Improving the quality of cause of death data for public health policy: are all 'garbage' codes equally problematic?

All countries need accurate and timely mortality statistics to inform health and social policy debates and to monitor progress towards national and global health development goals. In many countries, however, civil registration and vital statistics (CRVS) systems are poorly developed. Consequently, the statistics they produce are not fit for purpose. In part, this arises because the physicians certifying cause of death (COD) have either not been adequately trained in how to complete a death certificate according to the current International Statistical Classification of Diseases – Version 10 (ICD-10) [1], or they fail to appreciate the public health importance of what is often perceived as a largely administrative task [2]. This can be reinforced by cultural attitudes and perceptions among hospital administrators, who are generally unaware of the critical contribution that accurate medical certification of CODs makes to generating essential public health intelligence that can be used for planning. Unsurprisingly, these system deficiencies usually result in a high proportion of CODs being assigned to ‘garbage’ codes [3]. These have little or no public health value because they are too vague, are an immediate or intermediate COD, or are impossible as an underlying cause of death (UCOD). For example, septicaemia is often chosen as the underlying or precipitating COD when it is, in fact, the immediate cause arising from a many possible UCODs including communicable or non-communicable diseases, or an injury [3]. Prevention strategies would differ markedly depending on the UCOD; hence the importance of correct certification. Garbage codes bias a country’s true pattern of mortality. Studies of the quality of mortality statistics carried out in Thailand [4], Sri Lanka [5], and Iran [6], for example, have repeatedly found that the population’s likely true mortality pattern was considerably different from the pattern reported by the CRVS system. These discrepancies have been largely attributed to physicians’ extensive use of garbage codes

Education inequalities in adult all-cause mortality: first national data for Australia using linked census and mortality data

BACKGROUND: National linked mortality and census data have not previously been available for Australia. We estimated education-based mortality inequalities from linked census and mortality data that are suitable for international comparisons. METHODS: We used the Australian Bureau of Statistics Death Registrations to Census file, with data on deaths (2011-2012) linked probabilistically to census data (linkage rate 81%). To assess validity, we compared mortality rates by age group (25-44, 45-64, 65-84 years), sex and area-inequality measures to those based on complete death registration data. We used negative binomial regression to quantify inequalities in all-cause mortality in relation to five levels of education ['Bachelor degree or higher' (highest) to 'no Year 12 and no post-secondary qualification' (lowest)], separately by sex and age group, adjusting for single year of age and correcting for linkage bias and missing education data. RESULTS: Mortality rates and area-based inequality estimates were comparable to published national estimates. Men aged 25-84 years with the lowest education had age-adjusted mortality rates 2.20 [95% confidence interval (CI): 2.08‒2.33] times those of men with the highest education. Among women, the rate ratio was 1.64 (1.55‒1.74). Rate ratios were 3.87 (3.38‒4.44) in men and 2.57 (2.15‒3.07) in women aged 25-44 years, decreasing to 1.68 (1.60‒1.76) in men and 1.44 (1.36‒1.53) in women aged 65-84 years. Absolute education inequalities increased with age. One in three to four deaths (31%) was associated with less than Bachelor level education. CONCLUSIONS: These linked national data enabled valid estimates of education inequality in mortality suitable for international comparisons. The magnitude of relative inequality is substantial and similar to that reported for other high-income countries.Rosemary J Korda, Nicholas Biddle, John Lynch, James Eynstone-Hinkins, Kay Soga, Emily Banks ... et al