The quality and diagnostic value of open narratives in verbal autopsy: a mixed-methods analysis of partnered interviews from Malawi

Background Verbal autopsy (VA), the process of interviewing a deceased’s family or caregiver about signs and symptoms leading up to death, employs tools that ask a series of closed questions and can include an open narrative where respondents give an unprompted account of events preceding death. The extent to which an individual interviewer, who generally does not interpret the data, affects the quality of this data, and therefore the assigned cause of death, is poorly documented. We aimed to examine inter-interviewer reliability of open narrative and closed question data gathered during VA interviews. Methods During the introduction of VA data collection, as part of a larger study in Mchinji district, Malawi, we conducted partner interviews whereby two interviewers independently recorded open narrative and closed questions during the same interview. Closed questions were collected using a smartphone application (mobile-InterVA) and open narratives using pen and paper. We used mixed methods of analysis to evaluate the differences between recorded responses to open narratives and closed questions, causes of death assigned, and additional information gathered by open narrative. Results Eighteen partner interviews were conducted, with complete data for 11 pairs. Comparing closed questions between interviewers, the median number of differences was 1 (IQR: 0.5–3.5) of an average 65 answered; mean inter-interviewer concordance was 92 % (IQR: 92–99 %). Discrepancies in open narratives were summarized in five categories: demographics, history and care-seeking, diagnoses and symptoms, treatment and cultural. Most discrepancies were seen in the reporting of diagnoses and symptoms (e.g., malaria diagnosis); only one pair demonstrated no clear differences. The average number of clinical symptoms reported was 9 in open narratives and 20 in the closed questions. Open narratives contained additional information on health seeking and social issues surrounding deaths, which closed questions did not gather. Conclusions The information gleaned during open narratives was subject to inter-interviewer variability and contained a limited number of symptom indicators, suggesting that their use for assigning cause of death is questionable. However, they contained rich information on care-seeking, healthcare provision and social factors in the lead-up to death, which may be a valuable source of information for promoting accountable health services

Reliability of Community Health Worker Collected Data for Planning and Policy in a Peri-Urban Area of Kisumu, Kenya

A general introduction of this article is as follows: Reliable and timely health information is an essential foundation of public health action and health systems strengthening, both nationally and internationally (Aqil et al. in Health Policy Plan 24(3): 217–228, 2009; Bradshaw et al. in initial burden of disease estimates for South Africa, 2000. South African Medical Research Council, Cape Town, 2003). The need for sound information is especially urgent in the case of emergent diseases and other acute health threats, where rapid awareness, investigation and response can save lives and prevent broader national outbreaks and even global pandemics (Aqil et al. in Health Policy Plan 24(3): 217–228, 2009). The government of Kenya, through the ministry of public health and sanitation has rolled out the community health strategy as a way of improving health care at the household level. This involves community health workers collecting health status data at the household level, which is then used for dialogue at all the levels to inform decisions and actions towards improvement in health status. A lot of health interventions have involved the community health workers in reaching out to the community, hence successfully implementing these health interventions. Large scale involvement of community health workers in government initiatives and most especially to collect health data for use in the health systems has been minimal due to the assumption that the data may not be useful to the government, because its quality is uncertain. It was therefore necessary that the validity and reliability of the data collected by community health workers be determined, and whether this kind of data can be used for planning and policy formulation for the communities from which it is collected. This would go a long way to settle speculation on whether the data collected by these workers is valid and reliable for use in determining the health status, its causes and distribution, of a community. Our general objective of this article is to investigate the validity and reliability of Community Based Information, and we deal with research question “What is the reliability of data collected at the Community level by Community health workers?”. The methods which we use to find an reliable answer to this question is “Ten percent of all households visited by CHWs for data collection were recollected by a technically trained team. Test/retest method was applied to the data to establish reliability. The Kappa score, sensitivity, specificity and positive predictive values were also used to measure reliability”. Finally our findings are as follows: Latrine availability and Antenatal care presented good correspondence between the two sets of data. This was also true for exclusive breast feeding indicator. Measles immunization coverage showed less consistency than the rest of the child health indicators. At last we conclude and recommend that CHWs can accurately and reliably collect household data which can be used for health decisions and actions especially in resource poor settings where other approaches to population based data are too expensive

Women's groups practising participatory learning and action to improve maternal and newborn health in low-resource settings: a systematic review and meta-analysis

Maternal and neonatal mortality rates remain high in many low-income and middle-income countries. Different approaches for the improvement of birth outcomes have been used in community-based interventions, with heterogeneous effects on survival. We assessed the effects of women's groups practising participatory learning and action, compared with usual care, on birth outcomes in low-resource settings

Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards

Background: InterVA is a widely disseminated tool for cause of death attribution using information from verbal autopsies. Several studies have attempted to validate the concordance and accuracy of the tool, but the main limitation of these studies is that they compare cause of death as ascertained through hospital record review or hospital discharge diagnosis with the results of InterVA. This study provides a unique opportunity to assess the performance of InterVA compared to physician-certified verbal autopsies (PCVA) and alternative automated methods for analysis.Methods: Using clinical diagnostic gold standards to select 12,542 verbal autopsy cases, we assessed the performance of InterVA on both an individual and population level and compared the results to PCVA, conducting analyses separately for adults, children, and neonates. Following the recommendation of Murray et al., we randomly varied the cause composition over 500 test datasets to understand the performance of the tool in different settings. We also contrasted InterVA with an alternative Bayesian method, Simplified Symptom Pattern (SSP), to understand the strengths and weaknesses of the tool.Results: Across all age groups, InterVA performs worse than PCVA, both on an individual and population level. On an individual level, InterVA achieved a chance-corrected concordance of 24.2% for adults, 24.9% for children, and 6.3% for neonates (excluding free text, considering one cause selection). On a population level, InterVA achieved a cause-specific mortality fraction accuracy of 0.546 for adults, 0.504 for children, and 0.404 for neonates. The comparison to SSP revealed four specific characteristics that lead to superior performance of SSP. Increases in chance-corrected concordance are attained by developing cause-by-cause models (2%), using all items as opposed to only the ones that mapped to InterVA items (7%), assigning probabilities to clusters of symptoms (6%), and using empirical as opposed to expert probabilities (up to 8%).Conclusions: Given the widespread use of verbal autopsy for understanding the burden of disease and for setting health intervention priorities in areas that lack reliable vital registrations systems, accurate analysis of verbal autopsies is essential. While InterVA is an affordable and available mechanism for assigning causes of death using verbal autopsies, users should be aware of its suboptimal performance relative to other methods

Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring.

OBJECTIVE: Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. METHODS: A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. FINDINGS: A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. CONCLUSIONS: The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians

The Unequal World of Health Data

Peter Byass argues that less data are available on the health of the poor than of the rich, and discusses several alternative strategies to improve the representativeness of health data

Effect of participatory women's groups facilitated by Accredited Social Health Activists on birth outcomes in rural eastern India: a cluster-randomised controlled trial

BACKGROUND: A quarter of the world's neonatal deaths and 15% of maternal deaths happen in India. Few community-based strategies to improve maternal and newborn health have been tested through the country's government-approved Accredited Social Health Activists (ASHAs). We aimed to test the effect of participatory women's groups facilitated by ASHAs on birth outcomes, including neonatal mortality. METHODS: In this cluster-randomised controlled trial of a community intervention to improve maternal and newborn health, we randomly assigned (1:1) geographical clusters in rural Jharkhand and Odisha, eastern India to intervention (participatory women's groups) or control (no women's groups). Study participants were women of reproductive age (15-49 years) who gave birth between Sept 1, 2009, and Dec 31, 2012. In the intervention group, ASHAs supported women's groups through a participatory learning and action meeting cycle. Groups discussed and prioritised maternal and newborn health problems, identified strategies to address them, implemented the strategies, and assessed their progress. We identified births, stillbirths, and neonatal deaths, and interviewed mothers 6 weeks after delivery. The primary outcome was neonatal mortality over a 2 year follow up. Analyses were by intention to treat. This trial is registered with ISRCTN, number ISRCTN31567106. FINDINGS: Between September, 2009, and December, 2012, we randomly assigned 30 clusters (estimated population 156 519) to intervention (15 clusters, estimated population n=82 702) or control (15 clusters, n=73 817). During the follow-up period (Jan 1, 2011, to Dec 31, 2012), we identified 3700 births in the intervention group and 3519 in the control group. One intervention cluster was lost to follow up. The neonatal mortality rate during this period was 30 per 1000 livebirths in the intervention group and 44 per 1000 livebirths in the control group (odds ratio [OR] 0.69, 95% CI 0·53-0·89). INTERPRETATION: ASHAs can successfully reduce neonatal mortality through participatory meetings with women's groups. This is a scalable community-based approach to improving neonatal survival in rural, underserved areas of India. FUNDING: Big Lottery Fund (UK)

Measuring maternal mortality : an overview of opportunities and options for developing countries

Background:There is currently an unprecedented expressed need and demand for estimates of maternal mortality in developing countries. This has been stimulated in part by the creation of a Millennium Development Goal that will be judged partly on the basis of reductions in maternal mortality by 2015. Methods: Since the launch of the Safe Motherhood Initiative in 1987, new opportunities for data capture have arisen and new methods have been developed, tested and used. This paper provides a pragmatic overview of these methods and the optimal measurement strategies for different developing country contexts. Results: There are significant recent advances in the measurement of maternal mortality, yet also room for further improvement, particularly in assessing the magnitude and direction of biases and their implications for different data uses. Some of the innovations in measurement provide efficient mechanisms for gathering the requisite primary data at a reasonably low cost. No method, however, has zero costs. Investment is needed in measurement strategies for maternal mortality suited to the needs and resources of a country, and which also strengthen the technical capacity to generate and use credible estimates. Conclusion: Ownership of information is necessary for it to be acted upon: what you count is what you do. Difficulties with measurement must not be allowed to discourage efforts to reduce maternal mortality. Countries must be encouraged and enabled to count maternal deaths and act.WJG is funded partially by the University of Aberdeen. OMRC is partially funded by the London School of Hygiene and Tropical Medicine. CS and SA are partially funded by Johns Hopkins University. CAZ is funded by the Health Metrics Network at the World Health Organization. WJG, OMRC, CS and SA are also partially supported through an international research program, Immpact, funded by the Bill & Melinda Gates Foundation, the Department for International Development, the European Commission and USAID