Dataset Information

ANACONDA: a new tool to improve mortality and cause of death data.

ABSTRACT: BACKGROUND:The need to monitor the Sustainable Development Goals (SDGs) and to have access to reliable and timely mortality data has created a strong demand in countries for tools that can assist them in this. ANACONDA (Analysis of National Causes of Death for Action) is a new tool developed for this purpose which allows countries to assess how accurate their mortality and cause of death are. Applying ANACONDA will increase confidence and capacity among data custodians in countries about their mortality data and will give them insight into quality problems that will assist the improvement process. METHODS:ANACONDA builds on established epidemiological and demographic concepts to operationalise a series of 10 steps and numerous sub-steps to perform data checks. Extensive use is made of comparators to assess the plausibility of national mortality and cause of death statistics. The tool calculates a composite Vital Statistics Performance Index for Quality (VSPI(Q)) to measure how fit for purpose the data are. Extracts from analyses of country data are presented to show the types of outputs. RESULTS:Each of the 10 steps provides insight into how well the current data is describing different aspects of the mortality situation in the country, e.g. who dies of what, the completeness of the reporting, and the amount and types of unusable cause of death codes. It further identifies the exact codes that should not be used by the certifying physicians and their frequency, which makes it possible to institute a focused correction procedure. Finally, the VSPI(Q) allows periodic monitoring of data quality improvements and identifies priorities for action to strengthen the Civil Registration and Vital Statistics (CRVS) system. CONCLUSIONS:ANACONDA has demonstrated the potential to dramatically improve knowledge about disease patterns as well as the functioning of CRVS systems and has served as a platform for galvanising wider CRVS reforms in countries.

SUBMITTER: Mikkelsen L

PROVIDER: S-EPMC7061487 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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ANACONDA: a new tool to improve mortality and cause of death data.

Mikkelsen Lene L Moesgaard Kim K Hegnauer Michael M Lopez Alan D AD

BMC medicine 20200309 1

<h4>Background</h4>The need to monitor the Sustainable Development Goals (SDGs) and to have access to reliable and timely mortality data has created a strong demand in countries for tools that can assist them in this. ANACONDA (Analysis of National Causes of Death for Action) is a new tool developed for this purpose which allows countries to assess how accurate their mortality and cause of death are. Applying ANACONDA will increase confidence and capacity among data custodians in countries about ...[more]

PMID: 32146907

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Project description:Many states and local areas are affected by the national epidemic of drug-related mortality, which recently has shown signs of a rising "licit-to-illicit drug" death ratio. Appropriate local public health surveillance can help monitor and control this epidemic.Using our state as an example, we sought to illustrate how to describe the changes in drug death rates, causes, and circumstances. In contrast to most other surveillance reports, our approach includes both drug-induced and drug-related deaths as well as both demographic and socioeconomic characteristics of decedents.Cross-sectional study.All residents of the state of Wisconsin.Decedents from 1999 to 2008.Annual numbers and population-based rates of deaths due to drugs, including both identified and unidentified drugs. Information was obtained from death certificates with any of approximately 270 underlying, immediate, or contributing cause-of-death codes from the International Classification of Diseases, 10th Revision.Drug-related death rates increased during much of the 10-year study period, and the male-to-female death ratio rose. The median age at death from drug-related causes was 43 years. Opioid analgesic poisoning surpassed cocaine and heroin poisoning as the most frequent type of fatal drug poisoning. Of all 4828 deaths from drug-related causes--virtually all of which were certified by a county medical examiner or coroner--3410 (71%) were unintentional and 1053 (22%) were suicides. The unintentional-to-suicide death rate ratio grew from 1.6 to 3.5 during the study period. Methadone-related deaths increased from 10 in 1999 to 118 in 2008 (1080%), while benzodiazepine-related deaths rose from 23 to 106 (361%).Although premature deaths from drug use and abuse continue to rise, even surpassing deaths due to motor vehicle crash in some states, "multiple causes of death" information from death certificates is available to monitor their occurrence and nature and to inform selection of prevention strategies.

Project description:BackgroundAccurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments.MethodsWe describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings.ResultsThe proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD.ConclusionsWe provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

Project description:BackgroundAtrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions.Methods and resultsIn the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS2 score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P<0.0001) and age ≥75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P<0.0001) were associated with higher all-cause mortality. Multiple additional characteristics were independently associated with higher mortality, with decreasing creatinine clearance, chronic obstructive pulmonary disease, male sex, peripheral vascular disease, and diabetes being among the most strongly associated (model C-index 0.677).ConclusionsIn a large population of patients anticoagulated for nonvalvular atrial fibrillation, ≈7 in 10 deaths were cardiovascular, whereas <1 in 10 deaths were caused by nonhemorrhagic stroke or systemic embolism. Optimal prevention and treatment of heart failure, renal impairment, chronic obstructive pulmonary disease, and diabetes may improve survival.Clinical trial registrationURL: https://www.clinicaltrials.gov/. Unique identifier: NCT00403767.

Project description:BackgroundTrends in cause-specific mortality in most African countries are currently estimated from epidemiological models because the coverage of the civil registration system is low and national statistics on causes of death are unreliable at the national level. We aim to evaluate the performance of the death notification system in Antananarivo, the capital city of Madagascar, to inform cause-of-death statistics.MethodsInformation on the sex of the deceased, dates of birth and death, and underlying cause of death were transcribed from death registers maintained in Antananarivo. Causes of death were coded in ICD-9 and mapped to cause categories from the Global Burden of Disease 2016 Study (GBD). The performance of the notification system was assessed based on the Vital Statistics Performance Index, including six dimensions: completeness of death registration, quality of cause of death reporting, quality of age and sex reporting, internal consistency, level of cause-specific detail, and data availability and timeliness. We redistributed garbage codes and compared cause-specific mortality fractions in death records and estimates from the GBD with concordance correlation coefficients.ResultsThe death notification system in Antananarivo performed well on most dimensions, although 31% of all deaths registered over the period 1976-2015 were assigned to ICD codes considered as "major garbage codes" in the GBD 2016. The completeness of death notification, estimated with indirect demographic techniques, was higher than 90% in the period 1975-1993, and recent under-five mortality rates were consistent with estimates from Demographic and Health Surveys referring to the capital city. After redistributing garbage codes, cause-specific mortality fractions derived from death notification data were consistent with GBD 2016 for the whole country in the 1990s, with concordance correlation coefficients higher than 90%. There were larger deviations in recent years, with concordance correlation coefficients in 2015 at 0.74 (95% CI 0.66-0.81) for men and 0.81 (95% CI 0.74-0.86) for women.ConclusionsDeath notification in Antananarivo is a low-cost data source allowing real-time mortality monitoring, with a potential to improve disease burden estimates. Further efforts should be directed towards evaluating data quality in urban centers in Madagascar and other African countries to fill important data gaps on causes of death.

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Project description:IntroductionMisclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision-making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories.MethodsThe cause of death data were obtained from the World Health Organization Mortality Database and official country-specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics.ResultsIn 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were "immunodeficiency antibody" (ICD 9: 279-279.1; ICD 10: D80-D80.9) and "immunodeficiency other" (ICD 9: 279, 279.5-279.9; ICD 10: D83-D84.9, D89, D89.8-D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010-012.9; ICD 10: A10-A14, A15-A16.9) contributed the greatest proportion of all HIV misclassified deaths (25-62% per year) over the most years.ConclusionsCorrecting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.

Dataset Information

ANACONDA: a new tool to improve mortality and cause of death data.

Publications

ANACONDA: a new tool to improve mortality and cause of death data.

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