Mixed-methods analysis of select issues reported in the 2016 World Health Organization verbal autopsy questionnaire.

BACKGROUND: Use of a standardized verbal autopsy (VA) questionnaire, such as the World Health Organization (WHO) instrument, can improve the consistency and reliability of the data it collects. Systematically revising a questionnaire, however, requires evidence about the performance of its questions. The purpose of this investigation was to use a mixed methods approach to evaluate the performance of questions related to 14 previously reported issues in the 2016 version of the WHO questionnaire, where there were concerns of potential confusion, redundancy, or inability of the respondent to answer the question. The results from this mixed methods analysis are discussed across common themes that may have contributed to the underperformance of questions and have been compiled to inform decisions around the revision of the current VA instrument. METHODS: Quantitative analysis of 19,150 VAs for neonates, children, and adults from five project teams implementing VAs predominately in Sub-Saharan Africa included frequency distributions and cross-tabulations to evaluate response patterns among related questions. The association of respondent characteristics and response patterns was evaluated using prevalence ratios. Qualitative analysis included results from cognitive interviewing, an approach that provides a detailed understanding of the meanings and processes that respondents use to answer interview questions. Cognitive interviews were conducted among 149 participants in Morocco and Zambia. Findings from the qualitative and quantitative analyses were triangulated to identify common themes. RESULTS: Four broad themes contributing to the underperformance or redundancy within the instrument were identified: question sequence, overlap within the question series, questions outside the frame of reference of the respondent, and questions needing clarification. The series of questions associated with one of the 14 identified issues (the series of questions on injuries) related to question sequence; seven (tobacco use, sores, breast swelling, abdominal problem, vomiting, vaccination, and baby size) demonstrated similar response patterns among questions within each series capturing overlapping information. Respondent characteristics, including relationship to the deceased and whether or not the respondent lived with the deceased, were associated with differing frequencies of non-substantive responses in three question series (female health related issues, tobacco use, and baby size). An inconsistent understanding of related constructs was observed between questions related to sores/ulcers, birth weight/baby size, and diagnosis of dementia/presence of mental confusion. An incorrect association of the intended construct with that which was interpreted by the respondent was observed in the medical diagnosis question series. CONCLUSIONS: In this mixed methods analysis, we identified series of questions which could be shortened through elimination of redundancy, series of questions requiring clarification due to unclear constructs, and the impact of respondent characteristics on the quality of responses. These changes can lead to a better understanding of the question constructs by the respondents, increase the acceptance of the tool, and improve the overall accuracy of the VA instrument.

Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa.

BACKGROUND: Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated. OBJECTIVES: To compare the CODs identified by automated VA with those by complete autopsy to examine the validity of a VA tool. METHODS: The study site was the tertiary hospital in the capital city of Zambia. From September 2019 to January 2020, all BID cases aged 13 years and older brought to the hospital during the daytime on weekdays were enrolled in this study. External COD cases were excluded. The deceased's relatives were interviewed using the 2016 World Health Organization VA questionnaire. The data were analyzed using InterVA, an automated VA tool, to determine the CODs, which were compared with the results of complete autopsies. RESULTS: A total of 63 cases were included. The CODs of 50 BID cases were determined by both InterVA and complete autopsies. The positive predictive value of InterVA was 22%. InterVA determined the CODs correctly in 100% cases of maternal CODs, 27.5% cases of noncommunicable disease CODs, and 5.3% cases of communicable disease CODs. Using the three broader disease groups, 56.0% cases were classified in the same groups by both methods. CONCLUSION: While the positive predictive value was low, more than half of the cases were categorized into the same broader categories. However, there are several limitations in this study, including small sample size. More research is required to investigate the factors leading to discrepancies between the CODs determined by both methods to optimize the use of automated VA in Zambia.

Rapid assessment of the civil registration and vital statistics performance of health facilities in the five districts of Zambia: A cross-sectional study.

BACKGROUND: Civil registration and vital statistics (CRVS) are essential administrative tools for accurate statistical data on vital events. However, civil registration coverage is particularly poor in low- and middle-income countries. Currently, CRVS are attracting global attention, as their improvement is considered a priority. While health facility is one of the important actors involved in the management of quality CRVS, its function in CRVS remains unclear. Therefore, this work aims to investigate the CRVS performance of the health facility in Zambia, a low-income country, and identify the gaps for effective policy-making. METHODS: To assess the health facilities' CRVS performance, a questionnaire was developed based on existing assessment tools for the whole CRVS; this comprised 21 multiple-choice questions in 10 areas with four choices awarded between 0 and 3 points according to performance. These questionnaire-based interviews were conducted by information officers in all health facilities per first, secondary, and tertiary-level in five target districts of Zambia, selected via socioeconomic and geographic features. The average points were calculated in each area by each level of healthcare system and summarized in a single chart. RESULTS: The results indicated low scores in the following areas: staff compliance with standard reporting procedures, infrastructure, capacity of coding based on International Classification of Diseases among health personnel, documentation of the cause of death in medical records, and absence of a system to identify the cause of death of brought-in-dead cases. CONCLUSION: The tool developed in this work to evaluate the CRVS performance of health facilities was useful for identifying the gaps that need to be overcome to ensure the quality of CRVS in Zambia. However, its validity should be further investigated in other areas in Zambia as well as in other countries.

Application of verbal autopsy in routine civil registration in Lusaka District of Zambia.

BACKGROUND: Ascertaining the causes for deaths occurring outside health facilities is a significant problem in many developing countries where civil registration systems are not well developed or non-functional. Standardized and rigorous verbal autopsy methods is a potential solution to determine the cause of death. We conducted a demonstration project in Lusaka District of Zambia where verbal autopsy (VA) method was implemented in routine civil registration system. METHODS: About 3400 VA interviews were conducted for bodies "brought-in-dead" at Lusaka's two major teaching hospital mortuaries using a SmartVA questionnaire between October 2017 and September 2018. Probable underlying causes of deaths using VA and cause-specific mortality fractions were determined.. Demographic characteristics were analyzed for each VA-ascertained cause of death. RESULTS: Opportunistic infections (OIs) associated with HIV/AIDS such as pneumonia and tuberculosis, and malaria were among leading causes of deaths among bodies "brought-in-dead". Over 21.6 and 26.9% of deaths were attributable to external causes and non-communicable diseases (NCDs), respectively. The VA-ascertained causes of death varied by age-group and sex. External causes were more prevalent among males in middle ages (put an age range like 30-54 years old) and NCDs highly prevalent among those aged 55 years and older. CONCLUSIONS: VA application in civil registration system can provide the much-needed cause of death information for non-facility deaths in countries with under-developed or non-functional civil registration systems.

Analysis of causes of death among brought-in-dead cases in a third-level Hospital in Lusaka, Republic of Zambia, using the tariff method 2.0 for verbal autopsy: a cross-sectional study.

BACKGROUND: Over one third of deaths in Zambian health facilities involve someone who has already died before arrival (i.e., Brough in Dead), and in most BiD cases, the CoD have not been fully analyzed. Therefore, this study was designed to evaluate the function of automated VA based on the Tariff Method 2.0 to identify the CoD among the BiD cases and the usefulness by comparing the data on the death notification form. METHODS: The target site was one third-level hospital in the Republic of Zambia's capital city. All BiD cases who reached the target health facility from January to August 2017 were included. The deceased's closest relatives were interviewed using a structured VA questionnaire and the data were analyzed using the SmartVA to determine the CoD at the individual and population level. The CoD were compared with description on the death notification forms by using t-test and Cohen's kappa coefficient. RESULTS: One thousand three hundred seventy-eight and 209 cases were included for persons aged 13 years and older (Adult) and those aged 1 month to 13 years old (Child), respectively. The top CoD for Adults were infectious diseases followed by non-communicable diseases and that for Child were infectious diseases, followed by accidents. The proportion of cases with a determined CoD was significantly higher when using the SmartVA (75% for Adult and 67% for Child) than the death notification form (61%). A proportion (42.7% for Adult and 46% for Child) of the CoD-determined cases matched in both sources, with a low concordance rate for Adult (kappa coefficient = 0.1385) and a good for Child(kappa coefficient = 0.635). CONCLUSIONS: The CoD of the BiD cases were successfully analyzed using the SmartVA for the first time in Zambia. While there many erroneous descriptions on the death notification form, the SmartVA could determine the CoD among more BiD cases. Since the information on the death notification form is reflected in the national vital statistics, more accurate and complete CoD data are required. In order to strengthen the death registration system with accurate CoD, it will be useful to embed the SmartVA in Zambia's health information system.