EDITORIALS

 

Increased use of social autopsy is needed to improve maternal, neonatal and child health programmes in low-income countries

 

 

Peter WaiswaI, *; Henry D KalterII; Robert JakobIII; Robert E BlackII

IDepartment of Health Policy Planning and Management, School of Public Health, Makerere University College of Health Sciences, PO Box 7072, Kampala, Uganda
IIDepartment of International Health, John Hopkins University, Bloomberg School of Public Health, Baltimore, United States of America
IIIWorld Health Organization, Geneva, Switzerland

 

 

Although 2015 is only three years away, many countries are not on track to reach the United Nations Millennium Development Goals (MDGs), particularly goals 4 and 5, which call for reductions in child and maternal mortality rates. Targeted interventions are needed for rapid progress to take place. However, reliable estimates of the numbers, causes and determinants of death are needed to design the interventions. Such estimates are the basis of functional health information systems, which are the sources of data for the development and monitoring of evidence-based health policies and programmes.1 Countries unable to record the number of people who die or why they die cannot realize the full potential of their health systems.2 Nonetheless, many countries lack data on the social, behavioural and health systems determinants of child and maternal deaths. In some high-mortality settings, civil registration systems are so deficient that most deaths go unrecorded.3 Globally, fewer than one third of the 350 000 maternal deaths and 7 600 000 child deaths4 occurring annually are medically certified.5

The data needed to estimate cause-specific mortality rates can be obtained through alternative methods such as verbal autopsy, which consists of the use of standardized interview tools to question the caretakers of recently deceased persons about the symptoms that preceded the death.2 Area-specific disease profiles generated from these data can help subnational and national health planners improve health resource allocation, as illustrated by the United Republic of Tanzania's Essential Health Interventions Project.6 Yet despite the resources invested in developing verbal autopsy methods and tools, the non-biological factors contributing to a death cannot be determined from verbal autopsy data. This has led to the development of a complementary interview method known as "social autopsy", which explores the social, behavioural and health systems determinants of maternal and child deaths.7 During social autopsy, the caretaker of the deceased is interviewed in detail regarding any preventive care received by the deceased, the diagnostic procedures followed, the type and timing of any treatment provided inside or outside the home, and any barriers encountered during care seeking.8

While verbal autopsy data can be used to prioritize health problems and evaluate health programme impact, social autopsy data, which focus on modifiable factors present in the home, community and health system, can inform policies and practices for increasing access to and use of preventive and curative services. The data afforded by social autopsy can create awareness that maternal and child deaths are preventable, empower communities to actively participate in interventions for reducing child and maternal deaths, and increase health programme responsiveness and accountability.9

Despite its importance, social autopsy has not been widely practiced and still lacks standard methods for data collection and analysis. Two key models, known as Pathway to Survival10 and Three Delays,11 have been used to organize the care-seeking data generated by social autopsy.8, 9, 12 These models should guide future social autopsy studies, whose aim should be to maximize social autopsy's awareness-raising potential through participatory data sharing and development of interventions.7 The World Health Organization's Child Health Epidemiology Reference Group has been further developing and testing the Pathway to Survival and Three Delays analytical models in several low-income countries. The INDEPTH Network has also been developing its own social autopsy tools. Both groups have identified similar challenges, primarily the need to reduce the number of interview questions to make data collection faster, and to develop a suitable strategy for data analysis.

The standard social autopsy tool intended for use in combination with verbal autopsy is already under review to try to reduce the number of questions, but more resources should be invested in trying to simplify and standardize social autopsy methods and in encouraging the use of social autopsy, which is a new and still unfamiliar method. Resources should also be invested in bringing together interested parties with the aim of reaching consensus on standardized formats and computer-aided data analysis plans. All of these measures will enhance the visibility of social autopsy and promote routine collection and use of quality social autopsy data. Social autopsy instruments should be widely disseminated, along with tools for country adaptation, fieldworker training and community data sharing, and for integration with population-wide surveys. Tools of this type are direly needed for low-income countries to achieve the MDGs established for the reduction of child and maternal mortality.

 

Acknowledgements

Members of the Social Autopsy Working Group in addition to the authors: Rajiv Bahl, Evasius Bauni, Cynthia Boschi-Pinto, Daniel Kadobera, Karin Kallander, Claudio Lanata, Aloysius Mutebi and Rene Salgado.

 

References

1. Murray CJL, Lopez AD, Feehan DM, Peter ST, Yang G. Validation of the symptom pattern method for analyzing verbal autopsy data. PLoS Med 2007;4:e327. doi: 10.1371/journal.pmed.0040327 PMID: 18031196        

2. Baiden F, Bawah A, Biai A, Binka F, Boerma T, Byass P et al. Setting international standards for verbal autopsy. Bull World Health Organ 2007;85:570-1. doi: 10.2471/BLT.07.043745 PMID: 17768508        

3. Setel PW, Macfarlane SB, Szreter S, Mikkelsen L, Jha P, Stout S et al. A scandal of invisibility: making everyone count by counting everyone. Lancet 2007;370:1569-77. doi: 10.1016/S0140-6736(07)61307-5 PMID: 17992727        

4. Bhutta ZA, Chopra M, Axelson H, Berman P, Boerma T, Bryce J et al. Countdown to 2015 decade report (2000-10): taking stock of maternal, newborn, and child survival. Lancet 2010;375:2032-44. doi: 10.1016/S0140-6736(10)60678-2 PMID: 20569843        

5. The world health report 2008: primary health care - now more than ever. Geneva: World Health Organization; 2009.         

6. The International Development Research Centre [Internet]. Tanzania Essential Health Interventions Project. Ottawa: IDRC; 2011. Available from: http://www.idrc.ca/en/ev-3170-201-1-DO_TOPIC.html [accessed 2 May 2012]          .

7. Kalter HDR, Salgado M, Babille M, Koffi AK, Black RE. Social autopsy for maternal and child deaths: a comprehensive literature review to examine the concept and the development of the method. Popul Health Metr 2011;9:45. doi: 10.1186/1478-7954-9-45 PMID: 21819605        

8. Källander K, Kadobera D, Williams TN, Nielsen RT, Yevoo L, Mutebi A et al. Social autopsy: INDEPTH Network experiences of utility, process, practices, and challenges in investigating causes and contributors to mortality. Popul Health Metr 2011;9:44. doi: 10.1186/1478-7954-9-44 PMID: 21819604        

9. Kalter HD, Mohan P, Mishra A, Gaonkar N, Biswas AB, Balakrishnan S et al. Maternal death inquiry and response in India - the impact of contextual factors on defining an optimal model to help meet critical maternal health policy objectives. Health Res Policy Syst 2011;9:41. doi: 10.1186/1478-4505-9-41 PMID: 22128848        

10. Waldman R, Campbel CC, Steketee RW. Overcoming remaining barriers: the pathway to survival (Current Issues in Child Survival Series). Arlington: The Basic Support for Institutionalizing Child Survival (BASICS) Project; 1996.         

11. Thaddeus S, Maine D. Too far to walk: maternal mortality in context. Soc Sci Med 1994;38:1091-110. doi: 10.1016/0277-9536(94)90226-7 PMID: 8042057        

12. Waiswa P, Kallander K, Peterson S, Tomson G, Pariyo GW. Using the three delays model to understand why newborn babies die in eastern Uganda. Trop Med Int Health 2010;15:964-72. doi: 10.1111/j.1365-3156.2010.02557.x PMID: 20636527        

 

 

for the Social Autopsy Working Group
* Correspondence to Peter Waiswa (e-mail: pwaiswa2001@yahoo.com).

World Health Organization Genebra - Genebra - Switzerland
E-mail: bulletin@who.int