Abstract
BackgroundReliable and comparable data on causes of death are crucial for public health analysis, but the usefulness of these data can be markedly diminished when the approach to coding is not standardized across territories and/or over time. Because the Russian system of producing information on causes of death is highly decentralized, there may be discrepancies in the coding practices employed across the country. In this study, we evaluate the uniformity of cause-of-death coding practices across Russian regions using an indirect method.MethodsBased on 2002–2012 mortality data, we estimate the prevalence of the major causes of death (70 causes) in the mortality structures of 52 Russian regions. For each region-cause combination we measured the degree to which the share of a certain cause in the mortality structure of a certain region deviates from the respective inter-regional average share. We use heat map visualization and a regression model to determine whether there is regularity in the causes and the regions that is more likely to deviate from the average level across all regions. In addition to analyzing the comparability of cause-specific mortality structures in a spatial dimension, we examine the regional cause-of-death time series to identify the causes with temporal trends that vary greatly across regions.ResultsA high level of consistency was found both across regions and over time for transport accidents, most of the neoplasms, congenital malformations, and perinatal conditions. However, a high degree of inconsistency was found for mental and behavioral disorders, diseases of the nervous system, endocrine disorders, ill-defined causes of death, and certain cardiovascular diseases. This finding suggests that the coding practices for these causes of death are not uniform across regions. The level of consistency improves when causes of death can be grouped into broader diagnostic categories.ConclusionThis systematic analysis allows us to present a broader picture of the quality of cause-of-death coding at the regional level. For some causes of death, there is a high degree of variance across regions in the likelihood that these causes will be chosen as the underlying causes. In addition, for some causes of death the mortality statistics reflect the coding practices, rather than the real epidemiological situation.
Highlights
Reliable and comparable data on causes of death are crucial for public health analysis, but the usefulness of these data can be markedly diminished when the approach to coding is not standardized across territories and/or over time
The findings indicated that the International Classification of Diseases (ICD) chapter assignments in the cause-specific mortality statistics were quite reliable, but that the incidence of misattribution was higher when the recorded cause and the actual cause were in the same chapter [33]
The introduction of the ICD-10 and the RC-1999 classification systems in 1999 resulted in inconsistencies between the mortality series coded under the RC-1999 and the series coded under the previous SC-1988 classification
Summary
Reliable and comparable data on causes of death are crucial for public health analysis, but the usefulness of these data can be markedly diminished when the approach to coding is not standardized across territories and/or over time. Data on mortality by causes of death are important for monitoring epidemiological patterns These data, which are widely used in demographic and medical research, often provide crucial information for identifying public health problems and developing health care strategies. Even if the prevalence of such obvious problems is shown to be moderate, the quality of cause-of-death reporting can be considered imperfect; even if these problems are not immediately apparent, it is possible that certain causes of death are being systematically misclassified [5,6,7,8,9,10,11], and that the cause-specific mortality data being generated are of limited utility for the purposes of public health decision-making and research. The consistency of cause-specific mortality data at the subnational level determines the usability and the interpretability of national and subnational cause-of-death statistics [19, 20]
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