Garbage codes as causes of death and quality of mortality statistics in Belo Horizonte, Brazil

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.

Investigation of hospital deaths declared as garbage codes in Belo Horizonte, Brazil, in 2017

Background

Improving the quality of causes of death (COD) is vital for defining adequate public policies. In Brazil, one third of deaths are reported as having a cause that is not useful for public health analysis of cause-of-death data, the so-called garbage codes (GC). The investigation of these deaths is one of the strategies that could improve the quality of mortality statistics in the country.

Methods

For all GCs identified in 2017 in the routine mortality information system from Belo Horizonte city, Brazil, municipal health professionals collected information about the final disease obtained from hospital records or autopsies in a standardized form. A trained physician analyzed this information and filled in a new death certificate (DC). The DC that originally showed a GC as an underlying COD was categorized into GC reclassified when the garbage cause changed to a specific cause after investigation. Causes of death derived from the reclassified GCs were analyzed to assess the impact on the mortality profile before and after the investigation.

Results

In Belo Horizonte, 1,395 deaths out of 3,038 registered as garbage codes were investigated, with a 35% reduction in deaths due to these causes. There was an increase in deaths from ischemic heart diseases, Alzheimer's disease, chronic obstructive pulmonary disease, hemorrhagic and ischemic stroke, and violence.

Conclusions

The investigation of deaths from garbage codes modified the mortality profile and improved its quality, providing direction for more assertive public health policies. Strategies for training physicians to report specific causes of death is another strategy that could improve the quality of mortality data.

Key messages

This study proved to be a feasible strategy in improving the quality of causes of death in mortality statistics and should be incorporated into the surveillance routine activities in Brazil. The evaluation of the GC investigation is an important instrument in helping management of health interventions aiming at better quality of information and more qualified health services.

Improving the usefulness of mortality data in Brazil: reclassification of ill-defined causes of death

Background

Garbage codes (GC) among registered causes of death can bias mortality analysis. In Brazil, more than one million deaths occurred annually in 2006-2017 and around 100,000 deaths per year were originally attributed to GC ill-defined causes of death (IDCD) in the Mortality Information System (SIM - Sistema de Informação sobre Mortalidade). To provide more accurate cause-of-death analysis, routine investigations of IDCD in the health surveillance system have been implemented in the country since 2005. The objective of this study was to analyze specific underlying causes for deaths originally assigned as IDCD in the SIM in 2006-2017.

Methods

For all IDCD (ICD codes from chapter 18, or R-codes) 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. Proportions of reclassified deaths by cause-specific mortality fractions (CSMF) derived from the reclassified IDCD by age and four calendar periods were analyzed to assess specific causes detected after investigation.

Results

A high proportion of deaths due to IDCD was investigated in 2006-2017 (32%). From a total of 257,367 IDCD reclassified, chronic diseases (56.6%), injuries (7.2%), and infectious (5.2%) or neonatal, maternal, malnutrition (1.7%) were the underlying causes detected among IDCD. Neonatal-related conditions, interpersonal violence, 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.

Conclusions

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.

Key messages

Investigation of IDCD as part of routine data collection on a large scale as had occurred in Brazil in 2006-2017 is an innovative approach to strengthen population-level mortality statistics. In addition to reducing the proportions of IDCD by their reclassification into specific causes, this initiative opens up the prospect of using these results for redistributing remaining cases of IDCD.

Higher perinatal mortality in National Public Health System hospitals in Belo Horizonte, Brazil, 1999: a compositional or contextual effect?

OBJECTIVE

In Brazil, it was previously reported that in hospital perinatal, neonatal and infant mortality rates are higher for hospitals contracted to the National Public Health System (SUS) compared with non-SUS hospitals. We analyse whether this reflects a compositional effect (selection of patients) or a contextual effect.

DESIGN

Population-based cohort study.

SETTING

Belo Horizonte, Brazil, 1999.

POPULATION

A total of 36,469 births in 24 hospitals.

METHODS

A multilevel analysis was carried out using information gathered at the individual level on maternal education (used as an indicator of socio-economic status), maternal age, type of pregnancy and delivery, birthweight and sex of the fetus.

MAIN OUTCOME MEASURE

Perinatal death.

RESULTS

Risk factors for perinatal death included male sex (OR = 1.25; 95% CI 1.01-1.55), birthweight of 1500-2500 g (OR = 7.65; 95% CI 5.74-10.20), birthweight of 500-1500 g (OR = 187.54; 95% CI 141.31-248.39), less than 4 years of maternal education (OR = 2.93; 95% CI 1.68-5.10), as well as birth at private-SUS (OR = 2.92; 95% CI 1.87-4.54) or philanthropic-SUS hospitals (OR = 1.81; 95% CI 1.12-2.92). After controlling for individual characteristics, there was still a significant variation in perinatal deaths between hospitals categories.

CONCLUSION

Independent of compositional (or individual) characteristics, hospital factors exert an influence on the risk of perinatal death, primarily hospital category related to SUS. Considering the highest proportion of births in SUS hospitals in Brazil, especially private-SUS hospitals, improving hospital quality of care is an urgent priority for reducing the toll of perinatal and infant mortality, as well as inequalities in these outcomes.

Microbiological and epidemiological characterization of imipenem-resistant Pseudomonas aeruginosa strains from a Brazilian tertiary hospital: report from the SENTRY Antimicrobial Surveillance Program

OBJECTIVES

To evaluate the antimicrobial susceptibility profile, the genetic similarity, and the mechanisms of carbapenem resistance among imipenem-resistant Pseudomonas aeruginosa isolates collected from a Brazilian tertiary teaching hospital.

METHODS

Seventy-eight consecutive samples of P. aeruginosa were evaluated during 2000 and 2001. The antimicrobial susceptibility was evaluated by reference broth microdilution methods and the imipenem-resistant isolates were screened for metallo-beta-lactamase (MbetaL) production throughout disc approximation test and MbetaL Etest strips and isolates with positive screen test result were submitted to PCR assays using primers blaIMP-1, bla VIM-1, blaVIM-2 e blaSPM-1. The genetic similarity of MbetaL-producing strains was evaluated by automated ribotyping for epidemiological typing purpose.

RESULTS

Resistance rates were high to the majority of antimicrobial agents tested except polymyxin B, which inhibited all samples at the Clinical and Laboratory Standards Institute breakpoint (< or = 2 microg/ml). Twenty-nine (37.2%) isolates were resistant to imipenem and these isolates showed great genomic variability. MbetaL production was demonstrated in two imipenem-resistant isolates, which were detected using blaSPM-1 and blaIMP-2-specific primers. Sequence analysis revealed the presence of blaSPM-1 and a novel blaIMP-type gene, blaIMP-16.

CONCLUSION

The results of this study showed high resistance rates to the majority of antimicrobial agents among P. aeruginosa samples. High imipenem resistance rates were probably due to continuous selection of resistant mutants. The production of MbetaL did not represent a frequent mechanism of carbapenem resistance in this medical center; but a novel MbetaL was identified. Continued antimicrobial surveillance and infection control measures should be emphasized to minimize the emergence and dissemination of antimicrobial resistance.

[Association between socioeconomic factors and infant deaths due to diarrhea, pneumonia, and malnutrition in a metropolitan area of Southeast Brazil: a case-control study]

A population-based case-control study was carried out to identify determinant factors for post-neonatal infant deaths due to diarrhea, pneumonia, and malnutrition in Greater Metropolitan Belo Horizonte, Southeast Brazil. From May 1, 1991, to April 30, 1992, 511 post-neonatal deaths due to diarrhea, pneumonia, and malnutrition were selected after investigation of medical records to validate cause of death. Of this total, 396 deaths were compared to a neighborhood control group, matched for age. The study was carried out in a low-income area with a high proportion of families living in shantytowns. The article discusses the methodology and selected socioeconomic factors. Logistic regression analysis indicated that number of household appliances, mother's and father's education, and mother's marital and work status were significantly associated with risk of infant death, i.e., they were determinants of infant deaths due to avoidable causes.

[Postneonatal infant mortality and quality of medical care: a case-control study]

OBJECTIVE: To identify the risk factors for postneonatal infant mortality caused by diarrhea and pneumonia in relation to the quality of medical assistance. METHODS: Population-based case-control study of 277 postneonatal infant deaths caused by diarrhea and pneumonia occurring in the metropolitan area of Belo Horizonte, Brazil, between May/1991 and April/1992. The cases were compared with hospitalized controls, and matched by pathology, age and hospital. Information on cases and controls were collected from medical records and through home interviews. Some variables related to the quality of medical care were analyzed. McNemar test and conditional logistic regression were used to define the risk factors for postneonatal deaths. RESULTS: Multiple logistic regression analysis showed the following factors independently associated with increased risk of postneonatal death induced by diarrhea and pneumonia: delayed immunization (OR = 2.48; 95%CI=1.17-5.23), general status (serious) on hospital admission (OR=10.94; 95%CI=4.91-24.34), unaccomplished hospital procedures (OR=10.08; 95%CI = 3.55-20.59) and malnutrition on hospital admission (OR=3.58; 95%CI=1.42-9.07). CONCLUSIONS: The results indicate the low quality of medical assistance as an important risk factor for avoidable causes of postneonatal deaths. The authors highlight the lack of integration between the outpatient clinic and hospital activities as an important determinant of low quality. It is necessary that the performance of health services and their effect on avoidable infant mortality be widely discussed, also taking into consideration the preponderant role of socioeconomic variables