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Coding Quality of Deaths and its Impact on Elderly Unintentional Fall Mortality Data from 1990 to 2019: A Retrospective Analysis of the WHO Mortality Database

38 Pages Posted: 18 Aug 2021

See all articles by Junjie Hua

Junjie Hua

Central South University; Central South University - Department of Epidemiology and Health Statistics

Peishan Ning

Central South University - Department of Epidemiology and Health Statistics

Peixia Cheng

Central South University - Department of Epidemiology and Health Statistics

Zhenzhen Rao

Central South University; Central South University - Department of Epidemiology and Health Statistics

Jieyi He

Central South University - Department of Epidemiology and Health Statistics

Wangxin Xiao

Central South University - Department of Epidemiology and Health Statistics

Li Li

Central South University - Department of Epidemiology and Health Statistics

Yanhong Fu

Central South University; Central South University - Department of Epidemiology and Health Statistics

Ruotong Li

Central South University - Department of Epidemiology and Health Statistics

Jie Li

Central South University - Department of Epidemiology and Health Statistics

Wanhui Wang

Central South University; Central South University - Department of Epidemiology and Health Statistics

David C. Schwebel

University of Alabama at Birmingham; University of Alabama at Birmingham - Department of Psychology

Guoqing Hu

Central South University - Department of Epidemiology and Health Statistics

More...

Abstract

Background: Several studies have assessed the reporting quality of all-cause mortality data from the WHO Mortality Database, but little is known about coding quality and its impact on elderly unintentional fall mortality data worldwide, We aimed to assess the coding quality of deaths and its impact on elderly unintentional fall mortality.

Methods: We extracted mortality data from the World Health Organization (WHO) Mortality Database, 1990-2019. We calculated number of countries/territories that had mortality data in the WHO Mortality Database, and proportion of deaths with five types of problematic codes based on the 10th international classification of disease (ICD-10) (unspecified deaths, injury deaths with undetermined intent, unspecified unintentional injury, unintentional falls with unspecified mechanism, unintentional falls with unknown occurrence place). We estimated age-adjusted unintentional fall mortality before and after correcting problematic codes.

Findings: Only 64% (124/194) WHO member states had at least one-year mortality data in the WHO Mortality Database during 1990-2019, and data unavailability was more common for under-developed countries/territories than for developed countries/territories. As for the proportion of five types of problematic codes, coding quality was poor for many countries/territories included in the WHO Mortality Database. Among the study years when countries/territories possessed mortality data, 80%, 53%, 51%, and 63% had a proportion of unintentional fall deaths with unspecified mechanism over 50% in low-income, lower middle-income, upper middle-income, and high-income countries/territories, respectively; comparable proportions for unintentional fall deaths with unknown occurrence place were 100%, 42%, 71%, and 62%. Among the 94 countries/territories having mortality data, problematic codes caused a relative mortality difference ≥50% in 59 countries/territories (63%). After correcting problematic codes, 5 of 55 countries/territories with data witnessed a reverse in mortality changes between 2005 and 2015. Among the 82 countries/territories with mortality data for 5 or more years, 18 countries/territories (22%) experienced a directional reverse in linear regression coefficient.

Interpretation: The availability and quality of global data related to elderly unintentional fall mortality in the WHO Mortality Database was poor between 1990 and 2019. Varying data quality across countries/territories and over time have a substantial impact on mortality estimates and mortality comparisons. Global agencies plus each individual government should be aware of the importance of collecting and sharing high-quality mortality data, and take actions to improve data quality for inclusion in the WHO Mortality Database.

Funding: Natural Science Foundation of Hunan Province, China, and Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital).

Declaration of Interest: We declare no competing interests.

Ethical Approval: The research protocol was approved by the Medical Ethics Committee of Central
South University on 25 January 2021 (No. XYGW-2021-06).

Keywords: unintentional fall, mortality, data availability, coding quality, WHO Mortality Database

Suggested Citation

Hua, Junjie and Hua, Junjie and Ning, Peishan and Cheng, Peixia and Rao, Zhenzhen and He, Jieyi and Xiao, Wangxin and Li, Li and Fu, Yanhong and Fu, Yanhong and Li, Ruotong and Li, Jie and Wang, Wanhui and Wang, Wanhui and Schwebel, David C. and Schwebel, David C. and Hu, Guoqing, Coding Quality of Deaths and its Impact on Elderly Unintentional Fall Mortality Data from 1990 to 2019: A Retrospective Analysis of the WHO Mortality Database. Available at SSRN: https://ssrn.com/abstract=3907205 or http://dx.doi.org/10.2139/ssrn.3907205

Junjie Hua

Central South University

Changsha, 410083
China

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Peishan Ning

Central South University - Department of Epidemiology and Health Statistics

Hunan Sheng, 410008
China

Peixia Cheng

Central South University - Department of Epidemiology and Health Statistics

Hunan Sheng, 410008
China

Zhenzhen Rao

Central South University

Changsha, 410083
China

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Jieyi He

Central South University - Department of Epidemiology and Health Statistics

Hunan Sheng, 410008
China

Wangxin Xiao

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Li Li

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Yanhong Fu

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Central South University

Changsha, 410083
China

Ruotong Li

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Jie Li

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

Wanhui Wang

Central South University

Changsha, 410083
China

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

David C. Schwebel

University of Alabama at Birmingham

Birmingham, AL 35294-4460
United States

University of Alabama at Birmingham - Department of Psychology ( email )

Birmingham, AL
United States

Guoqing Hu (Contact Author)

Central South University - Department of Epidemiology and Health Statistics ( email )

Hunan Sheng, 410008
China

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