Risk factors for the ill-defined causes of death in the Brazilian states: a multilevel analysis

Factors associated with the quality of death certification in Brazilian municipalities: A data-driven non-linear model

Studies evaluating the local quality of death certification in Brazil focused on completeness of death reporting or inappropriate coding of causes of death, with few investigating missing data. We aimed to use missing and unexpected values in core topics to assess the quality of death certification in Brazilian municipalities, to evaluate its correlation with the percentage of garbage codes, and to employ a data-driven approach with non-linear models to investigate the association of the socioeconomic and health infrastructure context with quality of death statistics among municipalities. This retrospective study used data from the Mortality Information System (2010-2017), and municipal data regarding healthcare infrastructure, socioeconomic characteristics, and death rates. Quality of death certification was assessed by missing or unexpected values in the following core topics: dates of occurrence, registration, and birth, place of occurrence, certifier, sex, and marital status. Models were fit to classify municipalities according to the quality of death certification (poor quality defined as death records with missing or unexpected values in core topics ≥ 80%). Municipalities with poor quality of death certification (43.9%) presented larger populations, lower death rates, lower socioeconomic index, healthcare infrastructure with fewer beds and physicians, and higher proportion of public healthcare facilities. The correlation coefficients between quality of death certification assessed by missing or unexpected values and the proportion of garbage codes were weak (0.11-0.49), but stronger for municipalities with lower socioeconomic scores. The model that best fitted the data was the random forest classifier (ROC AUC = 0.76; precision-recall AUC = 0.78). This innovative way of assessing the quality of death certification could help quality improvement initiatives to include the correctness of essential fields, in addition to garbage coding or completeness of records, especially in municipalities with lower socioeconomic status where garbage coding and the correctness of core topics appear to be related issues.

Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses

Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.

Evolução da estrutura e resultados da Atenção Primária à Saúde no Brasil entre 2008 e 2019

Resumo Descreve a evolução da estrutura e resultados da Atenção Primária à Saúde (APS) no Brasil, entre 2008 e 2019. Foram calculadas a mediana de variáveis como: despesa per capita em APS por habitante coberto, cobertura da APS e as taxas de mortalidade e internações por condições sensíveis à atenção primária (CSAP) de 5.565 municípios brasileiros estratificados segundo porte populacional e quintil do Índice Brasileiro de Privação (IBP) e analisada a tendência mediana no período. Houve aumento de 12% na mediana da despesa em APS. A cobertura da APS expandiu, sendo que 3.168 municípios apresentaram 100% de cobertura em 2019, contra 2.632 em 2008. A mediana das taxas de mortalidade e internações por CSAP aumentou 0,2% e diminuiu 44,9% respectivamente. A despesa em APS foi menor nos municípios com maior privação socioeconômica. Quanto maior o porte populacional e melhores as condições socioeconômicas dos municípios, menor a cobertura da APS. Quanto maior a privação socioeconômica dos municípios, maiores foram as medianas das taxas de mortalidade por CSAP. Este estudo demonstrou que a evolução da APS foi heterogênea e está associada tanto ao porte populacional como às condições socioeconômicas dos municípios.

Evolution of the structure and results of Primary Health Care in Brazil between 2008 and 2019

Abstract This paper describes the structure and results of Primary Health Care (PHC) in Brazil between 2008 and 2019. The medians of the following variables were calculated: PHC spending per inhabitant covered, PHC coverage, and rates of mortality and hospitalizations due to primary care sensitive conditions (PCSC), in 5,565 Brazilian municipalities stratified according to population size and quintile of the Brazilian Deprivation Index (IBP), and the median trend in the period was analyzed. There was a 12% increase in median PHC spending. PHC coverage expanded, with 3,168 municipalities presenting 100% coverage in 2019, compared to 2,632 in 2008. The median rates of PCSC mortality and hospitalizations increased 0.2% and decreased 44.9%, respectively. PHC spending was lower in municipalities with greater socioeconomic deprivation. The bigger the population and the better the socioeconomic conditions were in the municipalities, the lower the PHC coverage. The greater the socioeconomic deprivation was in the municipalities, the higher the median PCSC mortality rates. This study showed that the evolution of PHC was heterogeneous and is associated both with the population size and with the socioeconomic conditions of the municipalities.

Análise da qualidade da informação sobre óbitos por neoplasias no Brasil, entre 2009 e 2019

RESUMO Objetivo: Avaliar a qualidade das informações sobre mortalidade por neoplasias no âmbito do Sistema de Informação sobre Mortalidade. Métodos: Estudo descritivo observacional com avaliação da qualidade do Sistema de Informação sobre Mortalidade, com desfecho referente aos dados de óbitos por neoplasias ocorridos entre os anos de 2009 e 2019 na população brasileira (≥15 anos). A qualidade da informação (QI) foi mensurada para o Brasil e para as Unidades Federativas por meio das dimensões: cobertura, especificidade e completude dos dados. Resultados: A qualidade da dimensão cobertura variou entre “boa” e “excelente” nas abrangências nacional e estadual. A dimensão especificidade foi classificada como inadequada predominantemente nos Estados das Regiões Norte e Nordeste. A proporção de causas mal definidas foi classificada como de “baixa” qualidade na maioria das unidades de análise ao longo da série. A completude dos dados variou de acordo com o indicador utilizado, os indicadores sexo e idade mostraram-se “excelentes” para todo o período e unidades de análise, a escolaridade apresentou variação de qualidade tanto nas unidades como nos períodos e o estado civil apresentou melhoria da qualidade de seu registro ao longo do período, assim como o indicador raça/cor. Conclusões: A qualidade dos dados de mortalidade por neoplasias na população brasileira (≥15 anos) é, em sua maioria, adequada, mas há lacunas importantes que merecem ser preenchidas, pois a ampliação da QI busca dar visibilidade à condição de saúde da população brasileira, bem como propor ações públicas para sua melhoria.

Analysis of quality of information about deaths from neoplasms in Brazil between 2009 and 2019

ABSTRACT Objective To assess the quality of information about mortality from neoplasm within the Mortality Information System. Methods: Descriptive observational study evaluating the quality of the Mortality Information System, with an outcome referring to data on deaths from neoplasm between 2009 and 2019 in the Brazilian population (≥15 years). Information Quality (IQ) was measured through coverage, specificity and completeness of data, at national and state level. Results: The quality of the coverage dimension ranged from “good” to “excellent” in the national and state coverages. Specificity was classified as inadequate mainly in the states of the North and Northeast regions. The proportion of ill-defined causes was classified as “poor” quality in most units of analysis throughout the series. Data completeness varied according to indicator. Gender and age indicators were proven “excellent” for the entire period and units of analysis, while educational level varied in quality across units and periods, marital status had its quality improved over the period, as well as ethnicity/skin color. Conclusions: The quality of data on mortality from neoplasm in the Brazilian population (≥15 years) is mostly adequate, but there are important gaps to be filled, as the expansion of IQ seeks to give visibility to the health condition of the Brazilian population and to propose public actions for its improvement.

Changes in the quality of cause-of-death statistics in Brazil: garbage codes among registered deaths in 1996-2016

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 GC were selected and classified into four categories, according to the GBD study proposal. GC 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 completeness between GC rates in states and the Sociodemographic Index (SDI) from the GBD study, for 1996-2005 and 2006-2016. We classified Brazilian states into three classes of development by applying tertiles cutoffs in the SDI state-level estimates.

RESULTS

Age-standardized mortality rates due to GCs in Brazil decreased from 1996 to 2016, particularly level 1 GCs. The most important GC groups were ill-defined causes (level 1) in 1996, and pneumonia unspecified (level 4) in 2016. At state level, there was a significant inverse association between SDI and the rate of level 1-2 GCs in 1996-2005, but both SDI and completeness had a non-expected significant direct association with levels 3-4. In 2006-2016, states with higher SDIs tended to have lower rates of all types of GCs. Mortality rates due to major GCs decreased in all three SDI classes in 1996-2016, but GC levels 3-4 decreased only in the high SDI category. States classified in the low or medium SDI groups were responsible for the most important decline of major GCs.

CONCLUSION

Occurrence of major GCs are associated with socioeconomic determinants over time in Brazil. Their reduction with decreasing disparity in rates between socioeconomic groups indicates progress in reducing inequalities and strengthening cause-of-death statistics in the country.

Change in the profile of causes of death after investigation of hospital deaths in Belo Horizonte, Brazil, 2017

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.

Improving the usefulness of mortality data: reclassification of ill-defined causes based on medical records and home interviews in Brazil

ABSTRACT Introduction: Brazil presented a high proportion of ill-defined causes of death (IDCD) in 2000, compromising accurate cause-of-death analysis. Objective: To analyze specific underlying causes for deaths originally assigned as IDCD in the Mortality Information System (SIM - Sistema de Informação sobre Mortalidade), after investigation activities implemented in country between 2006 and 2017. Method: For all IDCD identified in the SIM, municipal health professionals collected information about the final disease obtained from hospital records, autopsies, forms of family health teams, and home investigation. Specific causes among reclassified IDCD after investigation were evaluated according to age groups and four calendar periods. Results: Proportions of IDCD reassigned to other causes after review increased over time, reaching 30.1% in 2017. From a total of 257,367 IDCD reclassified in 2006-2017, neonatal-related conditions, injury, ischemic heart disease and stroke were the leading causes detected in the age groups 0-9 years, 10-29 years, 30-69 years, 70 years and over, respectively. Discussion: The similarity and plausibility of cause-specific proportions derived from the reclassification of IDCD by age group over time indicate the accuracy of the investigation data. Conclusion: High proportions of IDCD reassigned to more informative causes after review indicate the success of this approach to correct misclassification in the SIM, an initiative that should be maintained. Training physicians on death certification along with better quality of medical care and access to health services would lead to further improvement.