Service Delivery Indicators Health Survey 2012 - Harmonized Public Use Data
The SDI provides a set of metrics to benchmark the performance of schools and health facilities in Africa. The Indicators can be used to track progress within and across countries over time, and aim to enhance active monitoring of service delivery to increase public accountability and good governance. Ultimately, the goal of this effort is to help policymakers, citizens, service providers, donors, and other stakeholders enhance the quality of services and improve development outcomes. The perspective adopted by the Indicators is that of citizens accessing a service. The Indicators assemble objective and quantitative information from a survey of frontline service delivery units, using modules from the Public Expenditure Tracking Survey (PETS), Quantitative Service Delivery Survey (QSDS), and Staff Absence Survey (SAS). The SDI initiative is a partnership of the World Bank, the African Economic Research Consortium (AERC), and the African Development Bank. More information on the SDI survey instruments and data, and more generally on the SDI initiative can be found at: www.SDIndicators.org and www.worldbank.org/SDI, or by contacting SDI@worldbank.org.
Kind of data
Sample survey data [ssd]
Version 01: Harmonized, anonymous dataset for public distribution.
Representative of Kenya, rural/urban, and public/private.
Unit of analysis
There are two different units of analysis: facilities and individuals. Individuals are assessed both for absence and for knowledge.
Primary health care facilities and hospitals.
Producers and sponsors
World Bank Group
World Bank Group
Kenya Institute for Public Policy Research and Analysis
Data collection and processing
William and Flora Hewlett Foundation
Health Policy Project (USAID)
The survey used a multi-stage, cluster sampling strategy which allowed for disaggregation by geographic location (rural and urban); by provider type (public and private non-profit) and facility type (dispensaries/health posts, health centers and first level hospitals).
In Kenya, 15 of the 47 counties were chosen. Five counties were pre-selected, Nairobi and Mombasa, as the two most populous cities, and the capital (in the case of Nairobi), along with three others (Nyandarua, Nyamira, and Siaya) selected because of their baseline poverty rates and service delivery outcomes. The remaining ten counties were selected by stratifying the counties by above or below median urbanization; above- or below-median poverty and randomly selecting the counties with probability in proportion to their population size.
Four data sources were used in developing the sampling frame: (i) Public facilities, Ministries of Health; (ii) Non-public facilities; (iii) Location-specific data on the fraction of the local population living in poverty was obtained from the Kenya National Bureau of Statistics; and (iv) The fraction living in urban areas, was obtained from the national statistical authority.
In general, the facilities list was disaggregated by sub-national strata (regions, provinces or districts) and urban/rural location.
For further details of sampling design refer to http://www.sdindicators.org/kenya-health or Annex A of the final report (Kenya Service Delivery Indicators, Education and Health).
Deviations from sample design
Weighting coefficient data is available in the dataset
Dates of collection
Mode of data collection
Four modules were used, with multiple sections. All but module 4 (ressources) are in the archive.
Module 1 covers: (Section A) metadata; (B) general information; (C) Infrastructure; (D) Equipment, materials, and supplies; and (E) Drugs and consumables.
Module 2 covers: (Section A) basic demographic information on the facility; and (B) additional demographic information on a subset of staff.
Module 3 covers knowledge, as measured through seven patient case simulations.
Module 4 (not in the archive) covers resources and governance.
Data has been anonymized, but users commit to not seeking to re-identify statistical units in the data set.
The harmonized, anonymized datasets are available as public use files.
Researchers who feel that they need non-anonymized data should contact email@example.com with a statement of research objectives and a rationale for why they require such data. That will start the Research Use File discussion.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
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.