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Using multiple cause of death information to eliminate garbage codes

Author

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  • Agnieszka Fihel

    (Uniwersytet Warszawski)

  • Magdalena Muszyńska-Spielauer

    (Johannes Kepler Universität Linz)

Abstract

Background: International comparisons of mortality largely depend on the quality of data. With more than 20% of deaths annually assigned to ill-defined cardiovascular conditions, the mortality level due to well-defined causes of death is under-registered in Poland. Objective: We aim to reclassify cardiovascular garbage codes (GCs) into well-defined causes based on multiple causes of death (MCoD) data and to approximate mortality levels due to well-defined causes of death in Poland. We examine the usefulness of the MCoD approach for correcting low-quality data on causes of death. Methods: Based on the unique MCoD dataset for Poland, death counts due to cardiovascular GCs were reassigned to well-defined underlying causes in two steps: (1) manually for death records that included MCoD information constituting a logical chain of conditions leading to death and (2) with coarsened exact matching for the remaining death records. Age-specific and age-standardised death rates for large groups of causes were calculated before and after redistribution and compared to those of other Eastern European countries with relatively good data quality. Results: Of deaths originally assigned to cardiovascular GCs, 86,856 were reclassified, mostly to well-defined cardiovascular diseases, cancers, endocrine, nutritional and metabolic diseases, and respiratory diseases. The age-standardised death rate due to well-defined ischaemic heart diseases increased by 43%, and the rate due to cerebrovascular diseases by 22%. Cardiovascular mortality structure by large groups of causes became similar to the structure registered in other Eastern European countries characterised by a low prevalence of GCs. Conclusions: Coarsened exact matching performs relatively well when abundant MCoD information is available and enhances the comparability of cause-of-death data between countries. Contribution: Redistribution of GCs improves the quality of cause-of-death data and enhances their comparability between countries.

Suggested Citation

  • Agnieszka Fihel & Magdalena Muszyńska-Spielauer, 2021. "Using multiple cause of death information to eliminate garbage codes," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(11), pages 345-360.
    • Handle: RePEc:dem:demres:v:45:y:2021:i:11
    DOI: 10.4054/DemRes.2021.45.11
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    References listed on IDEAS

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    1. France Meslé, 2004. "Mortality in Central and Eastern Europe," Demographic Research Special Collections, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 2(3), pages 45-70.
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    Cited by:

    1. Fihel, Agnieszka & Janick, Anna & Buschner, Andrea & Ustinavičienė, Rūta & Trakienė, Aurelija, 2024. "The Importance of Cause-of-Death Certification for the COVID-19 Burden Assessment: the Case of Central Europe," SocArXiv hy9zn, Center for Open Science.
    2. Anna Sagan & Marina Karanikolos & Małgorzata Gałązka-Sobotka & Martin McKee & Monika Rozkrut & Iwona Kowalska-Bobko, 2022. "The Devil Is in the Data: Can Regional Variation in Amenable Mortality Help to Understand Changes in Health System Performance in Poland?," IJERPH, MDPI, vol. 19(7), pages 1-11, March.

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    More about this item

    Keywords

    cardiovascular diseases; cause of death; multiple causes of death; mortality; Poland; International Statistical Classification of Diseases and Related Health Problems; garbage codes;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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