Algorithms for enhancing public health utility of national causes-of-death data

Abstract

BackgroundCoverage and quality of cause-of-death (CoD) data varies across countries and time. Valid, reliable, and comparable assessments of trends in causes of death from even the best systems are limited by three problems: a) changes in the International Statistical Classification of Diseases and Related Health Problems (ICD) over time; b) the use of tabulation lists where substantial detail on causes of death is lost; and c) many deaths assigned to causes that cannot or should not be considered underlying causes of death, often called garbage codes (GCs). The Global Burden of Disease Study and the World Health Organization have developed various methods to enhance comparability of CoD data. In this study, we attempt to build on these approaches to enhance the utility of national cause-of-death data for public health analysis.MethodsBased on careful consideration of 4,434 country-years of CoD data from 145 countries from 1901 to 2008, encompassing 743 million deaths in ICD versions 1 to 10 as well as country-specific cause lists, we have developed a public health-oriented cause-of-death list. These 56 causes are organized hierarchically and encompass all deaths. Each cause has been mapped from ICD-6 to ICD-10 and, where possible, they have also been mapped to the International List of Causes of Death 1-5. We developed a typology of different classes of GCs. In each ICD revision, GCs have been identified. Target causes to which these GCs should be redistributed have been identified based on certification practice and/or pathophysiology. Proportionate redistribution, statistical models, and expert algorithms have been developed to redistribute GCs to target codes for each age-sex group.ResultsThe fraction of all deaths assigned to GCs varies tremendously across countries and revisions of the ICD. In general, across all country-years of data available, GCs have declined from more than 43% in ICD-7 to 24% in ICD-10. In some regions, such as Australasia, GCs in 2005 are as low as 11%, while in some developing countries, such as Thailand, they are greater than 50%. Across different age groups, the composition of GCs varies tremendously - three classes of GCs steadily increase with age, but ambiguous codes within a particular disease chapter are also common for injuries at younger ages. The impact of redistribution is to change the number of deaths assigned to particular causes for a given age-sex group. These changes alter ranks across countries for any given year by a number of different causes, change time trends, and alter the rank order of causes within a country.ConclusionsBy mapping CoD through different ICD versions and redistributing GCs, we believe the public health utility of CoD data can be substantially enhanced, leading to an increased demand for higher quality CoD data from health sector decision-makers.

Consistent declining trends in stroke mortality in Brazil: mission accomplished?

“…When studying mortality trends for the five regions of Brazil during 15 years, it is important to keep in mind that coverage and quality of cause-of-death data varies across regions and time. Valid, reliable, and comparable assessments of trends in causes of death from even the best systems are limited by coverage and quality of data issues 16 . The first step of a mortality analysis consists in using traditional demographic tools for correction of coverage.…”

“…Since the advent of the sixth revision, the ICD-10 has been used not only to code deaths but also to cover all types of medical information, including non-fatal disorders and nonspecific medical conditions 16 . In this study, causes such as atherosclerosis and hypertension, more plausible as risk factors than underlying cause of death, were redistributed to cerebrovascular and other cardiovascular diseases, according to preconized methods 1 .…”

“…Besides differences in coverage, many deaths assigned to causes that cannot or should not be considered underlying causes of death must be redistributed to a cause of death that makes sense in terms of causality or public health interpretation 16 . Since the advent of the sixth revision, the ICD-10 has been used not only to code deaths but also to cover all types of medical information, including non-fatal disorders and nonspecific medical conditions 16 .…”

Principais causas da mortalidade na infância no Brasil, em 1990 e 2015: estimativas do estudo de Carga Global de Doença

“…This methodology recommends that certain codes from the International Classification of Diseases (ICD) should not be considered as an underlying cause of death as they do not characterize this cause sufficiently to enable adequate public health interventions. These codes are named garbage codes, and considering that the burden of disease is estimated according to specific causes, these codes are redistributed 14 . Among more than 4,000 codes in the ICD-10 are considered to be garbage in the GBD 2015 study, the following were registered at a higher proportion in the SIM, in 2015, for children under 5 years of age: J18.0-J18.9-Unspecified pneumonia (n = 1,452), R00-R99-III-defined causes of death (n = 1,120), and A40.0-A41.9-Septicaemias (n = 779).…”

Qualidade da informação das estatísticas de mortalidade: códigos garbage declarados como causas de morte em Belo Horizonte, 2011-2013

“…However, studies have indicated a tendency in considering other ill-defined causes and incomplete diagnoses from other chapters of ICD-10, defined in conjunction with those in Chapter XVIII as garbage codes (GCs). Despite still undeserving attention by health services and professionals, the importance of this group of causes has been highlighted in order to advance the discussion on the quality of the information 5,6 . The definition of GC was introduced in the Global Burden of Disease Study 1990, published in 1996 7 .…”