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A method for reclassifying cause of death in cases categorized as “event of undetermined intent”

Overview of attention for article published in Population Health Metrics, September 2015
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Title
A method for reclassifying cause of death in cases categorized as “event of undetermined intent”
Published in
Population Health Metrics, September 2015
DOI 10.1186/s12963-015-0048-y
Pubmed ID
Authors

Evgeny Andreev, Vladimir M. Shkolnikov, William Alex Pridemore, Svetlana Yu. Nikitina

Abstract

We present a method for reclassifying external causes of death categorized as "event of undetermined intent" (EUIs) into non-transport accidents, suicides, or homicides. In nations like Russia and the UK the absolute number of EUIs is large, the EUI death rate is high, or EUIs comprise a non-trivial proportion of all deaths due to external causes. Overuse of this category may result in (1) substantially underestimating the mortality rate of deaths due to specific external causes and (2) threats to the validity of studies of the patterns and causes of external deaths and of evaluations of the impact of interventions meant to reduce them. We employ available characteristics about the deceased and the event to estimate the most likely cause of death using multinomial logistic regression. We use the set of known non-transport accidents, suicides, and homicides to calculate an mlogit-based linear score and an estimated classification probability (ECP). This ECP is applied to EUIs, with varying levels of minimal classification probability. We also present an optional second step that employs a population-level adjustment to reclassify deaths that remain undetermined (the proportion of which varies based on the minimal classification probability). We illustrate our method by applying it to Russia. Between 2000 and 2011, 521,000 Russian deaths (15 % percent of all deaths from external causes) were categorized as EUIs. We used data from anonymized micro-data on the ~3 million deaths from external causes. Our reclassification model used 10 decedent and event characteristics from the computerized death records. Results show that during this period about 14 % of non-transport accidents, 13 % of suicides, and 33 % of homicides were officially categorized as EUIs. Our findings also suggest that 2011 levels of non-transport accidents and suicides would have been about 24 % higher and of homicide about 82 % higher than that reported by official vital statistics data. Overuse of the external cause of death classification "event of undetermined intent" may indicate questionable quality of mortality data on external causes of death. This can have wide-ranging implications for families, medical professionals, the justice system, researchers, and policymakers. With our classification probability set as equal to or higher than 0.75, we were able to reclassify about two-thirds of EUI deaths in our sample. Our optional additional step allowed us to redistribute the remaining unclassified EUIs. Our method can be applied to data from any nation or sub-national population in which the EUI category is employed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 14%
Student > Master 4 14%
Student > Ph. D. Student 3 11%
Professor 2 7%
Other 2 7%
Other 5 18%
Unknown 8 29%
Readers by discipline Count As %
Social Sciences 8 29%
Medicine and Dentistry 4 14%
Psychology 3 11%
Business, Management and Accounting 1 4%
Economics, Econometrics and Finance 1 4%
Other 3 11%
Unknown 8 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 October 2018.
All research outputs
#13,955,130
of 22,826,360 outputs
Outputs from Population Health Metrics
#272
of 392 outputs
Outputs of similar age
#133,332
of 267,079 outputs
Outputs of similar age from Population Health Metrics
#8
of 12 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 392 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,079 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.