Redistribution of heart failure deaths using two methods: linkage of hospital records with death certificate data and multiple causes of death data

Heart failure is considered a garbage code when assigned as the underlying cause of death. Reassigning garbage codes to plausible causes reduces bias and increases comparability of mortality data. Two redistribution methods were applied to Brazilian data, from 2008 to 2012, for decedents aged 55 years and older. In the multiple causes of death method, heart failure deaths were redistributed based on the proportion of underlying causes found in matched deaths that had heart failure listed as an intermediate cause. In the hospitalization data method, heart failure deaths were redistributed based on data from the decedents’ corresponding hospitalization record. There were 123,269 (3.7%) heart failure deaths. The method with multiple causes of death redistributed 25.3% to hypertensive heart and kidney diseases, 22.6% to coronary heart diseases and 9.6% to diabetes. The total of 41,324 heart failure deaths were linked to hospitalization records. Heart failure was listed as the principal diagnosis in 45.8% of the corresponding hospitalization records. For those, no redistribution occurred. For the remaining ones, the hospitalization data method redistributed 21.2% to a group with other (non-cardiac) diseases, 6.5% to lower respiratory infections and 9.3% to other garbage codes. Heart failure is a frequently used garbage code in Brazil. We used two redistribution methods, which were straightforwardly applied but led to different results. These methods need to be validated, which can be done in the wake of a recent national study that will investigate a big sample of hospital deaths with garbage codes listed as underlying causes.

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923Quantifying multiple causes of death: Observed patterns in Australia, 2006–2017

International Journal of Epidemiology ◽

10.1093/ije/dyab168.084 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Karen Bishop ◽

Saliu Balogun ◽

James Eynston-Hinkins ◽

Lauren Moran ◽

Margarita Moreno-Betancur ◽

...

Keyword(s):

Cause Of Death ◽

Causes Of Death ◽

International Classification Of Diseases ◽

World Health ◽

Mortality Data ◽

Multiple Causes Of Death ◽

Underlying Causes ◽

Health Organization ◽

The Impact ◽

Multiple Causes

Abstract Background Four fifths of deaths in Australia involve multiple causes, but statistics typically use a single underlying cause of death (UC). The UC approach alone is insufficient for understanding the impact of non-underlying causes and identifying comorbid disease associations at death. Analysis of multiple causes of death (MC) is needed to measure the impact of all causes. We described MC patterns, considering cause-of-death coding and certification practices in Australia. Methods Using deaths registered in Australia from 2006 to 2017 (n = 1773525) coded to the International Classification of Diseases (ICD) and an extended classification (n = 136 causes) based on a World Health Organization short list, we described MCoD data by cause. Age-standardised rates based on UC and MC were compared using the standardised ratio of multiple to underlying causes (SRMU) to estimate the contribution of the cause to mortality compared to using the UC approach. Comorbidity was explored using the cause of death association indicator (CDAI) to compare the observed joint frequency of a contributory-underlying cause combined with expected frequency of the contributory cause (with any UC). Results On average 3.4 conditions caused each death and 24.4% of deaths had 5 plus causes. Largest SRMUs were for genitourinary diseases (8.0), blood diseases (7.8) and musculoskeletal conditions (6.7). CDAIs showed high associations between, for example, accidental alcohol and opioid poisoning, septicaemia and skin infections, and traumatic brain injury and falls. Conclusions MC indicators enhance measures of mortality and reassess the role of causes of death for descriptive and analytical epidemiology. Key messages This research demonstrates the value of MC analysis for Australian mortality data.

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Multiple causes of death related to Chagas' disease in Brazil, 1999 to 2007

Revista da Sociedade Brasileira de Medicina Tropical ◽

10.1590/s0037-86822012000500010 ◽

2012 ◽

Vol 45 (5) ◽

pp. 591-596 ◽

Cited By ~ 15

Author(s):

Francisco Rogerlândio Martins-Melo ◽

Alberto Novaes Ramos Junior ◽

Carlos Henrique Alencar ◽

Jorg Heukelbach

Keyword(s):

Chagas Disease ◽

Causes Of Death ◽

Therapeutic Potential ◽

Public Health Problem ◽

Mortality Data ◽

Major Public Health Problem ◽

Multiple Causes Of Death ◽

Conduction Disorders ◽

Disease Information ◽

Multiple Causes

INTRODUCTION: Chagas' disease is a major public health problem in Brazil and needs extensive and reliable information to support consistent prevention and control actions. This study describes the most common causes of death associated with deaths related to Chagas' disease (underlying or associated cause of death). METHODS: Mortality data were obtained from the Mortality Information System of the Ministry of Health (approximately 9 million deaths). We analyzed all deaths that occurred in Brazil between 1999 and 2007, where Chagas' disease was mentioned on the death certificate as underlying or associated cause (multiple causes of death). RESULTS: There was a total of 53,930 deaths related to Chagas' disease, 44,543 (82.6%) as underlying cause and 9,387 (17.4%) as associated cause. The main diseases and conditions associated with death by Chagas' disease as underlying cause included direct complications of cardiac involvement, such as conduction disorders/arrhythmias (41.4%) and heart failure (37.7%). Cerebrovascular disease (13.2%), ischemic heart disease (13.2%) and hypertensive diseases (9.3%) were the main underlying causes of deaths in which Chagas' disease was identified as an associated cause. CONCLUSIONS: Cardiovascular diseases were often associated with deaths related to Chagas' disease. Information from multiple causes of death recorded on death certificates allows reconstruction of the natural history of Chagas' disease and suggests preventive and therapeutic potential measures more adequate and specifics.

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Small-Area Variation in Multiple Causes of Death in Sweden—A Comparison with Underlying Causes of Death

International Journal of Epidemiology ◽

10.1093/ije/24.3.552 ◽

1995 ◽

Vol 24 (3) ◽

pp. 552-558 ◽

Cited By ~ 4

Author(s):

RAGNAR WESTERLING

Keyword(s):

Small Area ◽

Causes Of Death ◽

Multiple Causes Of Death ◽

Small Area Variation ◽

Underlying Causes ◽

Area Variation ◽

Multiple Causes

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Multimorbidity and multiple causes of death in heart failure

Journal of Public Health ◽

10.1007/s10389-020-01223-0 ◽

2020 ◽

Author(s):

Tilahun Nigatu Haregu ◽

Shane Nanayakkara ◽

Melinda Carrington ◽

David Kaye

Keyword(s):

Heart Failure ◽

Causes Of Death ◽

Multiple Causes Of Death ◽

Multiple Causes

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892Quantification of mortality incorporating multiple causes of death: Application of weighting strategies to Australian data

International Journal of Epidemiology ◽

10.1093/ije/dyab168.329 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Grace Joshy ◽

Karen Bishop ◽

Saliu Balogun ◽

Margarita Moreno-Betancur ◽

James Eynstone-Hinkins ◽

...

Keyword(s):

Causes Of Death ◽

Traditional Approach ◽

Heart Diseases ◽

International Classification Of Diseases ◽

Cerebrovascular Diseases ◽

World Health ◽

Weighting Method ◽

Multiple Causes Of Death ◽

Weighting Methods ◽

Multiple Causes

Abstract Background Mortality statistics are typically based on a single underlying cause of death (UCoD). Although UCoD provides a useful construct, the relevance of assuming that a single disease caused the death is diminishing, especially with increased life expectancy and high proportions of deaths in older ages from chronic/degenerative diseases. Focussing on common underlying causes of death in Australia, we quantified mortality incorporating weighting strategies for multiple causes of death (MCoD). Methods All deaths registered in Australia from 2015-2017 (478,396 deaths) and coded using International Classification of Diseases Version 10 were classified using an extended cause list (n = 136 causes) based on a World Health Organization short list. Age-standardised rates (ASR) were estimated using three weighting methods: (1) traditional approach using UCoD alone; (2) UCoD and associated causes of death (ACoDs) equally weighted and (3) UCoD weighted 0.5 arbitrarily and remaining 0.5 apportioned to the remaining ACoDs. Results Common UCoD were ischaemic heart diseases, cerebrovascular diseases, dementia; 57671, 31515 and 27377 deaths respectively. There were substantial changes in ASR depending on the weighting method used. Variation in mortality patterns estimated using the three weighting methods and challenges to further refinement of the weighting strategy will be discussed. Conclusions Mortality indicators incorporating MCoD enhance traditional measures of mortality and provide a means to reassess the role of diseases in causing death. Further disease specific methods are required to refine current weighting strategies. Key messages Weighting strategies for are useful for quantifying mortality incorporating MCoD, but methodological challenges exist.

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