Dataset Information

Four delays of child mortality in Rwanda: a mixed methods analysis of verbal social autopsies.

ABSTRACT:

Objectives

We sought to understand healthcare-seeking patterns and delays in obtaining effective treatment for rural Rwandan children aged 1-5 years by analysing verbal and social autopsies (VSA). Factors in the home, related to transport and to quality of care in the formal health sector (FHS) were thought to contribute to delays.

Design

We collected quantitative and qualitative cross-sectional data using the validated 2012 WHO VSA tool. Descriptive statistics were performed. We inductively and deductively coded narratives using the three delays model, conducted thematic content analysis and used convergent mixed methods to synthesise findings.

Setting

The study took place in the catchment areas of two rural district hospitals in Rwanda-Kirehe and Southern Kayonza. Participants were caregivers of children aged 1-5 years who died in our study area between March 2013 and February 2014.

Results

We analysed 77 VSAs. Although 74% of children (n=57) had contact with the FHS before dying, most (59%, n=45) died at home. Many caregivers (44%, n=34) considered using traditional medicine and 23 (33%) actually did. Qualitative themes reflected difficulty recognising the need for care, the importance of traditional medicine, especially for 'poisoning' and poor perceived quality of care. We identified an additional delay-phase IV-which occurred after leaving formal healthcare facilities. These delays were associated with caregiver dissatisfaction or inability to adhere to care plans.

Conclusion

Delays in deciding to seek care (phase I) and receiving quality care in FHS (phase III) dominated these narratives; delays in reaching a facility (phase II) were rarely discussed. An unwillingness or inability toadhere to treatment plans after leaving facilities (phase IV) were an important additional delay. Improving quality of care, especially provider capacity to communicate danger signs/treatment plans and promote adherence in the presence of alternative explanatory models informed by traditional medicine, could help prevent childhood deaths.

SUBMITTER: Roder-DeWan S

PROVIDER: S-EPMC6549629 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Four delays of child mortality in Rwanda: a mixed methods analysis of verbal social autopsies.

Roder-DeWan Sanam S Gupta Neil N Kagabo Daniel M DM Habumugisha Lameck L Nahimana Evrard E Mugeni Catherine C Bucyana Tatien T Hirschhorn Lisa R LR

BMJ open 20190527 5

<h4>Objectives</h4>We sought to understand healthcare-seeking patterns and delays in obtaining effective treatment for rural Rwandan children aged 1-5 years by analysing verbal and social autopsies (VSA). Factors in the home, related to transport and to quality of care in the formal health sector (FHS) were thought to contribute to delays.<h4>Design</h4>We collected quantitative and qualitative cross-sectional data using the validated 2012 WHO VSA tool. Descriptive statistics were performed. We ...[more]

PMID: 31133592

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Project description:BackgroundThe WHO standardised verbal autopsy (VA) instrument includes closed questions, ascertaining signs and symptoms of illness preceding death, and an optional open narrative. As VA analyses increasingly use automated algorithms, inclusion of narratives should be justified. We evaluated the role of open narratives on VA processes, data quality and respondent's emotional stress.MethodsA mixed-methods analysis was conducted using VA data for child deaths (0-59 months), between April 2013 and November 2016 in Mchinji district, Malawi. Deaths were prospectively randomised to receive closed questions only or open narrative followed by closed questions. On concluding the VA, interviewers self-completed questions on respondents' emotional stress. Logistic regression was used to determine associations with visible emotional distress during VAs. A group discussion with interviewers was conducted at the project end, to understand field experiences and explore future recommendations; data were coded using deductive themes.Results2509 VAs were included, with 49.8% (n=1341) randomised to open narratives. Narratives lasted a median of 7 minuntes (range: 1-113). Interviewers described improved rapport and felt narratives improved data quality, although there was no difference in the proportion of deaths with an indeterminate cause using an automated algorithm (5.3% vs 6.1%). The majority of respondents did not display visible emotional stress (81%). Those with a narrative had higher, but not statistically significant, odds of emotional distress (adjusted OR: 1.20; 95% CI: 0.98 to 1.47). Factors associated with emotional stress were: infant deaths versus neonates; deaths at a health centre or en-route to hospital versus home; and higher socioeconomic status. Non-parental respondents and increased time between death and interview were associated with lower odds of emotional distress.ConclusionConducting an open narrative may help build rapport, something valued by the interviewers. However, additional time and emotional burdens should be further justified, with quality and utility of narratives promoted through standardised recommendations.

Project description:BackgroundFollowing data access and storage concerns, Government of India transferred the management of its Sample Registration System (SRS) based mortality surveillance (formerly known as the Million Death Study) to an Indian agency. This paper introduces the new system, challenges it faced and its vision for future.MethodsThe All India Institute of Medical Sciences (AIIMS), New Delhi, the new nodal agency, established the "Mortality in India Established through Verbal Autopsy" (MINErVA) platform with state level partners across India in November 2017. The network in its first three years has undertaken capacity building of supervisors conducting verbal autopsy under the SRS, established a panel of trained physician reviewers and developed three IT-based platforms for training, quality control and coding. Coding of VA forms started from January 2015 onwards, and the cause specific mortality fractions (CSMF) of the first 14 185 adult verbal autopsy (VA) records for 2015 were compared with earlier published data for 2010-2013 to check for continuity of system performance.ResultsThe network consists of 25 institutions and a panel of 676 trained physician reviewers. 916 supervisors have been trained in conducting verbal autopsies. More than 75 000 VA forms have been coded to date. The median time taken for finalizing cause of death on the coding platform is 37 days. The level of physician agreement (67%) and proportion of VA forms requiring adjudication (12%) are consistent with published literature. Preliminary CSMF estimates for 2015 were comparable with those for 2010-2013 and identified same top ten causes of death. In addition to the delay, two major challenges identified for coding were language proficiency of physician reviewers vis-à-vis language of narratives and quality of verbal autopsies. While an initial strategic decision was made to consolidate the system to ensure continuity, future vision of the network is to move towards technology-based solutions including electronic data capture of VAs and its analysis and improving the use of mortality data in decision making.ConclusionMINErVA network is now fully functional and is moving towards achieving global standards. It provides valuable lessons for other developing countries to establish their own mortality surveillance systems.

Project description:BackgroundUnderstanding the determinants of preventable deaths of children under the age of five is important for accelerated annual declines - even as countries achieve the UN's Millennium Development Goals and the target date of 2015 has been reached. While research has documented the extent and nature of the overall rapid decline in child mortality in Niger, there is less clear evidence to provide insight into the contributors to such deaths. This issue is the central focus of this paper.MethodsWe analyzed a nationally representative cross-sectional sample of 620 child deaths from the 2012 Niger Verbal Autopsy/Social Autopsy (VASA) Survey. We conducted a descriptive analysis of the data on preventive and curative care, guided by the coverage of proven indicators along the continuum of well child care and illness recognition and care-seeking for child illnesses encompassed by the BASICS/CDC Pathway to Survival model.ResultsSix hundred twenty deaths of children (1-59 months of age) were confirmed from the VASA survey. The majority of these children lived in households with precarious socio-economic conditions. Among the 414 children whose fatal illnesses began at age 0-23 months, just 24.4% were appropriately fed. About 24% of children aged 12-59 months were fully immunized. Of 601 children tracked through the Pathway to Survival, 62.4% could reach the first health care provider after about 67 minutes travel time. Of the 306 children who left the first health care provider alive, 161 (52.6%) were not referred for further care nor received any home care recommendations, and just 19% were referred to a second provider. About 113 of the caregivers reported cost (35%), distance (35%) and lack of transport (30%) as constraints to care-seeking at a health facility.ConclusionDespite Niger's recent major achievements in reducing child mortality, the following determinants are crucial to continue building on the gains the country has made: improved socio-economic state of the poor in the country, investment in women's education, adoption of the a law to prevent marriage of young girls before 18 years of age, and implementation of health programs that encourage breastfeeding and complementary feeding, immunization, illness recognition, prompt and appropriate care-seeking, and improved referral rates.

Project description:BackgroundTo accelerate progress toward the Millennium Development Goal 4, reliable information on causes of child mortality is critical. With more national verbal autopsy (VA) studies becoming available, how to improve consistency of national VA derived child causes of death should be considered for the purpose of global comparison. We aimed to adapt a standardized computer algorithm to re-analyze national child VA studies conducted in Uganda, Rwanda and Ghana recently, and compare our results with those derived from physician review to explore issues surrounding the application of the standardized algorithm in place of physician review.Methods and findingsWe adapted the standardized computer algorithm considering the disease profile in Uganda, Rwanda and Ghana. We then derived cause-specific mortality fractions applying the adapted algorithm and compared the results with those ascertained by physician review by examining the individual- and population-level agreement. Our results showed that the leading causes of child mortality in Uganda, Rwanda and Ghana were pneumonia (16.5-21.1%) and malaria (16.8-25.6%) among children below five years and intrapartum-related complications (6.4-10.7%) and preterm birth complications (4.5-6.3%) among neonates. The individual level agreement was poor to substantial across causes (kappa statistics: -0.03 to 0.83), with moderate to substantial agreement observed for injury, congenital malformation, preterm birth complications, malaria and measles. At the population level, despite fairly different cause-specific mortality fractions, the ranking of the leading causes was largely similar.ConclusionsThe standardized computer algorithm produced internally consistent distribution of causes of child mortality. The results were also qualitatively comparable to those based on physician review from the perspective of public health policy. The standardized computer algorithm has the advantage of requiring minimal resources from the health care system and represents a promising way to re-analyze national or sub-national VA studies in place of physician review for the purpose of global comparison.

Project description:BackgroundVerbal autopsy (VA) is used to estimate the causes of death in areas with incomplete vital registration systems. The King and Lu method (KL) for direct estimation of cause-specific mortality fractions (CSMFs) from VA studies is an analysis technique that estimates CSMFs in a population without predicting individual-level cause of death as an intermediate step. In previous studies, KL has shown promise as an alternative to physician-certified verbal autopsy (PCVA). However, it has previously been impossible to validate KL with a large dataset of VAs for which the underlying cause of death is known to meet rigorous clinical diagnostic criteria.MethodsWe applied the KL method to adult, child, and neonatal VA datasets from the Population Health Metrics Research Consortium gold standard verbal autopsy validation study, a multisite sample of 12,542 VAs where gold standard cause of death was established using strict clinical diagnostic criteria. To emulate real-world populations with varying CSMFs, we evaluated the KL estimations for 500 different test datasets of varying cause distribution. We assessed the quality of these estimates in terms of CSMF accuracy as well as linear regression and compared this with the results of PCVA.ResultsKL performance is similar to PCVA in terms of CSMF accuracy, attaining values of 0.669, 0.698, and 0.795 for adult, child, and neonatal age groups, respectively, when health care experience (HCE) items were included. We found that the length of the cause list has a dramatic effect on KL estimation quality, with CSMF accuracy decreasing substantially as the length of the cause list increases. We found that KL is not reliant on HCE the way PCVA is, and without HCE, KL outperforms PCVA for all age groups.ConclusionsLike all computer methods for VA analysis, KL is faster and cheaper than PCVA. Since it is a direct estimation technique, though, it does not produce individual-level predictions. KL estimates are of similar quality to PCVA and slightly better in most cases. Compared to other recently developed methods, however, KL would only be the preferred technique when the cause list is short and individual-level predictions are not needed.

Dataset Information

Four delays of child mortality in Rwanda: a mixed methods analysis of verbal social autopsies.

Objectives

Design

Setting

Results

Conclusion

Publications

Four delays of child mortality in Rwanda: a mixed methods analysis of verbal social autopsies.

Similar Datasets

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