scholarly journals Bayesian hierarchical factor regression models to infer cause of death from verbal autopsy data

2021 ◽  
Author(s):  
Kelly R. Moran ◽  
Elizabeth L. Turner ◽  
David Dunson ◽  
Amy H. Herring
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Regression Models ◽  
Bayesian Hierarchical ◽  
Autopsy Data ◽  
Factor Regression

scholarly journals A Metadata Driven Module for Managing and Interpreting HDSS Verbal Autopsy Datasets using Interva-4 Model

2020 ◽  
Author(s):  
KOULIGA KOMBASSERE ◽  
Gideon Nimako ◽  
Irma Mare
Keyword(s):  
Data Collection ◽  
Longitudinal Studies ◽  
Cause Of Death ◽  
Relational Database ◽  
Verbal Autopsy ◽  
Data Object ◽  
Autopsy Data ◽  
Relational Database Management ◽  
Death Data ◽  
Over Time

Abstract Background: The World Health Organisation provides a standardised survey-based questionnaire for collecting cause of death data. This standardised tool is undergoing iterative changes almost every 3 to 5 years resulting in the redesign of in-use re-adapted questionnaires and their database schemes. Given the size of this questionnaire, its redesign process requiring a lot of time and resources does not allow research centres to update their questionnaire. In addition, the heaviness and the expensive cost of the Physician Certified Verbal Autopsy method used for collected data interpretation, led the emergence of new methods with which data are usually managed in ad hoc fashion by using spreadsheets and Comma Separated Value files. Therefore, these tools not allow preservation of the contextual metadata and also not support recovery and building relationship among data object. While the absence of data object relationships does not facilitate the use of relational database management systems and data preservation over time in longitudinal studies contexts such Health and Demographic surveillance systems.Results: This research used Microsoft Visual studio based on model-driven and metadata architectures associated with R.NET Package,R InterVA function, Google Maps API, eXtensible Mark-up Language and Microsoft SQL Server 2012 to develop a Verbal Autopsy data management platform. This platform assists INDEPTH Network HDSS fields sites to quickly follow the iterative changes of WHO questionnaire through questionnaire generation, data collection and entry, and a mapping layer that translates verbal autopsy CRF to ODK XML data dictionary enabling cause of death data collection in offline mode using handheld devices. In addition, being a R InterVA function aided tool for the interpretation of cause of death data, this web application has an interface for visualising cause of death patterns using Google Maps API.Conclusions: Verbal autopsy data management interpretation over time in the longitudinal studies context such Health and Demographic Surveillance System is feasible. Thereby, possibilities given by metadata-driven to build reliable software architecture for verbal autopsy data collection, interpretation and cause of death patterns visualisation and particularly compliance with regulatory relational database management requirements are achievable.

scholarly journals A comparative analysis of the InterVA model versus physician review in determining causes of neonatal deaths using verbal autopsy data from Nepal

2021 ◽  
Author(s):  
Dinesh Dharel ◽  
Penny Dawson ◽  
Daniel Adeyinka ◽  
Nazeem Muhajarine ◽  
Dinesh Neupane
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Neonatal Sepsis ◽  
Neonatal Death ◽  
Birth Asphyxia ◽  
Neonatal Infection ◽  
Proximate Cause ◽  
Neonatal Deaths ◽  
Physician Review ◽  
Autopsy Data

Abstract Background: Verbal autopsy is a common method of ascertaining the cause of neonatal death in low resource settings where majority of causes of deaths remain unregistered. We aimed to compare the causes of neonatal deaths assigned by computer algorithm-based model, InterVA (Interpreting Verbal Autopsy) with the usual standard of Physician Review of Verbal Autopsy (PRVA) using the verbal autopsy data collected by Morang Innovative Neonatal Intervention (MINI) study in Nepal. Methods: MINI was a prospective community intervention study aimed at managing newborn illnesses at household level. Trained field staff conducted a verbal autopsy of all neonatal deaths during the study period. The cause of death was assigned by two pediatricians, and by using InterVA version 5. Cohen's kappa coefficient was calculated to compare the agreement between InterVA and PRVA assigned proximate cause of death, using STATATM software version 16.1. Results: Among 381 verbal autopsies for neonatal deaths, only 311 (81.6%) were assigned one of birth asphyxia, neonatal infection, congenital anomalies or preterm-related complications as the proximate cause of death by both InterVA and PRVA, while the remaining 70 (18.4%) were assigned other or non-specific causes. The overall agreement between InterVA and PRVA-assigned cause of death categories was moderate (66.5% agreement, kappa=0.47). Moderate agreement was observed for neonatal infection (kappa=0.48) and congenital malformations (kappa=0.49), while it was fair for birth asphyxia (kappa=0.39), and preterm-related complications (kappa=0.31); but there was only slight agreement for neonatal sepsis (kappa=0.19) and neonatal pneumonia (kappa=0.16) as specific causes of death within neonatal infections. Conclusions: We observed moderate overall agreement for major categories of causes of neonatal death assigned by InterVA and PRVA. The moderate agreement was sustained for the classification of neonatal infection but poor for neonatal sepsis and neonatal pneumonia as distinct categories of neonatal infection. Further studies should investigate the comparative effectiveness of an updated version of InterVA with the current standard of assigning the cause of neonatal death through longitudinal and experimental designs.

Ascertaining the cause of death using verbal autopsy data: A probabilitic approach

2010 ◽  
Vol 72 (08/09) ◽  
Author(s):  
H Ramroth ◽  
M Ssennono ◽  
A Sié ◽  
H Becher
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Autopsy Data

scholarly journals Application of verbal autopsy in routine civil registration in Lusaka District of Zambia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
C. Chabila Mapoma ◽  
Brian Munkombwe ◽  
Chomba Mwango ◽  
Bupe Bwalya Bwalya ◽  
Audrey Kalindi ◽  
...  
Keyword(s):  
Middle Ages ◽  
Cause Of Death ◽  
Verbal Autopsy ◽  
Opportunistic Infections ◽  
Civil Registration System ◽  
Registration System ◽  
Civil Registration ◽  
Major Teaching Hospital ◽  
External Causes ◽  
Causes Of Deaths

Abstract 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.

scholarly journals Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

2021 ◽  
Vol 6 (5) ◽  
pp. e005387
Author(s):  
Tim Adair ◽  
Sonja Firth ◽  
Tint Pa Pa Phyo ◽  
Khin Sandar Bo ◽  
Alan D Lopez
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Integration Method ◽  
Mortality Rates ◽  
Vital Statistics ◽  
Death Registration ◽  
Chronic Respiratory Diseases ◽  
Health Goals ◽  
Specific Mortality ◽  
Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

scholarly journals Spatiotemporal mapping and detection of mortality cluster due to cardiovascular disease with Bayesian hierarchical framework using integrated nested Laplace approximation: A discussion of suitable statistic applications in Kersa, Oromia, Ethiopia

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Melkamu Dedefo ◽  
Henry Mwambi ◽  
Sileshi Fanta ◽  
Nega Assefa
Keyword(s):  
Cause Of Death ◽  
Linear Models ◽  
Temporal Distribution ◽  
Mortality Data ◽  
Contributing Factors ◽  
Bayesian Hierarchical ◽  
Hierarchical Framework ◽  
Temporal Models ◽  
Spatio Temporal ◽  
Non Parametric

Cardiovascular diseases (CVDs) are the leading cause of death globally and the number one cause of death globally. Over 75% of CVD deaths take place in low- and middle-income countries. Hence, comprehensive information about the spatio-temporal distribution of mortality due to cardio vascular disease is of interest. We fitted different spatio-temporal models within Bayesian hierarchical framework allowing different space-time interaction for mortality mapping with integrated nested Laplace approximations to analyze mortality data extracted from the health and demographic surveillance system in Kersa District in Hararege, Oromia Region, Ethiopia. The result indicates that non-parametric time trends models perform better than linear models. Among proposed models, one with non-parametric trend, type II interaction and second order random walk but without unstructured time effect was found to perform best according to our experience and. simulation study. An application based on real data revealed that, mortality due to CVD increased during the study period, while administrative regions in northern and south-eastern part of the study area showed a significantly elevated risk. The study highlighted distinct spatiotemporal clusters of mortality due to CVD within the study area. The study is a preliminary assessment step in prioritizing areas for further and more comprehensive research raising questions to be addressed by detailed investigation. Underlying contributing factors need to be identified and accurately quantified.

scholarly journals Minimally invasive autopsy for fetuses and children based on a combination of post-mortem MRI and endoscopic examination: a feasibility study

2019 ◽  
Vol 23 (46) ◽  
pp. 1-104 ◽  
Author(s):  
Celine Lewis ◽  
John C Hutchinson ◽  
Megan Riddington ◽  
Melissa Hill ◽  
Owen J Arthurs ◽  
...  
Keyword(s):  
Minimally Invasive ◽  
Cause Of Death ◽  
Clinical Indication ◽  
Religious Leaders ◽  
Training Requirements ◽  
Less Invasive ◽  
Sudden Unexplained Death ◽  
Unexplained Death ◽  
Minimally Invasive Autopsy ◽  
Autopsy Data

BackgroundLess invasive perinatal and paediatric autopsy methods, such as imaging alongside targeted endoscopy and organ biopsy, may address declining consent rates for traditional autopsy, but their acceptability and accuracy are not known.ObjectivesThe aims of this study were to provide empirical data on the acceptability and likely uptake for different types of autopsy among key stakeholders (study 1); and to analyse existing autopsy data sources to provide estimates of the potential efficacy of less invasive autopsy (LIA) and its projected utility in clinical practice (study 2).Review methodsStudy 1: this was a mixed-methods study. Parents were involved in research design and interpretation of findings. Substudy 1: a cross-sectional survey of 859 parents who had experienced miscarriage, termination of pregnancy for fetal anomaly, stillbirth, infant or child death, and interviews with 20 responders. Substudy 2: interviews with 25 health professionals and four coroners. Substudy 3: interviews with 16 religious leaders and eight focus groups, with 76 members of the Muslim and Jewish community. Study 2: a retrospective analysis of national data in addition to detailed information from an existing in-house autopsy database of > 5000 clinical cases that had undergone standard autopsy to determine the proportion of cases by clinical indication group for which tissue sampling of specific internal organs significantly contributed to the diagnosis.ResultsSubstudy 1: 91% of participants indicated that they would consent to some form of LIA, 54% would consent to standard autopsy, 74% to minimally invasive autopsy (MIA) and 77% to non-invasive autopsy (NIA). Substudy 2: participants viewed LIA as a positive development, but had concerns around the limitations of the technology and de-skilling the workforce. Cost implications, skills and training requirements were identified as implementation challenges. Substudy 3: religious leaders agreed that NIA was religiously permissible, but MIA was considered less acceptable. Community members indicated that they might consent to NIA if the body could be returned for burial within 24 hours. Study 2: in 5–10% of cases of sudden unexplained death in childhood and sudden unexplained death in infants, the final cause of death is determined by routine histological sampling of macroscopically normal organs, predominantly the heart and lungs, and in this group routine histological sampling therefore remains an important aspect of investigation. In contrast, routine histological examination of macroscopically normal organs rarely (< 0.5%) provides the cause of death in fetal cases, making LIA and NIA approaches potentially highly applicable.LimitationsA key limitation of the empirical research is that it is hypothetical. Further research is required to determine actual uptake. Furthermore, because of the retrospective nature of the autopsy data set, findings regarding the likely contribution of organ sampling to final diagnosis are based on extrapolation of findings from historical autopsies, and prospective data collection is required to validate the conclusions.ConclusionsLIA is viable and acceptable (except for unexplained deaths), and likely to increase uptake. Further health economic, performance and implementation studies are required to determine the optimal service configuration required to offer this as routine clinical care.FundingThe National Institute for Health Research Health Technology Assessment programme.

scholarly journals Can verbal autopsy improve the diagnostic accuracy of Physicians in Shanghai? Application of SmartVA

2021 ◽  
Author(s):  
Lei Chen ◽  
Tian Xia ◽  
Rasika Rampatige ◽  
Hang Li ◽  
Tim Adair ◽  
...  
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Medical Records ◽  
Community Health Centers ◽  
Causes Of Death ◽  
Practical Method ◽  
Initial Diagnosis ◽  
Hospital Death ◽  
Routine Practice ◽  
Record Review

Abstract Background Accurate data on causes of death are essential for policy makers and public health experts to plan appropriate health policies and interventions to improve population health. Whereas approximately 30% deaths of Shanghai either occur at home or are not medically attended; the recorded cause of death in these cases may be less reliable than for a hospital death. Verbal Autopsy is a practical method that can help determine causes of death in regions where medical records are insufficient or unavailable. In this research, the smart VA tool was adopted to assign the cause of death of home deaths and to validate the accuracy and efficiency of the tool, the results were compared with routine practice to ascertain the value, if any, of incorporating VA into the diagnostic practices of physician in Shanghai certifying the cause of home deaths. Methods This pilot study selected home deaths certified by 16 community health centers from 3 districts represent urban, suburb, and urban-suburb areas in Shanghai, from December 2017 to June 2018. The medical records for all deaths for which a VA was carried out in these 3 districts during same period were carefully evaluated an independent Medical Record Review (MRR) team. Causes of death from both the SmartVA sample and the UCOD from the MRR were transformed to the SmartVA cause list for comparison. The concordance between the initial diagnosis and MRR UCOD and post-VA diagnosis and MRR UCOD was assessed using Chance Corrected Concordance. Results Overall CSMF accuracy improved from 0.93, based on the initial diagnosis, to 0.96 after the application of SmartVA. The misclassification of the initial diagnosis compared to that from the MRR. 86.3% of the initial diagnoses assigned the correct CODs, after the VA investigation, 90.5% of the post-VA diagnosis assigned the correct CODs. Conclusions Although Shanghai has an established and well-functioning CRVS system, SmartVA for Physicians contributed to an improvement in the accuracy of death certification. In addition, SmartVA may be a useful tool for inferring some special causes of death, such as those CODs classified as undetermined.

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