Abstract
Background
Quality of cause-of-death information is fundamental for health planning. Traditionally, this quality has been assessed by the analysis of ill-defined causes from chapter XVIII of the International Classification of Diseases - 10th revision (ICD-10). However, studies have considered other useless diagnoses for public health purposes, defined, in conjunction with ill-defined causes, as garbage codes (GC). In Brazil, despite the high completeness of the Mortality Information System, approximately 30% of deaths are attributable to GCs. This study aims to analyze the frequency of GCs in Belo Horizonte municipality, the capital of Minas Gerais state, Brazil.
Methods
Data of deaths from 2011 to 2013 in Belo Horizonte were analyzed. GCs were classified according to the GBD 2015 study list. These codes were classified in: a) GCs from chapter XVIII of ICD-10 (GC-R), and b) GC from other chapters of ICD-10 (GC-nonR). Proportions of GC were calculated by sex, age, and place of occurrence.
Results
In Belo Horizonte, from the total of 44,123 deaths, 5.5% were classified as GC-R. The majority of GCs were GC-nonR (25% of total deaths). We observed a higher proportion of GC in children (1 to 4 years) and in people aged over 60 years. GC proportion was also higher in females, except in the age-groups under 1 year and 30-59 years. Home deaths (n = 7,760) had higher proportions of GCs compared with hospital deaths (n = 30,182), 36.9% and 28.7%, respectively. The leading GCs were the GC-R other ill-defined and unspecified causes of death (ICD-10 code R99)), and the GCs-nonR unspecified pneumonia (J18.9), unspecified stroke (I64), and unspecified septicemia (A41.9).
Conclusions
Analysis of GCs is essential to evaluate the quality of mortality information.
Key messages
Analysis of ill-defined causes (GC-R) is not sufficient to evaluate the quality of information on causes of death. Causes of death analysis should consider the total GC, in order to advance the discussion and promote adequate intervention on the quality of mortality statistics.
Normal Deviate Analysis of Mortality Statistics
