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Session XII: Vital Events
Measurement in M&E
Bates Buckner
MEASURE Evaluation
End-of-Phase-III Event, May 22,
2014
www.measureevaluation.org/eop
Births, Deaths, Causes of Death
and Illness
 Primal data elements, challenge to obtain
Long-term Goal – Strong Civil
Registration/Vital Statistics Systems
(CRVS)
 Health & Demographic Surveillance Sites
(HDSS), significant contribution, limitations
Interim and Mid-term Strategies
MEASURE Evaluation Phase III
 SAVVY – SAmple Vital Registration
with Verbal AutopsY
 Post-census enumeration surveys
 Maternal mortality estimation – census and
survey data
This Session
 Experience with SAVVY
 Robert Mswia
 Estimating Maternal
Mortality
 Kavita Singh
www.measureevaluation.org/eop
Strengthening Health Information
and Civil Registration/Vital Statistics
Systems – SAVVY– A Promising Approach
Robert Mswia
MEASURE Evaluation
End-of-Phase-III Event, May 22,
2014
Stepping Stones to a Vital Statistics System
Source: WHO/Health Metrics Network
DSS
SAVVY
SAVVY Data Collection: Census Enumeration
A census enumerator using a Tablet PC, and a
pen-and-paper when needed (Source: SAVVY
Tanzania)
SAVVY Data Collection: Verbal Autopsy Interview
A SAVVY Coordinator
conductingVA interview
for a probable cause of
death (Source: SAVVY
Tanzania)
Active Reporting of SAVVY Vital Events
A SAVVY Facilitator training Key Informants on using mobile
phones for reporting birth and death events in their communities
Different Scenarios – Examples
From 3 Countries Currently
Implementing SAVVY
 Zambia
 Tanzania
 Malawi
Case Study 1: Tanzania
Case Study 2 – Zambia
 SAVVY seen as key strategy for:
 Improving quality and coverage of vital
events
 Building national system of vital
registration
5.0
9.9
1.2
1.3
1.5
1.8
2.4
3.1
3.8
5.6
5.7
5.9
6.2
6.5
9.8
10.9
19.3
4.3
10.2
1.5
0.4
1.6
2.3
1.4
3.1
3.2
4.1
4.8
4.9
9.0
5.9
5.3
4.4
12.2
21.5
25 20 15 10 5 0 5 10 15 20 25
Ill-defined & undetermined causes
All other remaining causes
Maternal causes
Disorders of the kidney
Meningitis
Senility/oldage
Diabetes mellitus
Neoplasms
Stillbirth
Diarrhoeal diseases
Perinatal and neonatal conditions
Pneumonia/ARI
Disease of the circulatory system
Tuberculosis
Malnutrition
Injuries & Accidents
AFI / Malaria
HIV-related diseases
Females
(N=1,282)
Males
(N=1,474)
Example: Output from SAVVY
Zambia – Leading Causes of Death
SAVVY and the Saving Mothers,
Giving Life Initiative (SMGL)
in Zambia
 SAVVY approach adopted for M&E of
SMGL initiative in 4 districts.
 Document change in maternal deaths
before and after implementation of
program interventions
SMGL Zambia: Percent Distribution
of Maternal Deaths by Main Causes
(N = 91 maternal deaths)
SAVVY Implementation in Zambia
and Tanzania – Achievements
 Change in practice: Cause of death
certification based on ICD
 SAVVY data to complement HMIS data
 SAVVY incorporated into national M&E
strategic plans as key data source
Integration, Institutionalization,
Sustainability
 IntegratedinHMIS,M&Eandnationalregistration
bureaus–governmentcommitment
 Involvementofotherministriesandinstitutions
 LinkingCRVS,SAVVYandHMIS
 Capacitybuilding
 Goodwill
Key Issues in Maternal
Mortality-Estimation and
Cause of Death
Kavita Singh
MEASURE Evaluation
End-of-Phase-III Event, May 22, 2014
A Human Rights Issue
 Motherhood and
childhood are
entitled to special
care and
assistance.
UN General Assembly, 1948.
Article 25 of The UN Declaration
of Human Rights
Maternal Mortality Estimation
 Challenges
 Incomplete vital
registration systems
 Large sample sizes
needed for surveys
 Two key activities:
 2010 Bangladesh Maternal
Mortality Survey
 2014 Workshop on
Estimating Maternal
Mortality from Census Data
2010 Bangladesh Maternal
Mortality Survey (2010 BMMS)
 175,000 households surveyed
 Precise estimate of maternal
mortality
 Rich data on socio-
economic and biological/
health services factors
Ascertaining Cause of Death
from the 2010 BMMS
 Sisterhood Method
 Married womenareaskedaboutsurvival status
ofsisters
 Questions on Household Deaths
 Householdswere askedaboutdeaths since 2006
 Verbal Autopsy follow-up
 Householddeaths ofwomen13to49 were followed upwith a
verbal autopsy
Estimation from Census Data
 Largesamplesizesavailable
 Questionscanbeincludedonrecent
deathsandspecificallypregnancy-
relateddeaths
 Yields pregnancy-related mortality
rather than maternal mortality
estimates
 Sub-national level estimation is
possible
Estimation from Census Data
 Need to carefully assess quality of
census data first
 Reporting of adult (female) deaths
 Reporting of pregnancy-related deaths among all
deaths of women of reproductive age
 Reporting of births
 Key Resource: WHO (2013). WHO Guidance
for Measuring Maternal Mortality from a
Census. WHO, Geneva
Cause of Maternal Death
WHO (2010) A global overview of Maternal Mortality.
http://www.childinfo.org/maternal_mortality.html
Cause of Maternal Deaths Globally 1997-2007
Indirect Causes of Maternal Mortality:
A Study of Mozambique
 Post Census Verbal Autopsy Survey Data 2007-2008
 Indirect Causes
 18.2%: HIV; 23.1%: Malaria
 Study also found
 Provincial-level variation in cause of death.
 Population-level data revealed more indirect deaths
than facility-level data.
Singh,K, Moran, A, Story, W, Bailey, P, Chavane, L. Acknowledging HIV and Malaria as Major
Causes of Maternal Mortality in Sub-Saharan Africa: A Study of Mozambique (forthcoming)
Curtis, S, Mswia, R, Weaver E. Application for Measuring Maternal Mortality: Three Case Studies
using Verbal Autopsy. Presentation at the 2013 IUSSP International Population Conference.
Busan, Republic of Korea.
Indirect
Causes of
Maternal
Mortality:
A Study of
Mozambique
Summary
 Survey Methods: Provide a rich source of
information
 Census Method: A promising method of
pregnancy-related mortality estimation
 From a program and policy perspective
 Indirect causes of maternal mortality need attention in
Africa
 Cause of death and sub-national population-level data
are crucial
www.measureevaluation.org/eop

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Vital Events Measurement in M&E

  • 1. Session XII: Vital Events Measurement in M&E Bates Buckner MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  • 3. Births, Deaths, Causes of Death and Illness  Primal data elements, challenge to obtain
  • 4. Long-term Goal – Strong Civil Registration/Vital Statistics Systems (CRVS)  Health & Demographic Surveillance Sites (HDSS), significant contribution, limitations
  • 5. Interim and Mid-term Strategies MEASURE Evaluation Phase III  SAVVY – SAmple Vital Registration with Verbal AutopsY  Post-census enumeration surveys  Maternal mortality estimation – census and survey data
  • 6. This Session  Experience with SAVVY  Robert Mswia  Estimating Maternal Mortality  Kavita Singh
  • 8. Strengthening Health Information and Civil Registration/Vital Statistics Systems – SAVVY– A Promising Approach Robert Mswia MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  • 9. Stepping Stones to a Vital Statistics System Source: WHO/Health Metrics Network DSS SAVVY
  • 10. SAVVY Data Collection: Census Enumeration A census enumerator using a Tablet PC, and a pen-and-paper when needed (Source: SAVVY Tanzania)
  • 11. SAVVY Data Collection: Verbal Autopsy Interview A SAVVY Coordinator conductingVA interview for a probable cause of death (Source: SAVVY Tanzania)
  • 12. Active Reporting of SAVVY Vital Events A SAVVY Facilitator training Key Informants on using mobile phones for reporting birth and death events in their communities
  • 13. Different Scenarios – Examples From 3 Countries Currently Implementing SAVVY  Zambia  Tanzania  Malawi
  • 14. Case Study 1: Tanzania
  • 15. Case Study 2 – Zambia  SAVVY seen as key strategy for:  Improving quality and coverage of vital events  Building national system of vital registration
  • 16. 5.0 9.9 1.2 1.3 1.5 1.8 2.4 3.1 3.8 5.6 5.7 5.9 6.2 6.5 9.8 10.9 19.3 4.3 10.2 1.5 0.4 1.6 2.3 1.4 3.1 3.2 4.1 4.8 4.9 9.0 5.9 5.3 4.4 12.2 21.5 25 20 15 10 5 0 5 10 15 20 25 Ill-defined & undetermined causes All other remaining causes Maternal causes Disorders of the kidney Meningitis Senility/oldage Diabetes mellitus Neoplasms Stillbirth Diarrhoeal diseases Perinatal and neonatal conditions Pneumonia/ARI Disease of the circulatory system Tuberculosis Malnutrition Injuries & Accidents AFI / Malaria HIV-related diseases Females (N=1,282) Males (N=1,474) Example: Output from SAVVY Zambia – Leading Causes of Death
  • 17. SAVVY and the Saving Mothers, Giving Life Initiative (SMGL) in Zambia  SAVVY approach adopted for M&E of SMGL initiative in 4 districts.  Document change in maternal deaths before and after implementation of program interventions
  • 18. SMGL Zambia: Percent Distribution of Maternal Deaths by Main Causes (N = 91 maternal deaths)
  • 19. SAVVY Implementation in Zambia and Tanzania – Achievements  Change in practice: Cause of death certification based on ICD  SAVVY data to complement HMIS data  SAVVY incorporated into national M&E strategic plans as key data source
  • 20. Integration, Institutionalization, Sustainability  IntegratedinHMIS,M&Eandnationalregistration bureaus–governmentcommitment  Involvementofotherministriesandinstitutions  LinkingCRVS,SAVVYandHMIS  Capacitybuilding  Goodwill
  • 21. Key Issues in Maternal Mortality-Estimation and Cause of Death Kavita Singh MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  • 22. A Human Rights Issue  Motherhood and childhood are entitled to special care and assistance. UN General Assembly, 1948. Article 25 of The UN Declaration of Human Rights
  • 23. Maternal Mortality Estimation  Challenges  Incomplete vital registration systems  Large sample sizes needed for surveys  Two key activities:  2010 Bangladesh Maternal Mortality Survey  2014 Workshop on Estimating Maternal Mortality from Census Data
  • 24. 2010 Bangladesh Maternal Mortality Survey (2010 BMMS)  175,000 households surveyed  Precise estimate of maternal mortality  Rich data on socio- economic and biological/ health services factors
  • 25. Ascertaining Cause of Death from the 2010 BMMS  Sisterhood Method  Married womenareaskedaboutsurvival status ofsisters  Questions on Household Deaths  Householdswere askedaboutdeaths since 2006  Verbal Autopsy follow-up  Householddeaths ofwomen13to49 were followed upwith a verbal autopsy
  • 26. Estimation from Census Data  Largesamplesizesavailable  Questionscanbeincludedonrecent deathsandspecificallypregnancy- relateddeaths  Yields pregnancy-related mortality rather than maternal mortality estimates  Sub-national level estimation is possible
  • 27. Estimation from Census Data  Need to carefully assess quality of census data first  Reporting of adult (female) deaths  Reporting of pregnancy-related deaths among all deaths of women of reproductive age  Reporting of births  Key Resource: WHO (2013). WHO Guidance for Measuring Maternal Mortality from a Census. WHO, Geneva
  • 28. Cause of Maternal Death WHO (2010) A global overview of Maternal Mortality. http://www.childinfo.org/maternal_mortality.html Cause of Maternal Deaths Globally 1997-2007
  • 29. Indirect Causes of Maternal Mortality: A Study of Mozambique  Post Census Verbal Autopsy Survey Data 2007-2008  Indirect Causes  18.2%: HIV; 23.1%: Malaria  Study also found  Provincial-level variation in cause of death.  Population-level data revealed more indirect deaths than facility-level data. Singh,K, Moran, A, Story, W, Bailey, P, Chavane, L. Acknowledging HIV and Malaria as Major Causes of Maternal Mortality in Sub-Saharan Africa: A Study of Mozambique (forthcoming) Curtis, S, Mswia, R, Weaver E. Application for Measuring Maternal Mortality: Three Case Studies using Verbal Autopsy. Presentation at the 2013 IUSSP International Population Conference. Busan, Republic of Korea.
  • 31. Summary  Survey Methods: Provide a rich source of information  Census Method: A promising method of pregnancy-related mortality estimation  From a program and policy perspective  Indirect causes of maternal mortality need attention in Africa  Cause of death and sub-national population-level data are crucial