International Journal of Epidemiology, 2015, 79–86 doi: 10.1093/ije/dyu223 Advance Access Publication Date: 29 November 2014 Data Resource Profile
Data Resource Profile
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Data Resource Profile: The sentinel panel of districts: Tanzania’s national platform for health impact evaluation Gregory S Kabadi,1,3* Eveline Geubbels,1 Isaac Lyatuu,1 Paul Smithson,1 Richard Amaro,1 Sylvia Meku,2Joanna A Schellenberg3 and Honorati Masanja1 1
Ifakara Health Institute, Dar es Salaam, Tanzania, 2National Bureau of Statistics, Dar es Salaam, Tanzania and 3London School of Hygiene and Tropical Medicine, London, UK *Corresponding author. Sentinel Panel of Districts, Ifakara Health Institute, Plot 463 Kiko Avenue, Mikocheni, Dar es Salaam, Tanzania. E-mail: [email protected] Accepted 27 October 2014
Abstract The Sentinel Panel of Districts (SPD) consists of 23 districts selected to provide nationally representative data on demographic and health indicators in Tanzania. The SPD has two arms: SAVVY and FBIS. SAVVY (SAmple Vital registration with Verbal autopsY) is a demographic surveillance system that provides nationally representative estimates of mortalities based on age, sex, residence and zone. SAVVY covers over 805 000 persons, or about 2% of the Tanzania mainland population, and uses repeat household census every 4–5 years, with ongoing reporting of births, deaths and causes of deaths. The FBIS (Facility-Based Information System) collects routine national health management information system data. These health service use data are collected monthly at all public and private health facilities in SPD districts, i.e. about 35% of all facilities in Mainland Tanzania. Both SAVVY and FBIS systems are capable of generating supplementary information from nested periodic surveys. Additional information about the design of the SPD is available online: access to some of SPD’s aggregate data can be requested by sending an e-mail to [[email protected]]. Key words: Health facility surveillance, demographic and mortality surveillance, representative sample, subSaharan Africa
Key Messages The Tanzanian Sentinel Panel of Districts (SPD): • is a very powerful information platform that generates population-based and facility-based demographic, health and
all-cause and age- and sex-specific mortality data; • is a national sample with results stratified by residence and zones providing comprehensive monitoring for all
government health sector strategic plan indicators; C The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association V
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International Journal of Epidemiology, 2015, Vol. 44, No. 1 • provides an economical and high-quality platform for monitoring and evaluation, with an opportunity for fundamental
and operational research, including research on social determinants of health, equity analyses and health systems intervention evaluation; • will be sustained through a combination of core research and commissioned monitoring and evaluation funding.
Data resource area and population coverage
Each arm of the SPD has obtained its own ethical approval. Both SAVVY and FBIS arms received ethical approval from the Tanzania’s National Institute for Medical Research. SAVVY was further cleared by Centers for Disease Control and Prevention (CDC). Informed consent was elicited from interview participants during SAVVY censuses and verbal autopsy interviews. Informed consent was not required for FBIS data from health facilities review as there was no direct contact with participants and data contained no identification of patients, as these were aggregated at district level. Box 1 describes resource basics.
Investment in global and national health programmes has increased over the past decade and this has led to an increased demand for evidence of the impact made by new programmes in target countries and populations.1 This requires quality information and statistics to track performance, provide accountability, measure impact and assess progress towards common targets such as the Millennium Development Goals.2 This demand has exposed the major gaps in quality and timeliness of health statistics in many low- and middle-income countries (LMIC) and provides an opportunity for countries to improve their health information systems. For example, estimation of mortality and its causes in such countries is usually done by quantification of deaths in a specific area and period, establishing causes of the deaths (for the numerator) and counting the population within the area under study (for the denominator). Quantification of deaths and establishing causes of deaths in communities has been shown to perform well through the use of verbal autopsy methods.3–5 In some respects, Tanzania has a well-elaborated poverty monitoring system, including systems to monitor health-related indicators.4 However, like many LMIC, Tanzania lacks a comprehensive vital registration system and hence is unable to produce nationally representative annual estimates of key demographic variables including mortality rates and causes. To provide a sustainable source of reliable nationally representative data on demographic, population health and health systems indicators, Ifakara Health Institute (IHI) in collaboration with the Tanzanian National Bureau of Statistics (NBS), the Tanzanian National Institute for Medical Research (NIMR) and the Ministry of Health and Social Welfare (MOHSW) created a new initiative called the Sentinel Panel of Districts (SPD). The SPD has design features similar to what has been proposed for the national evaluation platform by Victora et al.5 and was considered ideal for implementing facilitybased and community-based survey modules that would provide routine, annual, nationally representative data. The SPD is also designed with the intention to provide rapid-response enquiries into implementation status and effectiveness of specific policy initiatives including health system reforms. Last, the SPD offers the opportunity for
Box 1. Description of basic resource items Country (and areas covered) Groups covered
Mainland Tanzania; nationally representative sample of 23 (out of 119) districts Individuals in sampled households; all health facilities in SPD districts
Survey type
Repeated cross-sectional demo-
Data collection
Health facilities: first round in 2010
graphic and facility assessment dates
followed by continuous repeated monthly surveys. Households: phased-in baseline censuses from 2011 with repeat censuses planned in 2015, continuous birth and death monitoring and verbal autopsy interviews
Topic headings
Health service use statistics; allcause and specific mortality rates
Funding sources SPD is funded by: the US Centers for Disease Control and Prevention [1U2GPS001990-01]; Ifakara Health Institute core resources, with support from the governments of the UK, Switzerland, Norway, and Ireland; and the Global Fund for fight against AIDS, TB and Malaria
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Data resource basics
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fundamental and operational research, including research on social determinants of health and equity analyses. SPD covers a total of 23 nationally representative districts of the Mainland Tanzania and is implemented through two arms: the Facility-Based Information System (FBIS) and the SAmple Vital registration with Verbal autopsY (SAVVY). Tanzania’s NBS selected the districts primarily for use in implementing the SAVVY arm. NBS used a two-stage Sampford’s probability with proportion to size sampling method on the 2002 Tanzania Population and Housing Census dataset [Tanzania’s National Bureau of Statistics (Ministry of Planning, Economy and Empowerment) Population and Housing Census 2002]. Data can be obtained by contacting the Director General by e-mail at: [[email protected]]. More information is available at: [http://www.nbs.go.tz/tnada/index.php/catalog/7#page ¼overview&tab¼study-desc]. The 35% coverage of health facilities was based on the number of facilities in the SPD master list compared with the number of health facilities in Mainland Tanzania for 2010. The sample provided estimates for Mainland Tanzania as a whole and included all administrative zones, males/females and urban/rural areas. All special enumeration areas such as schools, hospitals, police and military barracks and all districts involved in demographic monitoring were excluded from the sampling frame. The final SAVVY sample included approximately 167 200 households (or about 7500 households per district), with a population of over 805 000 (or about 2% of Mainland
Tanzania’s population). The FBIS system adopted all SAVVY districts and covers 1608 dispensaries, 193 health centres and 87 hospitals. Figure 1 shows the geographical location of the 23 districts and the governance structure. Overall, implementation of the SPD is led by IHI with support from NBS and NIMR and in close consultation with MOHSW.
SAVVY survey frequency and measures SAVVY started with baseline enumeration censuses in March 2011 and continued in phases until it reached the full scale of all 23 districts in March 2014. Continuous monitoring of vital events and conducting verbal autopsy (VA) interviews in enumeration areas began shortly after commencement of baseline censuses and is done prospectively. Follow-up enumeration censuses will be conducted every 5 years, with a second census round starting in the first districts starting in 2015. SAVVY data collection is grouped into three categories: census enumeration, birth and death notifications and VA interviews. During initial setup of the SAVVY arm, baseline censuses were conducted in all districts enumerating all households within the selected enumeration areas, and captured a snapshot of the population. Each household was visited and family structure data were collected including details of the head of household and each member’s name, gender, occupation and education. Follow-up questions were asked for female household members on
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Figure 1. Geographical locations of districts and types of data from SPDs. b for Mainland Tanzania only (excludes those from Zanzibar).
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number of children. During baseline census, data on retrospective death events of the past 12 months were also collected. A notification system of vital events was set up following the baseline censuses. Each birth or death event occurring in SAVVY enumeration areas triggered a notification message sent by a community key informant using a mobile phone. The procedure is further elaborated in Figure 2. In addition to reporting vital events, SAVVY also promotes vital registration through use of government registers provided by the Registration Insolvency and Trusteeship Agency (RITA).6 Each death notification event is followed by a VA interview with the head of household or a person who took care of the deceased. Interviewers use the three standard World Health Organization’s 2002 VA questionnaires: for newborns (aged 0–28 days), children (aged 29 days-14 years) and adults (aged 15 years and above).7 These questionnaires are designed to collect background information on the deceased including their age, sex, marital status and health data prior to death. Other information collected in verbal autopsy interviews includes history of chronic illness, a narrative account of events leading to death, symptom checklist and duration, lifestyle (use of alcohol, drugs and smoking) and a sequence of use of health services prior to death. All information on verbal autopsy interviews (those captured retrospectively and prospectively during baseline census) is sent to trained physicians in order to establish a probable cause of death. Each death is coded independently using the World Health Organization International Classification of Diseases and Health Related Conditions version 10 (ICD 10).8
FBIS survey frequency and measures FBIS data collection began in January 2010 and is conducted monthly from all health facilities in SPD districts. FBIS data collection and processes involve all health facilities in the district. Each month, FBIS coordinators along with Health Management Information System (HMIS) focal person(s) in the council health management team (CHMT) visit health facilities within their respective districts and collect summaries of aggregated data using national HMIS summary forms. Service delivery staff within health facilities record data in standard government HMIS registers. The information is then entered into District Health Information System (DHIS) software.9 DHIS is a national data warehouse coordinated by the MOHSW and University of Dar es Salaam Department of Computer Science. The DHIS database keeps record of data for a minimum of 46 indicators commonly known as indicators for the third revision of the Tanzanian Health System’s Strategic Plan (HSSP III). HSSP III indicators include information on diseases and conditions such as measles, DPT-Hb3, HIV/AIDS, malaria, tuberculosis, leprosy, cholera, high blood pressure and on health status such as neonatal, infant, under-five and maternal mortality. All diagnostic information at facility level is collected from both outpatient and inpatient departments. Aggregate data stored in the DHIS database can be stratified in various ways including by age grou (5 years), sex, organization units and period of aggregation. Box 2 shows a summary list of the variables included for both the SAVVY and the FBIS arms of the SPD.
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Figure 2. Summary of SAVVY birth and death event notification and VA processing. A ¼ End of the process; E ¼ Enumeration area.
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Box 2. Summary list of variables for the SAVVY and FBIS arms of the SPD platform SAVVY census Identification section (including region name, district name, ward name, enumeration area, description of the location/ household), respondent counts, recent household deaths, lists of household members with their corresponding sex, date of birth (and complete age in years), school attendance, highest grade of education completed, current work status, information on biological mother and father, and for household female members aged 12 – 49 years: how many children they have, date of birth of their last born, type of birth, sex of last born, where is/current status of last born, if last born was twin, what sex was the other twin SAVVY active monitoring of vital events (births and deaths) Identification section (including region name, district name, ward name, enumeration area, description of the location/ ber of children, mother’s education, mother’s occupation, father’s name, father’s education, father’s occupation, type of birth (singleton/multiple), baby’s name, baby’s date of birth, baby’s sex, baby’s status, if multiple birth: name, sex, and status of the twin SAVVY verbal autopsy Include a long list of variables in three age-group questionnaires: children under 4 weeks (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, mother’s pregnancy and delivery history, condition of baby soon after birth, neonatal illness history, mother’s health and contextual factors, treatment and health service use for the final illness, and data extracted from death certificate and health records); children aged 4 weeks to 14 years (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, history of previously known medical conditions including injuries, symptoms and signs noted during final illness of infants, status of mother and symptoms noted during the final illness for all children, treatment and health service use for the final illness, data extracted from death certificate and health records); and those of age 15 years and above (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, history of previously known medical conditions including injuries, signs and symptoms associated with illness of women, signs and symptoms associated with pregnancy, signs and symptoms associated with final illness, treatment and health service use for the final illness, risk factors, data extracted from death certificate and health records). Complete list and verbal autopsy questionnaires can be downloaded from: [http://www.cpc.unc.edu/measure/tools/monitoring-evaluation-systems/savvy] SAVVY causes of death Disease or condition directly leading to death, antecedent causes, other significant conditions contributing to the death, but not related to the disease or conditions causing it FBIS The FBIS collects data for many variables from different sources of data in health facilities. The key groupings include variables on: notifiable and non-notifiable communicable diseases for both under-5 years and 5þ year-olds, facilitybased national HIV care and ART treatment programme (both monthly and quarterly), Extended Programme for Immunization (EPI variables including BCG, polio, DPT Hep B1,2,3, measles, tetanus toxoid and micronutrients), quarterly reporting of stocks for essential drugs, monthly counselling and testing services (both voluntary and provider-initiated), Infectious Disease Reporting System (IDRS), maternal health service [including antenatal care, family planning, labour and delivery ward data on delivery outcomes, referrals, maternal deaths, early and late neonatal deaths, stillbirths, delivery complications, EmONC interventions,and postnatal care, Prevention of Mother to Child Transmission of HIV/AIDS (PMTCT) antenatal and postpartum, sexually transmitted infections]
SAVVY data resource use Due to national representativeness, data generated from SPD’s SAVVY are of important use for national-level planning. Box 3 shows the basic characteristics of SAVVY districts. The majority (70%) of the population lives in rural districts. Women outnumber men and have lower death
proportions than men. Table 1 shows that SAVVY demographic indicators are similar to national indicators based on the 2012 National Population and Household Census. The population pyramid (Figure 3) shows typical characteristics of a developing country associated with relatively high death and birth rates and low life expectancy.
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household), key informant’s name and identification number, mother’s name, mother’s date of birth, mother’s num-
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Box 3. Values of population characteristics in SAVVY enumeration areas Number of districts
23
Total population
644 217
Males (%)
48%
Population rural (%)
70%
Male baseline crude death counts (%)
52%
Figure 4. General Service Readiness by Domain.
ation areas of 20 SPD districts Indicator Crude birth rate Crude death rate Infant mortality rate Under-five mortality ratio Maternal mortality ratio
a
SAVVY
National
35.7 10.2 47.1 85.7 462.0
38.1 11.8 51.0 81.0 454.0
a
Source: Tanzanian Demographic and Household Survey, 2010.
Figure 3. Population pyramid with SAVVY populations in enumeration areas, 23 districts.
FBIS data resource use IHI generated a full report on Service Availability and Readiness Assessment (SARA).10 The assessment was commissioned by the MOHSW on behalf of the Global Fund to fight AIDS, Tuberculosis and Malaria (GFATM). Using the FBIS infrastructure, IHI conducted the assessment from May to December 2012, covering over 1200 health facilities. The report presented an account of availability and readiness of specific service types, e.g. malaria and HIV treatment services and obstetric care. The general service readiness index (GSR) is a composite measure that combines results from five domains of amenities, equipment, standard precautions for infection prevention, diagnostics, and medicines and commodities. The GSR was low at 42% (Figure 4). Availability of basic equipment scored the
highest, and availability of basic amenities such as power, computers with e-mail/internet access, private consultation room and sanitation facilities scoring the lowest. Availability of medicines in health facilities was also low at 41%. More results of the assessment are found in the full SARA report which can be downloaded from the SPD website.11 The SARA survey will be repeated in 2014/2015. Planned work using the SPD includes evaluation of national programmes and research into health-seeking trajectories, into inequity in access to services and into other social determinants of mortality and fertility. One example is the national roll-out of Performance Based Financing (PBF) in the health sector which will be evaluated in a plausibility design with comparison of service use indicators before and after the implementation of the PBF intervention, both in districts that received the intervention and in control districts to which the PBF has not yet been rolled out. Another planned evaluation is impact of antiretroviral treatment programmes on HIV mortality, using an ecological dose-response analysis for which SPD mortality. Service use data will be complemented with data on need for antiretroviral therapy (ART) based on modelled HIV prevalence. Funding permitting, we will describe to what level inequity (by age, location, education and occupation of mother and father) exists in accessing emergency obstetric care (EmOC) in Tanzania and to what extent these inequities in access are associated with neonatal and maternal mortality. In addition, FBIS data were used in a just-completed PhD thesis that involved a selection of indicators for developing and testing an approach for measuring the implementation strength of focused antenatal care (FANC) and EmOC programmes—as an alternative method for evaluating large-scale maternal health programmes in low- and middle-income countries (Gregory Kabadi, personal communication, unpublished results/submitted for publication/ in preparation). Lastly, using VA interview data, healthseeking trajectories for persons who died from cancer will be investigated to explore where in the screening-to-treatment cascade opportunities for early diagnosis and treatment are missed and for which subgroups.
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Table 1. Basic demographic rates and ratios from enumer-
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Strengths and weaknesses
Data resource access: SPD extends data -sharing policies that are currently put in place by the two arms projects. The FBIS project (facilitybased) is a collaborative work with the Tanzanian Ministry of Health and Social Welfare and follows datsharing policies set by the Ministry. To access FBIS data, an application must be accompanied by a research protocol complying with the Tanzanian National Institute for Medical Research for ethical approval and data protection. More information on ethical guidelines is available at: [http://www.nimr.or.tz/ethical-guidelines/]. Please contact the Permanent Secretary of the Ministry of Health and
Social Welfare by post at P.O Box 9083 Dar es Salaam, Tanzania OR by phone at þ255-22-2120261 OR by filling an elaborate online application at: [http://www.moh.go.tz/ index.php/contact-us]. On the other hand, the SAVVY project (household/community-based) shares access to its aggregated data by joint permission from the Ifakara Health Institute and the US Centers for Disease Control and Prevention (CDC). Researchers and those interested in collaborating with the Ifakara Health Institute should send an e-mail application to the Director of Research and SAVVY’s principal investigator, Dr Honorati Masanja at: [[email protected]]. Currently, basic aggregated data for birth and deaths by district and sex are available in tabular and graphical form at our SAVVY website.12 Shortly, data access will be extended to include top causes of deaths.
Funding This work was supported by the US Centers for Disease Control and Prevention [1U2GPS001990-01]; the Global Fund for fight against AIDS, TB and Malaria; and the Ifakara Health Institute core resources; with support from the governments of the UK; Switzerland; Norway; and Ireland.
Contributors H.M., E.G. and P.S. conceived and designed the platform and submitted the grant proposal. H.M. was the principal investigator. S.M. prepared the sample of districts and enumeration areas from the Tanzania Master Statistical Plan and supervised SAVVY quality assurance. H.M. and G.S.K. designed the forms. G.S.K. and R.A. recruited platform staff. R.A. managed day-to-day activities in SPD districts. I.L. was responsible for data management, data extraction and data cleaning. H.M., G.S.K., S.M., I.L. and R.A. analysed and interpreted the data. G.S.K. prepared the first draft of the manuscript. J.A.S., P.S., E.G. and H.M. critically revised the manuscript. All authors contributed to and approved the final manuscript. H.M. is guarantor. Conflict of interest: None declared.
References 1. Horton R, Murray C, Frenk J. A new initiative and invitation for health monitoring, tracking, and evaluation. Lancet 2008; 371:1139–40. 2. Lozano R, Soliz P, Gakidou E et al. Benchmarking of performance of Mexican states with effective coverage. Lancet 2006;368:1729–41.
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Due to its national representativeness, large study population and vast coverage of different parts of the country with high variations in disease burden, ethnicity, socioeconomic profiles and intensity of implementation of various health programmes, the SPD (as opposed to small-scale surveys and HDSS) allows for programme evaluation and research into inequity and social determinants of health services access and health outcomes with much better estimates. For individual level data from SPD, analysis is limited to a small number of determinants at this point; however, for ecological analysis more determinants can be investigated by complementing SPD data with those from other national surveys such as the National Panel Survey for Poverty Monitoring. SPD is also unique in that unlike most HDSSs in Africa, it includes large metropolitan urban populations, and thus allows for research into urban health. In addition, compared with HDSSs, SPD is relatively cheap to operate due to its limited number of census enumerations. Most active HDSSs run at least two to three rounds of censuses per year compared with only about two SAVVY rounds of censuses (baseline and repeat) within 5 years. The SPD’s SAVVY employs the best practice in sample and demographic surveillance techniques, survey sampling methods and validated VA methods. Despite its notable strength, the SPD platform is demanding in terms of logistical management. Also, contrary to HDSSs, the SPD’s SAVVY does not conduct follow-up visits on events such as pregnancies and thereby is not most suited for research into neonatal health. In- and outmigration of household members are not captured, potentially leading to inaccurate denominator counts in areas with high mobility. Furthermore, the current set-up of the SPD does not provide the infrastructure for patient-level data capture of facility-based information and thus cannot be used to study individual-level determinants of patient service use.
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7. World Health Organization. Verbal Autopsy Standards: Ascertaining and Attributing Causes of Death. Verbal Autopsy Instruments. 2007 version. Geneva: WHO, 2007. 8. World Health Organization. International Classification of Diseases Version 2010. Geneva: WHO, 2010. 9. Tanzania Ministry of Health and Social Welfare. The District Health Information Software version 2. http://www.dhis2.org (17 December 2004, date last accessed). 10. Ifakara Health Institute. Sentinel Panel of Districts: SARA methods. http://spd.ihi.or.tz/sara (15 November 2012, date last accessed) 11. Service Availability and Readiness Assessment. http://spd.ihi.or. tz/sara/download.jsp 12. Ifakara Health Institute. Sentinel Panel of Districts: SAVVY basic results. http://spd.ihi.or.tz/savvy (15 November 2012, date last accessed).
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3. Soleman N, Chandramohan D, Shibuya K. Verbal autopsy: current practices and challenges. Bull World Health Organ 2006;84:239–45. 4. United Republic of Tanzania. Ministry of Finance. Poverty Monitoring. Web, accessed on March 9th, 2011, document available at: http://www.povertymonitoring.go.tz/Mkukuta/ Mkukuta%20English.pdf 5. Victora CG, Black RE, Boerma JT, Bryce J. Measuring impact in the Millennium Development Goal era and beyond: a new approach to large-scale effectiveness evaluations. Lancet 2011;377:85–95. 6. Registration, Insolvency and Trusteeship Agency (RITA) of the Tanzanian Ministry of Justice and Constitutional Affairs. http:// www.rita.go.tz/?lang¼en&pg¼ (12 March 2011, date last accessed).
International Journal of Epidemiology, 2015, Vol. 44, No. 1
Data Resource Profile
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Data Resource Profile: The sentinel panel of districts: Tanzania’s national platform for health impact evaluation Gregory S Kabadi,1,3* Eveline Geubbels,1 Isaac Lyatuu,1 Paul Smithson,1 Richard Amaro,1 Sylvia Meku,2Joanna A Schellenberg3 and Honorati Masanja1 1
Ifakara Health Institute, Dar es Salaam, Tanzania, 2National Bureau of Statistics, Dar es Salaam, Tanzania and 3London School of Hygiene and Tropical Medicine, London, UK *Corresponding author. Sentinel Panel of Districts, Ifakara Health Institute, Plot 463 Kiko Avenue, Mikocheni, Dar es Salaam, Tanzania. E-mail: [email protected] Accepted 27 October 2014
Abstract The Sentinel Panel of Districts (SPD) consists of 23 districts selected to provide nationally representative data on demographic and health indicators in Tanzania. The SPD has two arms: SAVVY and FBIS. SAVVY (SAmple Vital registration with Verbal autopsY) is a demographic surveillance system that provides nationally representative estimates of mortalities based on age, sex, residence and zone. SAVVY covers over 805 000 persons, or about 2% of the Tanzania mainland population, and uses repeat household census every 4–5 years, with ongoing reporting of births, deaths and causes of deaths. The FBIS (Facility-Based Information System) collects routine national health management information system data. These health service use data are collected monthly at all public and private health facilities in SPD districts, i.e. about 35% of all facilities in Mainland Tanzania. Both SAVVY and FBIS systems are capable of generating supplementary information from nested periodic surveys. Additional information about the design of the SPD is available online: access to some of SPD’s aggregate data can be requested by sending an e-mail to [[email protected]]. Key words: Health facility surveillance, demographic and mortality surveillance, representative sample, subSaharan Africa
Key Messages The Tanzanian Sentinel Panel of Districts (SPD): • is a very powerful information platform that generates population-based and facility-based demographic, health and
all-cause and age- and sex-specific mortality data; • is a national sample with results stratified by residence and zones providing comprehensive monitoring for all
government health sector strategic plan indicators; C The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association V
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International Journal of Epidemiology, 2015, Vol. 44, No. 1 • provides an economical and high-quality platform for monitoring and evaluation, with an opportunity for fundamental
and operational research, including research on social determinants of health, equity analyses and health systems intervention evaluation; • will be sustained through a combination of core research and commissioned monitoring and evaluation funding.
Data resource area and population coverage
Each arm of the SPD has obtained its own ethical approval. Both SAVVY and FBIS arms received ethical approval from the Tanzania’s National Institute for Medical Research. SAVVY was further cleared by Centers for Disease Control and Prevention (CDC). Informed consent was elicited from interview participants during SAVVY censuses and verbal autopsy interviews. Informed consent was not required for FBIS data from health facilities review as there was no direct contact with participants and data contained no identification of patients, as these were aggregated at district level. Box 1 describes resource basics.
Investment in global and national health programmes has increased over the past decade and this has led to an increased demand for evidence of the impact made by new programmes in target countries and populations.1 This requires quality information and statistics to track performance, provide accountability, measure impact and assess progress towards common targets such as the Millennium Development Goals.2 This demand has exposed the major gaps in quality and timeliness of health statistics in many low- and middle-income countries (LMIC) and provides an opportunity for countries to improve their health information systems. For example, estimation of mortality and its causes in such countries is usually done by quantification of deaths in a specific area and period, establishing causes of the deaths (for the numerator) and counting the population within the area under study (for the denominator). Quantification of deaths and establishing causes of deaths in communities has been shown to perform well through the use of verbal autopsy methods.3–5 In some respects, Tanzania has a well-elaborated poverty monitoring system, including systems to monitor health-related indicators.4 However, like many LMIC, Tanzania lacks a comprehensive vital registration system and hence is unable to produce nationally representative annual estimates of key demographic variables including mortality rates and causes. To provide a sustainable source of reliable nationally representative data on demographic, population health and health systems indicators, Ifakara Health Institute (IHI) in collaboration with the Tanzanian National Bureau of Statistics (NBS), the Tanzanian National Institute for Medical Research (NIMR) and the Ministry of Health and Social Welfare (MOHSW) created a new initiative called the Sentinel Panel of Districts (SPD). The SPD has design features similar to what has been proposed for the national evaluation platform by Victora et al.5 and was considered ideal for implementing facilitybased and community-based survey modules that would provide routine, annual, nationally representative data. The SPD is also designed with the intention to provide rapid-response enquiries into implementation status and effectiveness of specific policy initiatives including health system reforms. Last, the SPD offers the opportunity for
Box 1. Description of basic resource items Country (and areas covered) Groups covered
Mainland Tanzania; nationally representative sample of 23 (out of 119) districts Individuals in sampled households; all health facilities in SPD districts
Survey type
Repeated cross-sectional demo-
Data collection
Health facilities: first round in 2010
graphic and facility assessment dates
followed by continuous repeated monthly surveys. Households: phased-in baseline censuses from 2011 with repeat censuses planned in 2015, continuous birth and death monitoring and verbal autopsy interviews
Topic headings
Health service use statistics; allcause and specific mortality rates
Funding sources SPD is funded by: the US Centers for Disease Control and Prevention [1U2GPS001990-01]; Ifakara Health Institute core resources, with support from the governments of the UK, Switzerland, Norway, and Ireland; and the Global Fund for fight against AIDS, TB and Malaria
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fundamental and operational research, including research on social determinants of health and equity analyses. SPD covers a total of 23 nationally representative districts of the Mainland Tanzania and is implemented through two arms: the Facility-Based Information System (FBIS) and the SAmple Vital registration with Verbal autopsY (SAVVY). Tanzania’s NBS selected the districts primarily for use in implementing the SAVVY arm. NBS used a two-stage Sampford’s probability with proportion to size sampling method on the 2002 Tanzania Population and Housing Census dataset [Tanzania’s National Bureau of Statistics (Ministry of Planning, Economy and Empowerment) Population and Housing Census 2002]. Data can be obtained by contacting the Director General by e-mail at: [[email protected]]. More information is available at: [http://www.nbs.go.tz/tnada/index.php/catalog/7#page ¼overview&tab¼study-desc]. The 35% coverage of health facilities was based on the number of facilities in the SPD master list compared with the number of health facilities in Mainland Tanzania for 2010. The sample provided estimates for Mainland Tanzania as a whole and included all administrative zones, males/females and urban/rural areas. All special enumeration areas such as schools, hospitals, police and military barracks and all districts involved in demographic monitoring were excluded from the sampling frame. The final SAVVY sample included approximately 167 200 households (or about 7500 households per district), with a population of over 805 000 (or about 2% of Mainland
Tanzania’s population). The FBIS system adopted all SAVVY districts and covers 1608 dispensaries, 193 health centres and 87 hospitals. Figure 1 shows the geographical location of the 23 districts and the governance structure. Overall, implementation of the SPD is led by IHI with support from NBS and NIMR and in close consultation with MOHSW.
SAVVY survey frequency and measures SAVVY started with baseline enumeration censuses in March 2011 and continued in phases until it reached the full scale of all 23 districts in March 2014. Continuous monitoring of vital events and conducting verbal autopsy (VA) interviews in enumeration areas began shortly after commencement of baseline censuses and is done prospectively. Follow-up enumeration censuses will be conducted every 5 years, with a second census round starting in the first districts starting in 2015. SAVVY data collection is grouped into three categories: census enumeration, birth and death notifications and VA interviews. During initial setup of the SAVVY arm, baseline censuses were conducted in all districts enumerating all households within the selected enumeration areas, and captured a snapshot of the population. Each household was visited and family structure data were collected including details of the head of household and each member’s name, gender, occupation and education. Follow-up questions were asked for female household members on
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Figure 1. Geographical locations of districts and types of data from SPDs. b for Mainland Tanzania only (excludes those from Zanzibar).
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number of children. During baseline census, data on retrospective death events of the past 12 months were also collected. A notification system of vital events was set up following the baseline censuses. Each birth or death event occurring in SAVVY enumeration areas triggered a notification message sent by a community key informant using a mobile phone. The procedure is further elaborated in Figure 2. In addition to reporting vital events, SAVVY also promotes vital registration through use of government registers provided by the Registration Insolvency and Trusteeship Agency (RITA).6 Each death notification event is followed by a VA interview with the head of household or a person who took care of the deceased. Interviewers use the three standard World Health Organization’s 2002 VA questionnaires: for newborns (aged 0–28 days), children (aged 29 days-14 years) and adults (aged 15 years and above).7 These questionnaires are designed to collect background information on the deceased including their age, sex, marital status and health data prior to death. Other information collected in verbal autopsy interviews includes history of chronic illness, a narrative account of events leading to death, symptom checklist and duration, lifestyle (use of alcohol, drugs and smoking) and a sequence of use of health services prior to death. All information on verbal autopsy interviews (those captured retrospectively and prospectively during baseline census) is sent to trained physicians in order to establish a probable cause of death. Each death is coded independently using the World Health Organization International Classification of Diseases and Health Related Conditions version 10 (ICD 10).8
FBIS survey frequency and measures FBIS data collection began in January 2010 and is conducted monthly from all health facilities in SPD districts. FBIS data collection and processes involve all health facilities in the district. Each month, FBIS coordinators along with Health Management Information System (HMIS) focal person(s) in the council health management team (CHMT) visit health facilities within their respective districts and collect summaries of aggregated data using national HMIS summary forms. Service delivery staff within health facilities record data in standard government HMIS registers. The information is then entered into District Health Information System (DHIS) software.9 DHIS is a national data warehouse coordinated by the MOHSW and University of Dar es Salaam Department of Computer Science. The DHIS database keeps record of data for a minimum of 46 indicators commonly known as indicators for the third revision of the Tanzanian Health System’s Strategic Plan (HSSP III). HSSP III indicators include information on diseases and conditions such as measles, DPT-Hb3, HIV/AIDS, malaria, tuberculosis, leprosy, cholera, high blood pressure and on health status such as neonatal, infant, under-five and maternal mortality. All diagnostic information at facility level is collected from both outpatient and inpatient departments. Aggregate data stored in the DHIS database can be stratified in various ways including by age grou (5 years), sex, organization units and period of aggregation. Box 2 shows a summary list of the variables included for both the SAVVY and the FBIS arms of the SPD.
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Figure 2. Summary of SAVVY birth and death event notification and VA processing. A ¼ End of the process; E ¼ Enumeration area.
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Box 2. Summary list of variables for the SAVVY and FBIS arms of the SPD platform SAVVY census Identification section (including region name, district name, ward name, enumeration area, description of the location/ household), respondent counts, recent household deaths, lists of household members with their corresponding sex, date of birth (and complete age in years), school attendance, highest grade of education completed, current work status, information on biological mother and father, and for household female members aged 12 – 49 years: how many children they have, date of birth of their last born, type of birth, sex of last born, where is/current status of last born, if last born was twin, what sex was the other twin SAVVY active monitoring of vital events (births and deaths) Identification section (including region name, district name, ward name, enumeration area, description of the location/ ber of children, mother’s education, mother’s occupation, father’s name, father’s education, father’s occupation, type of birth (singleton/multiple), baby’s name, baby’s date of birth, baby’s sex, baby’s status, if multiple birth: name, sex, and status of the twin SAVVY verbal autopsy Include a long list of variables in three age-group questionnaires: children under 4 weeks (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, mother’s pregnancy and delivery history, condition of baby soon after birth, neonatal illness history, mother’s health and contextual factors, treatment and health service use for the final illness, and data extracted from death certificate and health records); children aged 4 weeks to 14 years (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, history of previously known medical conditions including injuries, symptoms and signs noted during final illness of infants, status of mother and symptoms noted during the final illness for all children, treatment and health service use for the final illness, data extracted from death certificate and health records); and those of age 15 years and above (demographic data, information on deceased and date and place of death, brief account of illness/events leading to death, history of previously known medical conditions including injuries, signs and symptoms associated with illness of women, signs and symptoms associated with pregnancy, signs and symptoms associated with final illness, treatment and health service use for the final illness, risk factors, data extracted from death certificate and health records). Complete list and verbal autopsy questionnaires can be downloaded from: [http://www.cpc.unc.edu/measure/tools/monitoring-evaluation-systems/savvy] SAVVY causes of death Disease or condition directly leading to death, antecedent causes, other significant conditions contributing to the death, but not related to the disease or conditions causing it FBIS The FBIS collects data for many variables from different sources of data in health facilities. The key groupings include variables on: notifiable and non-notifiable communicable diseases for both under-5 years and 5þ year-olds, facilitybased national HIV care and ART treatment programme (both monthly and quarterly), Extended Programme for Immunization (EPI variables including BCG, polio, DPT Hep B1,2,3, measles, tetanus toxoid and micronutrients), quarterly reporting of stocks for essential drugs, monthly counselling and testing services (both voluntary and provider-initiated), Infectious Disease Reporting System (IDRS), maternal health service [including antenatal care, family planning, labour and delivery ward data on delivery outcomes, referrals, maternal deaths, early and late neonatal deaths, stillbirths, delivery complications, EmONC interventions,and postnatal care, Prevention of Mother to Child Transmission of HIV/AIDS (PMTCT) antenatal and postpartum, sexually transmitted infections]
SAVVY data resource use Due to national representativeness, data generated from SPD’s SAVVY are of important use for national-level planning. Box 3 shows the basic characteristics of SAVVY districts. The majority (70%) of the population lives in rural districts. Women outnumber men and have lower death
proportions than men. Table 1 shows that SAVVY demographic indicators are similar to national indicators based on the 2012 National Population and Household Census. The population pyramid (Figure 3) shows typical characteristics of a developing country associated with relatively high death and birth rates and low life expectancy.
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household), key informant’s name and identification number, mother’s name, mother’s date of birth, mother’s num-
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Box 3. Values of population characteristics in SAVVY enumeration areas Number of districts
23
Total population
644 217
Males (%)
48%
Population rural (%)
70%
Male baseline crude death counts (%)
52%
Figure 4. General Service Readiness by Domain.
ation areas of 20 SPD districts Indicator Crude birth rate Crude death rate Infant mortality rate Under-five mortality ratio Maternal mortality ratio
a
SAVVY
National
35.7 10.2 47.1 85.7 462.0
38.1 11.8 51.0 81.0 454.0
a
Source: Tanzanian Demographic and Household Survey, 2010.
Figure 3. Population pyramid with SAVVY populations in enumeration areas, 23 districts.
FBIS data resource use IHI generated a full report on Service Availability and Readiness Assessment (SARA).10 The assessment was commissioned by the MOHSW on behalf of the Global Fund to fight AIDS, Tuberculosis and Malaria (GFATM). Using the FBIS infrastructure, IHI conducted the assessment from May to December 2012, covering over 1200 health facilities. The report presented an account of availability and readiness of specific service types, e.g. malaria and HIV treatment services and obstetric care. The general service readiness index (GSR) is a composite measure that combines results from five domains of amenities, equipment, standard precautions for infection prevention, diagnostics, and medicines and commodities. The GSR was low at 42% (Figure 4). Availability of basic equipment scored the
highest, and availability of basic amenities such as power, computers with e-mail/internet access, private consultation room and sanitation facilities scoring the lowest. Availability of medicines in health facilities was also low at 41%. More results of the assessment are found in the full SARA report which can be downloaded from the SPD website.11 The SARA survey will be repeated in 2014/2015. Planned work using the SPD includes evaluation of national programmes and research into health-seeking trajectories, into inequity in access to services and into other social determinants of mortality and fertility. One example is the national roll-out of Performance Based Financing (PBF) in the health sector which will be evaluated in a plausibility design with comparison of service use indicators before and after the implementation of the PBF intervention, both in districts that received the intervention and in control districts to which the PBF has not yet been rolled out. Another planned evaluation is impact of antiretroviral treatment programmes on HIV mortality, using an ecological dose-response analysis for which SPD mortality. Service use data will be complemented with data on need for antiretroviral therapy (ART) based on modelled HIV prevalence. Funding permitting, we will describe to what level inequity (by age, location, education and occupation of mother and father) exists in accessing emergency obstetric care (EmOC) in Tanzania and to what extent these inequities in access are associated with neonatal and maternal mortality. In addition, FBIS data were used in a just-completed PhD thesis that involved a selection of indicators for developing and testing an approach for measuring the implementation strength of focused antenatal care (FANC) and EmOC programmes—as an alternative method for evaluating large-scale maternal health programmes in low- and middle-income countries (Gregory Kabadi, personal communication, unpublished results/submitted for publication/ in preparation). Lastly, using VA interview data, healthseeking trajectories for persons who died from cancer will be investigated to explore where in the screening-to-treatment cascade opportunities for early diagnosis and treatment are missed and for which subgroups.
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Table 1. Basic demographic rates and ratios from enumer-
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Strengths and weaknesses
Data resource access: SPD extends data -sharing policies that are currently put in place by the two arms projects. The FBIS project (facilitybased) is a collaborative work with the Tanzanian Ministry of Health and Social Welfare and follows datsharing policies set by the Ministry. To access FBIS data, an application must be accompanied by a research protocol complying with the Tanzanian National Institute for Medical Research for ethical approval and data protection. More information on ethical guidelines is available at: [http://www.nimr.or.tz/ethical-guidelines/]. Please contact the Permanent Secretary of the Ministry of Health and
Social Welfare by post at P.O Box 9083 Dar es Salaam, Tanzania OR by phone at þ255-22-2120261 OR by filling an elaborate online application at: [http://www.moh.go.tz/ index.php/contact-us]. On the other hand, the SAVVY project (household/community-based) shares access to its aggregated data by joint permission from the Ifakara Health Institute and the US Centers for Disease Control and Prevention (CDC). Researchers and those interested in collaborating with the Ifakara Health Institute should send an e-mail application to the Director of Research and SAVVY’s principal investigator, Dr Honorati Masanja at: [[email protected]]. Currently, basic aggregated data for birth and deaths by district and sex are available in tabular and graphical form at our SAVVY website.12 Shortly, data access will be extended to include top causes of deaths.
Funding This work was supported by the US Centers for Disease Control and Prevention [1U2GPS001990-01]; the Global Fund for fight against AIDS, TB and Malaria; and the Ifakara Health Institute core resources; with support from the governments of the UK; Switzerland; Norway; and Ireland.
Contributors H.M., E.G. and P.S. conceived and designed the platform and submitted the grant proposal. H.M. was the principal investigator. S.M. prepared the sample of districts and enumeration areas from the Tanzania Master Statistical Plan and supervised SAVVY quality assurance. H.M. and G.S.K. designed the forms. G.S.K. and R.A. recruited platform staff. R.A. managed day-to-day activities in SPD districts. I.L. was responsible for data management, data extraction and data cleaning. H.M., G.S.K., S.M., I.L. and R.A. analysed and interpreted the data. G.S.K. prepared the first draft of the manuscript. J.A.S., P.S., E.G. and H.M. critically revised the manuscript. All authors contributed to and approved the final manuscript. H.M. is guarantor. Conflict of interest: None declared.
References 1. Horton R, Murray C, Frenk J. A new initiative and invitation for health monitoring, tracking, and evaluation. Lancet 2008; 371:1139–40. 2. Lozano R, Soliz P, Gakidou E et al. Benchmarking of performance of Mexican states with effective coverage. Lancet 2006;368:1729–41.
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Due to its national representativeness, large study population and vast coverage of different parts of the country with high variations in disease burden, ethnicity, socioeconomic profiles and intensity of implementation of various health programmes, the SPD (as opposed to small-scale surveys and HDSS) allows for programme evaluation and research into inequity and social determinants of health services access and health outcomes with much better estimates. For individual level data from SPD, analysis is limited to a small number of determinants at this point; however, for ecological analysis more determinants can be investigated by complementing SPD data with those from other national surveys such as the National Panel Survey for Poverty Monitoring. SPD is also unique in that unlike most HDSSs in Africa, it includes large metropolitan urban populations, and thus allows for research into urban health. In addition, compared with HDSSs, SPD is relatively cheap to operate due to its limited number of census enumerations. Most active HDSSs run at least two to three rounds of censuses per year compared with only about two SAVVY rounds of censuses (baseline and repeat) within 5 years. The SPD’s SAVVY employs the best practice in sample and demographic surveillance techniques, survey sampling methods and validated VA methods. Despite its notable strength, the SPD platform is demanding in terms of logistical management. Also, contrary to HDSSs, the SPD’s SAVVY does not conduct follow-up visits on events such as pregnancies and thereby is not most suited for research into neonatal health. In- and outmigration of household members are not captured, potentially leading to inaccurate denominator counts in areas with high mobility. Furthermore, the current set-up of the SPD does not provide the infrastructure for patient-level data capture of facility-based information and thus cannot be used to study individual-level determinants of patient service use.
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3. Soleman N, Chandramohan D, Shibuya K. Verbal autopsy: current practices and challenges. Bull World Health Organ 2006;84:239–45. 4. United Republic of Tanzania. Ministry of Finance. Poverty Monitoring. Web, accessed on March 9th, 2011, document available at: http://www.povertymonitoring.go.tz/Mkukuta/ Mkukuta%20English.pdf 5. Victora CG, Black RE, Boerma JT, Bryce J. Measuring impact in the Millennium Development Goal era and beyond: a new approach to large-scale effectiveness evaluations. Lancet 2011;377:85–95. 6. Registration, Insolvency and Trusteeship Agency (RITA) of the Tanzanian Ministry of Justice and Constitutional Affairs. http:// www.rita.go.tz/?lang¼en&pg¼ (12 March 2011, date last accessed).
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