Service Delivery Indicators Health Survey 2014 - Harmonized Public Use Data
Mozambique, 2014
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Reference ID
MOZ_2014_SDI-H_v01_M_v02_A_PUF
Producer(s)
Waly Wane, Ezequiel Molina
Collection(s)
Metadata
Created on
Apr 01, 2021
Last modified
Apr 01, 2021
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Identification
Survey ID Number
MOZ_2014_SDI-H_v01_M_v02_A_PUF
Title
Service Delivery Indicators Health Survey 2014 - Harmonized Public Use Data
Country/Economy
| Name | Country code |
|---|---|
| Mozambique | MOZ |
Series Information
This survey is part of the Service Delivery Indicators (SDI) project, an initiative led by the World Bank. SDI surveys track the quality of service delivery in primary schools and frontline health facilities globally. The indicators can be used to track progress within and across countries and over time. The surveys aim to enhance the active monitoring of service delivery to increase public accountability and good governance. Ultimately, the goal of the program is to support policymakers, citizens, service providers, donors, and other stakeholders in enhancing the quality of service delivery and improve development outcomes.
Since the inception of the initiative in 2010, twenty-four surveys have been completed in twelve countries in Africa, capturing the health and primary education service delivery experience of over 500 million people. The surveys have now been extended beyond Africa to the rest of the rest of the globe, with surveys in Latin America (Guatemala), East Asia/Pacific (Indonesia), and South Asia (Bhutan) currently underway.
The data were harmonized to a common standard to facilitate comparisons across countries and over time. The data was also anonymized to preserve the confidentiality of the data of respondents. The harmonization and anonymization work were conducted by the SDI team at the World Bank.
SDI surveys are documented in the Microdata Library as Service Delivery Indicators Health Surveys and Service Delivery Indicators Education Surveys.
Since the inception of the initiative in 2010, twenty-four surveys have been completed in twelve countries in Africa, capturing the health and primary education service delivery experience of over 500 million people. The surveys have now been extended beyond Africa to the rest of the rest of the globe, with surveys in Latin America (Guatemala), East Asia/Pacific (Indonesia), and South Asia (Bhutan) currently underway.
The data were harmonized to a common standard to facilitate comparisons across countries and over time. The data was also anonymized to preserve the confidentiality of the data of respondents. The harmonization and anonymization work were conducted by the SDI team at the World Bank.
SDI surveys are documented in the Microdata Library as Service Delivery Indicators Health Surveys and Service Delivery Indicators Education Surveys.
Abstract
The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.
The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.
The Mozambique SDI Health survey team visited a sample of 195 health facilities across Mozambique between April and June 2014. The survey team collected rosters covering 2,972 workers for absenteeism and assessed 694 health workers for competence using patient case simulations.
The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.
The Mozambique SDI Health survey team visited a sample of 195 health facilities across Mozambique between April and June 2014. The survey team collected rosters covering 2,972 workers for absenteeism and assessed 694 health workers for competence using patient case simulations.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Health facilities and healthcare providers
Version
Version Description
v02, harmonized and anonymized data for public distribution.
Version Date
1615780800
Version Notes
Data was cleaned, including renaming and relabeling variables, fixing incorrect value labels, fixing and recategorizing missing observations, deleting analysis/supervision variables, reordering variables to reflect instrument structure and fixing incorrect category values. As a final step, the data was anonymized.
Scope
Notes
The core Health SDI indicators are:
1) Provider Effort:
• Caseload per health provider: Number of outpatient visits per clinician per day.
• Provider absenteeism: Share of up to 10 randomly-selected providers absent from the facility during an unannounced visit.
2) Provider Knowledge and Ability:
• Diagnostic accuracy: Percent of correct diagnoses provided in the five clinical vignettes.
• Treatment accuracy: Percent of correct treatments provided in the five clinical vignettes.
• Management of maternal and neonatal complications: Number of relevant treatment actions proposed by the clinician.
3) Availability of Inputs:
• Infrastructure availability: Availability of an improved water source, an improved toilet and electricity
• Medicine availability: Percent of 14 basic medicines which were available and in-stock at the time of the survey.
• Equipment availability: Availability of functioning thermometer, stethoscope, sphygmomanometer and weighing scale.
1) Provider Effort:
• Caseload per health provider: Number of outpatient visits per clinician per day.
• Provider absenteeism: Share of up to 10 randomly-selected providers absent from the facility during an unannounced visit.
2) Provider Knowledge and Ability:
• Diagnostic accuracy: Percent of correct diagnoses provided in the five clinical vignettes.
• Treatment accuracy: Percent of correct treatments provided in the five clinical vignettes.
• Management of maternal and neonatal complications: Number of relevant treatment actions proposed by the clinician.
3) Availability of Inputs:
• Infrastructure availability: Availability of an improved water source, an improved toilet and electricity
• Medicine availability: Percent of 14 basic medicines which were available and in-stock at the time of the survey.
• Equipment availability: Availability of functioning thermometer, stethoscope, sphygmomanometer and weighing scale.
Coverage
Geographic Coverage
National
Universe
All health facilities providing primary-level care
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Waly Wane | The World Bank |
| Ezequiel Molina | The World Bank |
Funding Agency/Sponsor
| Name |
|---|
| William and Flora Hewlett Foundation |
| The World Bank |
Sampling
Sampling Procedure
The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.
The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.
Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.
The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.
Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.
Weighting
SDI survey estimates must be properly weighted using a sampling weight to assure representativeness of the population of interest. The basic weight for each sampling unit is equal to the inverse of its probability of selection which is computed by multiplying the probabilities of selection at each sampling stage. Sampling weights are stored in the weights file.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-04 | 2014-06 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name |
|---|
| COWI Mozambique |
Questionnaires
Questionnaires
The SDI Health Survey Questionnaire consists of four modules and weights:
Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.
Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.
Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.
Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.
Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.
Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.
Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.
Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.
Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.
Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.
Data Processing
Data Editing
Quality control was performed in Stata.
Other Processing
Datasets have been cleaned, anonymized, and harmonized using Stata.
For some variables and observations, missings were recoded and/or distinctly labeled as:
Skips: "-999", or ".a"
Don't Know: "999", "99", or ".b"
Confidential Information (Anonymized): "Confidential", or ".c "
Not Available: ".n"
For some variables and observations, missings were recoded and/or distinctly labeled as:
Skips: "-999", or ".a"
Don't Know: "999", "99", or ".b"
Confidential Information (Anonymized): "Confidential", or ".c "
Not Available: ".n"
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| SDI Team | HD Practice Group, The World Bank | sdi@worldbank.org |
Confidentiality
Details about the anonymization process can be found in the documentation provided with these datasets.
Access conditions
The harmonized, anonymized datasets are available as public use files (for use under a License).
Researchers who would like access to non-anonymized data should contact sdi@worldbank.org with a statement of research objectives and a rationale for why they require such data. That will start the research use file discussion.
Researchers who would like access to non-anonymized data should contact sdi@worldbank.org with a statement of research objectives and a rationale for why they require such data. That will start the research use file discussion.
Citation requirements
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
Example:
Waly Wane., Ezequiel Molina., World Bank. Mozambique Service Delivery Indicators Health Survey 2014 - Harmonized Public Use Data (SDI-H 2014). Ref: MOZ_2014_SDI-H_v01_M_v02_A_PUF. Downloaded from [uri] on [date].
- 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
Example:
Waly Wane., Ezequiel Molina., World Bank. Mozambique Service Delivery Indicators Health Survey 2014 - Harmonized Public Use Data (SDI-H 2014). Ref: MOZ_2014_SDI-H_v01_M_v02_A_PUF. Downloaded from [uri] on [date].
Access authority
| Name | Affiliation | |
|---|---|---|
| SDI Team | World Bank | sdi@worldbank.org |
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_MOZ_2014_SDI-H_v01_M_v02_A_PUF_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the Study |
Date of Metadata Production
2021-03-22
DDI Document version
V02 (March 2021). This version differs from the original version in the following ways:
Data was cleaned, including renaming and relabeling variables, fixing incorrect value labels, fixing and recategorizing missing observations, deleting analysis/supervision variables, reordering variables to reflect instrument structure and fixing incorrect category values. As a final step, the data was anonymized. The metadata and documentation included in this version reflect and explain these changes.
Data was cleaned, including renaming and relabeling variables, fixing incorrect value labels, fixing and recategorizing missing observations, deleting analysis/supervision variables, reordering variables to reflect instrument structure and fixing incorrect category values. As a final step, the data was anonymized. The metadata and documentation included in this version reflect and explain these changes.