
This project contains the following underlying data:
- Budget Analysis for Uganda_Oct 17- final.xlsx (DSW FP budget analysis tool filled out with data for Uganda)
- DHIS Service workload by county MOH 09052019_JO Example calculations.xlsx (workload statistics and FP allocations for Kenyan counties with example calculations)
- Summarised_workload statistics_Kenya_28062019.xlsx (workload statistics and FP allocations for Kenyan counties with links to county websites and budgets)
Open Science Framework: Family planning financing: tracking domestic family planning budget allocations at national and sub-national level in Kenya and Uganda http://www.doi.org/10.17605/OSF.IO/DRN2H (Ongwae, 2019)
This project contains the following extended data:
- FP Budget Methodology 2017 - Kenya & Tanzania.docx (guide to using the DSW FP budget analysis tool)
Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
I would like to acknowledge Mr. Lukwago Daniel and Ms. Diana Tibesigwa for supporting the execution (data collection and analysis) of the study in Uganda and Mr. Joblin Omari for supporting the undertaking of the study in Kenya.
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Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
No
If applicable, is the statistical analysis and its interpretation appropriate?
Not applicable
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Health financing including national health accounts and other resource tracking methods.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
No
If applicable, is the statistical analysis and its interpretation appropriate?
Not applicable
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
No
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Sexual and Reproductive Health; Family planning; HIV/AIDS; Gynaecological oncology.
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
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Version 1 13 Dec 19 |
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Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
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