Evidence map›Paper›PMID 35073870›Full record

ArticleBMC geriatrics2022

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.

Junjie Hua, Peishan Ning, Peixia Cheng, Zhenzhen Rao, Jieyi He, Wangxin Xiao, Li Li, Yanhong Fu, Ruotong Li, Jie Li and 3 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Junjie HuaDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Peishan NingDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Peixia ChengDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Zhenzhen RaoDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Jieyi HeDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Wangxin XiaoDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Li LiDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Yanhong FuDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Ruotong LiDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Jie LiDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
Wanhui WangDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China.
David C SchwebelDepartment of Psychology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
Guoqing HuDepartment of Epidemiology and Health Statistics; Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410078, China. huguoqing009@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral 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.

methodsUsing data from the WHO Mortality Database, 1990-2019, we calculated the number of countries/territories that had mortality data in the database, and the proportion of deaths with five types of problematic codes based on the 10th International Classification of Disease (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.

resultsOnly 64% (124/194) of WHO member states had at least 1 year of mortality data in the database during 1990-2019, and data unavailability was more common for underdeveloped countries/territories than for developed countries/territories. Coding quality was poor for many countries/territories. 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.

conclusionsThe availability and coding quality of global data related to elderly unintentional fall mortality was poor between 1990 and 2019. When data are available, varying coding 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 action to improve data quality for inclusion in the WHO Mortality Database.

Indexed as

International Classification of DiseasesAgedCause of DeathDatabases, FactualHumansRetrospective StudiesWorld Health OrganizationCoding qualityData availabilityMortalityUnintentional fallWHO Mortality Database

Identifiers

PMID35073870
PMCPMC8785483

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