Public health utility of cause of death data: applying empirical algorithms to improve data quality

Autor: Nicole Davis Weaver, Anna Skryabina, Jalal Arabloo, Segun Emmanuel Ibitoye, Mahaveer Golechha, Yasir Waheed, Gebiyaw Wudie Tsegaye, Akshaya Srikanth Bhagavathula, Reza Mohammadpourhodki, Simon Hay, Ilse Dippenaar, Rafael Lozano, Mostafa Dianatinasab, Valentin Skryabin, Bach Tran, Andrew Olagunju, Lorenzo Monasta, Azeem Majeed, Hamidreza Komaki, Mohamad-Hani Temsah, Abdallah Samy, Eduarda Fernandes, Shafiu Mohammed, Carlos Castañeda-Orjuela
Rok vydání: 2021
Předmět:
Male
Index (economics)
ACCURACY
Garbage codes
Negative association
030204 cardiovascular system & hematology
Global Health
Health informatics
Global Burden of Disease
0302 clinical medicine
Japan
030212 general & internal medicine
Cause of death
Health Policy
Redistribution (cultural anthropology)
Vital registration
STATISTICS
Data Accuracy
Computer Science Applications
Geography
GBD Cause of Death Collaborators
MORTALITY DATA
HEART-FAILURE
Female
France
Life Sciences & Biomedicine
Algorithms
Brazil
Research Article
medicine.medical_specialty
Computer applications to medicine. Medical informatics
COMPLETION
R858-859.7
Health Informatics
Star ranking system
03 medical and health sciences
medicine
Humans
UNDERLYING CAUSE
CERTIFICATION
Science & Technology
US
business.industry
Public health
1103 Clinical Sciences
0806 Information Systems
Data quality
Redistribution
business
Medical Informatics
Demography
Zdroj: BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-20 (2021)
ISSN: 1472-6947
Popis: 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. Conclusions We provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.
Databáze: OpenAIRE
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