Algorithms for enhancing public health utility of national causes-of-death dataReport as inadecuate




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Population Health Metrics

, 8:9

First Online: 10 May 2010Received: 09 March 2010Accepted: 10 May 2010DOI: 10.1186-1478-7954-8-9

Cite this article as: Naghavi, M., Makela, S., Foreman, K. et al. Popul Health Metrics 2010 8: 9. doi:10.1186-1478-7954-8-9

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.

List of AbbreviationsBTLBasic Tabulation List ICD-9

CoDCause of Death

GBDGlobal Burden of Disease Study

GCGarbage Code

ICDInternational Statistical Classification of Diseases and Related Health Problems

IHMEInstitute for Health Metrics and Evaluation

ILCDInternational List of Causes of Death

UCDUnderlying Cause of Death

WHOWorld Health Organization

ACMEAutomatic Classification of Medical Entry.

Electronic supplementary materialThe online version of this article doi:10.1186-1478-7954-8-9 contains supplementary material, which is available to authorized users.

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Author: Mohsen Naghavi - Susanna Makela - Kyle Foreman - Janaki O-Brien - Farshad Pourmalek - Rafael Lozano

Source: https://link.springer.com/







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