ArticleAnnals of epidemiology2025
Algorithm development for the automation of death certificate analysis and coding.
Article in Annals of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
purposeWe developed an open-source, rule-based algorithm to automate cause of death coding for analyzing mortality in understudied populations, such as people experiencing homelessness, and dynamic public health crises including overdoses and climate-related deaths.
methodsDeath categories of immediate public health concern were selected and keyword lists representing each category were developed in consultation with a domain expert. A rule-based keyword matching algorithm was built to assign death records into the selected death categories. The algorithm was trained on death certificate data from five counties across the United States. A case study applying the algorithm to deaths among people experiencing homelessness in Clark County, NV from 2015 to 2018 (N = 646) tested the accuracy of the program against a manual coder.
resultsThere was strong agreement between the algorithm and the manual coder in the all-cause identification (κ 0.905) and mutually exclusive sorting (κ 0.853) methods. Our findings illustrate the algorithm's ability to accurately classify death certificates into useful categories.
conclusionThis open-source, customizable algorithm may be utilized by researchers, journalists, and others to conduct mortality analyses with publicly available death certificate data, bridging gaps in existing mortality tracking efforts.
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