NGA_2017_HRBFIE-EL_v01_M
State Health Investment Project: Impact Evaluation Endline Survey, 2017
NSHIP IE
Name | Country code |
---|---|
Nigeria | NGA |
Other Household Health Survey
This is the endline survey for the impact evaluation of a health results-based financing pilot in Nigeria. The baseline data were collected in 2014 while these endline data are from 2017.
Despite years of human and financial investment in the Nigerian Health Sector, the country did not achieve the health-related millennium development goals (MDGs) by 2015. According to a 2010 UNDP MDG report, the likelihood that the country will achieve MDG 4 (reducing under-five mortality by two thirds between 1990 and 2015) and MDG 5 (reducing maternal mortality ratio by three quarters between 1990 and 2015) is average at best. Although the under-five mortality rate fell by a fifth in five years, from 201 deaths/1,000 live births in 2003 to 157 deaths/1,000 live births in 2008, and the maternal mortality ratio fell by 32 percent (800 deaths/100,000 live births in 2003 to 545 deaths/100,000 live births in 2008); these figures do not come close to the two-thirds and three quarters level set for the MDGs. The main challenges to achieving these goals have been identified as “declining resources, ensuring universal access to an essential package of care, improving the quality of healthcare services and increasing demand for health services and providing financial access especially to vulnerable groups” (UNDP 2010).
To overcome these challenges and accelerate the progress of the country to achieving the health related MDGs, innovative approaches are needed to effectively manage the Nigeria health system and improve on its efficiency to enhance the health status of the population. The World Bank and the government of Nigeria are in the process of preparing a results-based financing (RBF) project which provides incentives for improving performance at critical levels within the Nigerian health system and aims to address some of these challenges. A key feature of the RBF project in the Nigerian context is the provision of financial incentives to States and Local Government Agencies (LGA) based on results achieved. In addition, select health facilities will also receive performance incentives. This approach will also build institutional capacity for health system management while introducing a culture of performance excellence at the health facility level and higher levels of health systems management. Given the innovative nature of the proposed project interventions, the World Bank and the Government of Nigeria seek to nest a rigorous impact evaluation in the project to provide evidence that can be used to inform decisions on whether to scale up the innovations implemented under the project. The primary goal of the impact evaluation of the RBF project in Nigeria is to determine if providing financial incentives linked directly to performance increases the quantity and quality of maternal and child health (MCH) services. In addition, it is anticipated that the impact evaluation should provide answers that are generalizable to specific regions in Nigeria.
These are the endline data in support of this impact evaluation.
Sample survey data [ssd]
Health facility; household
Version 2.1: Edited, anonymous dataset for public distribution.
These data have been anonymized.
HOUSEHOLD: Household characteristics, household listing, education, asset ownership, water and sanitation, household use of insecticide treated mosquito nets and healthcare utilization, women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage, contraception and HIV/AIDS knowledge, and healthcare utilization, birth history, children's characteristics, vitamin A, breastfeeding, care of illness, malaria, immunization, and anthropometry, with an optional module for child development.
FACILITY: health service provision, facility assessment, structural quality of laboratory, pharmacy, and maternity ward, patient exit interviews, direct observation of care, provider interviews, provider knowledge tests.
Urban and rural areas in the six states of Adamawa, Benue, Nasarawa, Ogun, Ondo, and Taraba.
Primary and secondary health facilities in treatment states. In control states, a randomly-selected sample of primary and secondary health facilities.
Households with recent pregnancies (in the last two years) or a currently pregnant woman from the catchment areas of the above facilities.
Name | Affiliation |
---|---|
Eeshani Kandpal (World Bank) | The World Bank |
Name | Affiliation | Role |
---|---|---|
Federal Ministry of Health | Federal Government of Nigeria | Technical Supervision |
Nigerian Bureau of Statistics | Federal Government of Nigeria | Data Collection |
National Population Commission of Nigeria | Federal Government of Nigeria | Data Collection |
Development Economics Data Group | The World Bank | Data Collection |
Name | Abbreviation | Role |
---|---|---|
Health Results Innovation Trust Fund | HRITF | Funder |
The sample frame for the health facility surveys comprised one randomly-chosen facility per ward from all functioning primary and secondary health facilities in each LGA (77 LGAs in total; all but one pre-pilot LGA in treatment state). For indicators that are measured at the level of the health facility, the evaluation is a two-level cluster randomized trial, that is, a study in which units are nested within clusters and the clusters are randomly assigned to the treatment or control condition. In this case, health facilities are nested within LGAs and LGAs are randomly assigned to the treatment or control condition. The referral (secondary) hospital in each LGA was also sampled.
HOUSEHOLDS: The sampling frame consists of households in the 77 LGAs that are part of the evaluation. To ensure an efficient sample, the sampling frame was limited to those households that included at least one woman who has given birth or been pregnant in the last two years. By restricting the sampling frame in such a way, we maximize the proportion of the sample that will have at least one woman who gave birth in the last two years, and the proportion of households that have at least one child under the age of five. While this sampling frame does not give us a fully representative sample of the Nigerian population, it gives a representative sample of the population of interest from this program. Sampling of households was done as follows: First, we listed all enumeration areas in the LGAs that belong to the study, and then randomly drew enumeration areas with probability based on size. Within enumeration areas, the survey firm listed all households within the enumeration area that included at least one woman who has given birth within the last 2 years. Then, 15 households were randomly drawn from that listing.
Start | End |
---|---|
2017-07 | 2017-09 |
Name |
---|
Nigerian Bureau of Statistics |
National Population Commission of Nigeria |
Development Economics Research Group and Development Economics Data Group of The World Bank.
Data editing took place at a number of stages throughout the processing, including:
• Office editing and coding
• During data entry
• Structure checking and completeness
• Secondary editing
• Structural checking of Stata data files
Name | Affiliation |
---|---|
Cathrine Machingauta | The World Bank |
2019-07-26
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
---|---|
yes | Affidavit of Confidentiality |
Licensed datasets, accessible under conditions and following review.
Use of the dataset must be acknowledged using a citation which would include:
Example:
The Federal Ministry of Health and The World Bank. Nigeria State Health Investment Project: Impact Evaluation Endline Survey, 2017. Ref. NGA_2017_HRBFIE-EL_v01_M. Dataset downloaded from [URL] on [date]
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
(c) 2017, The World Bank.
Name | Affiliation | |
---|---|---|
Eeshani Kandpal | The World Bank | ekandpal@worldbank.org |
DDI_NGA_2017_HRBFIE-EL_v01_M_WB
Name | Abbreviation | Affiliation | Role |
---|---|---|---|
Development Economics Data Group | DECDG | The World Bank Group | Documentation of the DDI |
2021-07-26
Version 01 (July 2021)