Service Availability and Readiness Assessment 2012
Tanzania, 2012
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Reference ID
TZA_2012_SARA_v01_M
Producer(s)
Honorati Masanja, Paul Smithson, Yahya Ipuge
Created on
Mar 13, 2015
Last modified
Mar 29, 2019
Page views
7399
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793
Identification
Survey ID Number
TZA_2012_SARA_v01_M
Title
Service Availability and Readiness Assessment 2012
Country
| Name | Country code |
|---|---|
| Tanzania | TZA |
Series Information
World Health Organization (WHO)
http://www.who.int/healthinfo/systems/sara_introduction/en/
The Service Availability and Readiness Assessment (SARA) is a health facility assessment tool designed to assess and monitor the service availability and readiness of the health sector and to generate evidence to support the planning and managing of a health system. SARA is designed as a systematic survey to generate a set of tracer indicators of service availability and readiness. The survey objective is to generate reliable and regular information on service delivery (such as the availability of key human and infrastructure resources), on the availability of basic equipment, basic amenities, essential medicines, and diagnostic capacities, and on the readiness of health facilities to provide basic health-care interventions relating to family planning, child health services, basic and comprehensive emergency obstetric care, HIV, TB, malaria, and non-communicable diseases.
Sound information on the supply and quality of health services is necessary for health systems management, monitoring, and evaluation. The efforts to scale up interventions for HIV/AIDS, malaria, safe motherhood, child health, and to achieve the Millennium Development Goals (MDGs) through global health partnerships have drawn attention to the need for strong country monitoring of health services, covering the public, private-for profit, and the private not-for-profit sectors, and their readiness to deliver key interventions. With the increased demand for accountability and the need to demonstrate results at country and global levels, information is needed to track how health systems respond to increased inputs and improved processes over time and the impact such inputs and processes have on improved health outcomes and better health status.
The service availability and readiness assessment (SARA) methodology was developed through a joint World Health Organization (WHO) – United States Agency for International Development (USAID) collaboration to fill critical gaps is measuring and tracking progress in health systems strengthening. The SARA methodology builds upon previous and current approaches designed to assess service delivery including the service availability mapping (SAM) tool developed by WHO, and the service provision assessment (SPA) tool developed by ICF International under the USAID-funded MEASURE DHS project (monitoring and evaluation to assess and use results, demographic and health surveys) project, among others. It draws on best practices and lessons learned from the many countries that have implemented health facility assessments as well as guidelines and standards developed by WHO technical programmes and the work of the International Health Facility Assessment Network (IHFAN).
http://www.who.int/healthinfo/systems/sara_introduction/en/
The Service Availability and Readiness Assessment (SARA) is a health facility assessment tool designed to assess and monitor the service availability and readiness of the health sector and to generate evidence to support the planning and managing of a health system. SARA is designed as a systematic survey to generate a set of tracer indicators of service availability and readiness. The survey objective is to generate reliable and regular information on service delivery (such as the availability of key human and infrastructure resources), on the availability of basic equipment, basic amenities, essential medicines, and diagnostic capacities, and on the readiness of health facilities to provide basic health-care interventions relating to family planning, child health services, basic and comprehensive emergency obstetric care, HIV, TB, malaria, and non-communicable diseases.
Sound information on the supply and quality of health services is necessary for health systems management, monitoring, and evaluation. The efforts to scale up interventions for HIV/AIDS, malaria, safe motherhood, child health, and to achieve the Millennium Development Goals (MDGs) through global health partnerships have drawn attention to the need for strong country monitoring of health services, covering the public, private-for profit, and the private not-for-profit sectors, and their readiness to deliver key interventions. With the increased demand for accountability and the need to demonstrate results at country and global levels, information is needed to track how health systems respond to increased inputs and improved processes over time and the impact such inputs and processes have on improved health outcomes and better health status.
The service availability and readiness assessment (SARA) methodology was developed through a joint World Health Organization (WHO) – United States Agency for International Development (USAID) collaboration to fill critical gaps is measuring and tracking progress in health systems strengthening. The SARA methodology builds upon previous and current approaches designed to assess service delivery including the service availability mapping (SAM) tool developed by WHO, and the service provision assessment (SPA) tool developed by ICF International under the USAID-funded MEASURE DHS project (monitoring and evaluation to assess and use results, demographic and health surveys) project, among others. It draws on best practices and lessons learned from the many countries that have implemented health facility assessments as well as guidelines and standards developed by WHO technical programmes and the work of the International Health Facility Assessment Network (IHFAN).
Abstract
The Tanzania “Service Availability and Readiness Assessment” provides a snapshot of the current status of health service provision in Mainland Tanzania in 2012. The study used an international standard questionnaire instrument and indicators. Data were collected from a sample of districts and health facilities to provide a representative portrayal of health services in the country as a whole. The survey provides estimates of general health care availability and readiness, as well as detailed assessments of specific areas of health care provision.
The publication represents a major contribution to effective monitoring of health service delivery in the country. As well as filling an immediate information gap, the survey provides a “baseline” situation assessment against which future progress may be judged. The report also responds to the increased demand for accountability by publishing objective measures of service delivery capability. In highlighting areas of strength and weakness, the report will aid health planners and managers to prioritise effort and allocate resources.
The publication represents a major contribution to effective monitoring of health service delivery in the country. As well as filling an immediate information gap, the survey provides a “baseline” situation assessment against which future progress may be judged. The report also responds to the increased demand for accountability by publishing objective measures of service delivery capability. In highlighting areas of strength and weakness, the report will aid health planners and managers to prioritise effort and allocate resources.
Kind of Data
Sample survey data [ssd]
Version
Version Description
v2.0
Version Date
2014-05-09
Scope
Notes
Health care
Health care facilities
Health care services
Availability
Readiness
Health care facilities
Health care services
Availability
Readiness
Coverage
Geographic Coverage
Country analysis, Tanzania.
Nationally representative, stratified through regions and districts.
Nationally representative, stratified through regions and districts.
Geographic Unit
Country, by facility.
Universe
Country health services.
Health Facilities in Tanzania
All levels (Hospital -> Dispensary)
Nationally representative.
Health Facilities in Tanzania
All levels (Hospital -> Dispensary)
Nationally representative.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Honorati Masanja | Ifakara Health Institute |
| Paul Smithson | Ifakara Health Institute |
| Yahya Ipuge | Ifakara Health Institute |
Producers
| Name |
|---|
| Ifakara Health Institute |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| Ministry of Health and Social Welfare | MOHSW |
| Global Fund |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Isaac Lyatuu | IHI | Data Analyst |
| Gregory Kabadi | IHI | Data Analyst |
| Juan Manuel Blanco | IHI | Data Analyst |
Sampling
Sampling Procedure
The sample for this survey comprised all districts in the Sentinel Panel of Districts (SPD). This is a panel of 23 districts, plus an additional four districts where demographic sentinel surveillance systems are in operation (Rufiji, Kilombero, Ulanga, Kigoma Urban). The SPD district sampling was conducted by the National Bureau of Statistics using a two-stage, population-weighted probability sample to assure a nationally representative sample of districts that also permitted stratification by zone and by urban/rural area. Sampling weights were included during statistical analysis to account for district's selection probability in a multistage sample design. Probability of a district to be included in a zone was calculated as number of districts selected over total number of districts in a zone. Sampling weights at first stage were calculated as a reciprocal of the probability of a district to be included in SAVVY sample. Since all health facilities in selected districts had equal chances of being included, no sampling weights were incorporated at second stage. It should be noted that results presented in the tables are the number of observations (unweighted counts) whereas results presented as percentages are based on weighted observations.
The overall sample of 27 districts had an estimated total population (2012) of 12.4 million, representing 27% of the total (estimated) Tanzania mainland 2012 population of 45.9 million. The total number of facilities (1908) in the SARA target sample represents approximately 27% of the estimated 7000 health facilities in Mainland Tanzania. Specialist, referral and national hospitals are omitted from the SPD facility sample and are therefore NOT represented in the results presented here, although regional hospitals are included. The total number of facilities in the sample districts is presented in Table 1.1. The target sample numbered 1908 health facilities. Data were collected at 1311 facilities, representing 60% of the target sample. Fourteen facilities had to be dropped in the final analysis due to inability to match it to facility identity, leaving a final total sample number of 1297. Of the 597 facilities where data were not collected, over half (310) were in the Dar es Salaam districts of Temeke,
Ilala and Kinondoni. A further 146 facilities were not covered in the districts of Sumbawanga, Kasulu and Mbozi. Reasons for lower response rate in these districts include the large number of facilities, highly dispersed (difficult to reach) facilities. In one case (Kasulu) illness of the enumerator precluded completion of data collection, while in another (Mbozi) time constraints meant that the deadline for commencing data analysis closed before data collection had been completed. The response completeness rate for this first SARA is certainly lower than ideal. However, we are of the view that the drop out will not seriously bias the results, except to say that private clinics are probably under-represented in our final sample. For future SARA exercises it will be important to have a realistic timeline for fieldwork, analysis and reporting so that data gaps can be followed up and higher reporting completeness can be attained.
The overall sample of 27 districts had an estimated total population (2012) of 12.4 million, representing 27% of the total (estimated) Tanzania mainland 2012 population of 45.9 million. The total number of facilities (1908) in the SARA target sample represents approximately 27% of the estimated 7000 health facilities in Mainland Tanzania. Specialist, referral and national hospitals are omitted from the SPD facility sample and are therefore NOT represented in the results presented here, although regional hospitals are included. The total number of facilities in the sample districts is presented in Table 1.1. The target sample numbered 1908 health facilities. Data were collected at 1311 facilities, representing 60% of the target sample. Fourteen facilities had to be dropped in the final analysis due to inability to match it to facility identity, leaving a final total sample number of 1297. Of the 597 facilities where data were not collected, over half (310) were in the Dar es Salaam districts of Temeke,
Ilala and Kinondoni. A further 146 facilities were not covered in the districts of Sumbawanga, Kasulu and Mbozi. Reasons for lower response rate in these districts include the large number of facilities, highly dispersed (difficult to reach) facilities. In one case (Kasulu) illness of the enumerator precluded completion of data collection, while in another (Mbozi) time constraints meant that the deadline for commencing data analysis closed before data collection had been completed. The response completeness rate for this first SARA is certainly lower than ideal. However, we are of the view that the drop out will not seriously bias the results, except to say that private clinics are probably under-represented in our final sample. For future SARA exercises it will be important to have a realistic timeline for fieldwork, analysis and reporting so that data gaps can be followed up and higher reporting completeness can be attained.
Response Rate
Total facilities, Facilities Interviewed and Final Sample for data analysis
Locationl | Total Facilities per Master list(1) | Facilities Interviewed(2) | Facilities included in final dataset for analysis(3) | Overall response rate(3/1)
Arusha Municipal 63 61 61 97%
Babati District 40 42 42 78%
Bagamoyo District 74 63 63 85%
Geita District 54 48 48 88%
Ilala Municipal 164 103 103 63%
Iringa Municipal Council 36 26 26 72%
Kahama District 59 60 60 95%
Kasulu District 85 38 38 45%
Ujiji (Kigoma Urban) 21 20 20 95%
Kilombero District 54 46 45 83%
Kilosa District 76 52 52 68%
Kinondoni Municipal 247 81 80 32%
Kondoa District 73 60 60 82%
Mbozi District 69 25 25 36%
Moshi Rural 74 66 66 89%
Mtwara Urban District 21 19 19 90%
Muleba District Council 42 37 37 88%
Musoma District 62 56 54 68%
Ruangwa 29 26 26 90%
Rufiji District 70 60 60 86%
Singida Rural 60 50 50 83%
Songea Municipal Council 27 23 23 85%
Sumbawanga District Council 123 68 68 55%
Tanga City Council 59 51 51 86%
Temeke Municipal 136 53 51 38%
Ulanga District 53 35 35 66%
Uyui District 37 34 34 92%
Total 1908 1311 1297 68%
Locationl | Total Facilities per Master list(1) | Facilities Interviewed(2) | Facilities included in final dataset for analysis(3) | Overall response rate(3/1)
Arusha Municipal 63 61 61 97%
Babati District 40 42 42 78%
Bagamoyo District 74 63 63 85%
Geita District 54 48 48 88%
Ilala Municipal 164 103 103 63%
Iringa Municipal Council 36 26 26 72%
Kahama District 59 60 60 95%
Kasulu District 85 38 38 45%
Ujiji (Kigoma Urban) 21 20 20 95%
Kilombero District 54 46 45 83%
Kilosa District 76 52 52 68%
Kinondoni Municipal 247 81 80 32%
Kondoa District 73 60 60 82%
Mbozi District 69 25 25 36%
Moshi Rural 74 66 66 89%
Mtwara Urban District 21 19 19 90%
Muleba District Council 42 37 37 88%
Musoma District 62 56 54 68%
Ruangwa 29 26 26 90%
Rufiji District 70 60 60 86%
Singida Rural 60 50 50 83%
Songea Municipal Council 27 23 23 85%
Sumbawanga District Council 123 68 68 55%
Tanga City Council 59 51 51 86%
Temeke Municipal 136 53 51 38%
Ulanga District 53 35 35 66%
Uyui District 37 34 34 92%
Total 1908 1311 1297 68%
Weighting
Check in the Final Report.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2012-05 | 2012-06 | 1 |
| 2012-07 | 2012-08 | 2 |
| 2012-12 | 2012-12 | 3 |
Time periods
| Start date | End date |
|---|---|
| 2012-01-01 | 2012-12-31 |
Data source
- World Health Organization (WHO): http://www.who.int/healthinfo/systems/sara_introduction/en/
Data Collection Mode
Face-to-face [f2f]
Supervision
MOHSW and IHI
A three days training of data collectors was organized to orient participants on how to use the data collection tools. Two data collectors from each district received training. A participatory teaching and learning approach was used that included presentations with question and answer sessions and practice on understanding and filling in the questionnaires. Each district team visited health facilities and administered data collection questionnaires to respective facility in-charges or the person responsible for respective specific services. Supervisors from the MOHSW and IHI went to all districts to provide supervision and reviewed data collection for completeness and quality.
A three days training of data collectors was organized to orient participants on how to use the data collection tools. Two data collectors from each district received training. A participatory teaching and learning approach was used that included presentations with question and answer sessions and practice on understanding and filling in the questionnaires. Each district team visited health facilities and administered data collection questionnaires to respective facility in-charges or the person responsible for respective specific services. Supervisors from the MOHSW and IHI went to all districts to provide supervision and reviewed data collection for completeness and quality.
Data Collectors
| Name | Affiliation |
|---|---|
| FBIS Coordinators | IHI |
| HMIS Focal Persons | Council Health Management Team |
Questionnaires
Questionnaires
Questionnaire.
Paper -> Entered web base (Google forms).
See among the attached material, the questionnaire.
http://www.who.int/entity/healthinfo/systems/sara_indicators_questionnaire/en/index.html
Paper -> Entered web base (Google forms).
See among the attached material, the questionnaire.
http://www.who.int/entity/healthinfo/systems/sara_indicators_questionnaire/en/index.html
Data Processing
Data Editing
Cleaning technique : cold deck, manual.
Other Processing
Data digitalization : Google Forms.
Data management : SQL Management Studio
Analysis, cleaning: Stata 12
Data management : SQL Management Studio
Analysis, cleaning: Stata 12
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Isaac Lyatuu | Ifakara Health Institute | ilyatuu@ihi.or.tz |
Access conditions
The dataset is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of IHI.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the IHI.
4. No attempt will be made to produce links among datasets provided by the IHI, or among data from IHI and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from IHI will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to IHI.
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of IHI.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the IHI.
4. No attempt will be made to produce links among datasets provided by the IHI, or among data from IHI and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from IHI will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to IHI.
Citation requirements
"Ifakara Health Institute,Tanzania Service Availability and Readiness Assessment (SARA) 2012, Version 2.0 of the public use dataset (July 2013), provided by Ifakara Health Institute, Dar es Salaam, Tanzania. data.ihi.or.tz"
Access authority
| Name | Affiliation | |
|---|---|---|
| Data Unit | Ifakara Health Institute | dc@ihi.or.tz |
Location of Data Collection
Ifakara Health Institute
Archive where study is originally stored
Ifakara Health Institute
http://data.ihi.or.tz/index.php/catalog/5
Cost: None
http://data.ihi.or.tz/index.php/catalog/5
Cost: None
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.
Copyright
Ifakara Health Institute
Metadata production
DDI Document ID
DDI_TZA_2012_SARA_v01_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| Juan Manuel BLANCO | Ifakara Health Institute | Documentation of the DDI |
Date of Metadata Production
2014-05-09
DDI Document version
Version 02 (January 2015). Edited version based on Version 01 DDI (DDI_IHI_HEALTH_SARA_2014_v04) that was done by Ifakara Health Institute.