Investigation of hospital deaths declared as garbage codes in Belo Horizonte, Brazil, in 2017 (original) (raw)
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2020
Background: Registered causes in vital statistics classified as garbage codes (GC) are considered indicators of quality of cause-of-death data. Our aim was to describe temporal changes in this quality in Brazil, and the leading GCs according to levels assembled for the Global Burden of Disease (GBD) study. We also assessed socioeconomic differences in the burden of different levels of GCs at a regional level. Methods: We extracted data from the Brazilian Mortality Information System from 1996 to 2016. All three and four digit ICD-10 codes considered as GC were selected and classified into four categories, according to the GBD study proposal. GCs levels 1 and 2 are the most damaging unusable codes, or major GCs. Proportionate distribution of deaths by GC levels according selected variables were performed. Age-standardized mortality rates after correction of underreporting of deaths were calculated to investigate temporal relationships as was the linear association adjusted for comple...
2020
Background: Accurate cause of death (COD) data are essential for policy and planning. Garbage codes (GCs), such as external causes with no further specific information, are commonly used as an indicator of poor quality of COD information. The investigation of GC using an effective instrument is necessary to convert them into useful data for public health. Aim: This study was conducted to analyze the effectiveness of the new investigation of deaths from external causes (IDEC) form, proposed by Ministry of Health, Brazil, to improve the quality of COD. Methods: The study compared the performance of the IDEC form on 164 external GC deaths with a stratified matched sample of 2,283 external GC deaths that used the existing standard GC form. The percentage of GCs that were reclassified into valid causes was calculated. Analyses according to subgroup (age, type of external cause) and exploration of the reclassifications of deaths between different cause groups were conducted. Qualitative d...
Revista Brasileira De Epidemiologia, 2019
Introduction: Deaths certified with ill-defined causes or garbage codes (GC) compromise the analysis of mortality and its use for planning and evaluation of public health policies. The hospital investigation of these causes is one of the strategies qualifying the profile of mortality in the country. Objective: To evaluate the change in the hospital mortality profile after investigation of deaths certified with GC in 2017 in Belo Horizonte, Brazil. Methods: A sample of hospital deaths reported with GC in the Mortality Information System (SIM) of Belo Horizonte in 2017 was investigated and subsequently certified by a physician to compare the mortality profile before and after investigation. Results: After investigating 1,395 deaths out of 3,038 reported with GC, a reduction of 35.5% of these causes was observed. Groups of all ages presented decreases in GC occurrence. A higher proportional increase was observed for deaths due to ischemic heart diseases, Alzheimer's disease, chronic obstructive pulmonary disease, ischemic and hemorrhagic stroke, and external causes of death (accidental falls, homicides and traffic/transport accidents). Conclusion: The investigation on reported hospital deaths is one of the strategies to improve mortality statistics, reducing the occurrence of GC among reported deaths and changing the mortality profile in these facilities. The importance of continuous physician training in cause-of-death certification is emphasized.
Reliability of cause of death coding: an international comparison
Cadernos de Saúde Pública, 2015
This study evaluates the agreement of nosologic coding of cardiovascular causes of death between a Chilean coder and one in the United States, in a stratified random sample of death certificates of persons aged ≥ 60, issued in 2008 in the Valparaíso and Metropolitan regions, Chile. All causes of death were converted to ICD-10 codes in parallel by both coders. Concordance was analyzed with inter-coder agreement and Cohen’s kappa coefficient by level of specification ICD-10 code for the underlying cause and the total causes of death coding. Inter-coder agreement was 76.4% for all causes of death and 80.6% for the underlying cause (agreement at the four-digit level), with differences by the level of specification of the ICD-10 code, by line of the death certificate, and by number of causes of death per certificate. Cohen's kappa coefficient was 0.76 (95%CI: 0.68-0.84) for the underlying cause and 0.75 (95%CI: 0.74-0.77) for the total causes of death. In conclusion, causes of death ...
Revista Brasileira de Epidemiologia, 2014
Objective: The proportion of ill-defined causes of death (IDCD) was persistently high in some regions of Brazil in 2004. In 2005, the Brazilian government implemented a project in order to decrease this proportion, especially in higher priority states and municipalities. This study aimed to evaluate the performance of this project in Alagoas -a state from the Northeast region of Brazil. Method: We selected a probabilistic sample of 18 municipalities. For all IDCD identified in 2010, we collected the verbal autopsy (VA) questionnaires used for home investigation, and the Ministry of Health (MoH) form, which contains information about the final disease and cause of death taken from hospital records, autopsies, family health teams, and civil registry office records. The completion rate of the MoH form and VA was calculated using the number of deaths with specific causes assigned among investigated deaths. Results: A total of 681 IDCD were recorded in 2010 in the sample, of which 26% had a MoH and/or VA3 forms completed. Although the majority of cases were attended by health professionals during the terminal disease, the completion rate was 45% using the MoH form and 80% when VA was performed. Conclusions: Our findings provide evidence that the training of the epidemiological surveillance teams in the investigation and certification of causes of death could contribute to improve the quality of mortality data.
Garbage codes in the Norwegian Cause of Death Registry 1996–2019
BMC Public Health, 2022
Background: Reliable statistics on the underlying cause of death are essential for monitoring the health in a population. When there is insufficient information to identify the true underlying cause of death, the death will be classified using less informative codes, garbage codes. If many deaths are assigned a garbage code, the information value of the cause-of-death statistics is reduced. The aim of this study was to analyse the use of garbage codes in the Norwegian Cause of Death Registry (NCoDR). Methods: Data from NCoDR on all deaths among Norwegian residents in the years 1996-2019 were used to describe the occurrence of garbage codes. We used logistic regression analyses to identify determinants for the use of garbage codes. Possible explanatory factors were year of death, sex, age of death, place of death and whether an autopsy was performed. Results: A total of 29.0% (290,469/1,000,128) of the deaths were coded with a garbage code; 14.1% (140,804/1,000,128) with a major and 15.0% (149,665/1,000,128) with a minor garbage code. The five most common major garbage codes overall were ICD-10 codes I50 (heart failure), R96 (sudden death), R54 (senility), X59 (exposure to unspecified factor), and A41 (other sepsis). The most prevalent minor garbage codes were I64 (unspecified stroke), J18 (unspecified pneumonia), C80 (malignant neoplasm with unknown primary site), E14 (unspecified diabetes mellitus), and I69 (sequelae of cerebrovascular disease). The most important determinants for the use of garbage codes were the age of the deceased (OR 17.4 for age ≥ 90 vs age < 1) and death outside hospital (OR 2.08 for unknown place of death vs hospital). Conclusion: Over a 24-year period, garbage codes were used in 29.0% of all deaths. The most important determinants of a death to be assigned a garbage code were advanced age and place of death outside hospital. Knowledge of the national epidemiological situation, as well as the rules and guidelines for mortality coding, is essential for understanding the prevalence and distribution of garbage codes, in order to rely on vital statistics.
Public health utility of cause of death data: applying empirical algorithms to improve data quality
BMC Medical Informatics and Decision Making, 2021
Background: Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments. Methods: We describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings. Results: The proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD.
Revista de Saúde Pública, 2014
OBJECTIVE To propose a method of redistributing ill-defined causes of death (IDCD) based on the investigation of such causes.METHODS In 2010, an evaluation of the results of investigating the causes of death classified as IDCD in accordance with chapter 18 of the International Classification of Diseases (ICD-10) by the Mortality Information System was performed. The redistribution coefficients were calculated according to the proportional distribution of ill-defined causes reclassified after investigation in any chapter of the ICD-10, except for chapter 18, and used to redistribute the ill-defined causes not investigated and remaining by sex and age. The IDCD redistribution coefficient was compared with two usual methods of redistribution: a) Total redistribution coefficient, based on the proportional distribution of all the defined causes originally notified and b) Non-external redistribution coefficient, similar to the previous, but excluding external causes.RESULTS Of the 97,314 ...
Population Health Metrics, 2014
Background: The World Health Organization has developed proposals on how efforts to reduce non-communicable diseases (NCD) in low-and middle-income countries may be monitored over time. One of the proposed indicators is the unconditional probability of death between the ages of 30 and 70 from any of the four main groups of non-communicable diseases -cardiovascular disease, cancer, chronic respiratory disease, and diabetes. Our objective is to describe information-processing methods developed to facilitate this monitoring of mortality over time for Brazil. Methods: We developed an IPython Notebook which incorporates mortality records, population sizes, estimates of sub notification, redistribution of ill-defined causes of death, international disease codes, and world standard population weights for five-year age group, gender, state, and year strata. The approach permits flexibility in the incorporation of different estimates of sub-notification and ill-defined causes of death. The main output is a "Basic Sheet", where each line provides corrected deaths by disease categories and denominators for a given stratum. This sheet is then used to generate desired statistics. Results: This collection of shareable computer code and data organizes the approach necessary for calculations, making the data available to interested parties for the remaining relatively simple calculations. The mortality statistic suggested by the World Health Organization is derived from this sheet.