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Algorithm development for the automation of death certificate analysis and coding.

Kaylee McCord1, Emma L Gause2, Suzanne McLone3

  • 1Boston University Chobanian and Avedisian School of Medicine, 72 E Concord St, Boston, MA 02118, USA.

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Summary
This summary is machine-generated.

An open-source algorithm automates cause of death coding for analyzing mortality in homeless populations and public health crises. It accurately classifies death certificates, aiding mortality tracking efforts.

Keywords:
AlgorithmCause of DeathDeath CertificateMortalityOverdose

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Area of Science:

  • Public Health
  • Data Science
  • Mortality Statistics

Background:

  • Analyzing mortality data is crucial for public health surveillance.
  • Understudied populations and emerging crises pose challenges for traditional mortality analysis.
  • Existing methods for cause of death coding can be time-consuming and resource-intensive.

Purpose of the Study:

  • To develop an open-source, rule-based algorithm for automated cause of death coding.
  • To enable mortality analysis in understudied populations and during public health crises.
  • To improve the efficiency and accuracy of mortality data classification.

Main Methods:

  • Selected death categories of immediate public health concern.
  • Developed keyword lists in consultation with a domain expert.
  • Built and trained a rule-based keyword matching algorithm on US death certificate data.
  • Validated the algorithm against manual coding in a case study of deaths among people experiencing homelessness.

Main Results:

  • The algorithm demonstrated strong agreement with manual coding for all-cause identification (κ=0.905) and mutually exclusive sorting (κ=0.853).
  • The findings confirm the algorithm's capability to accurately classify death certificates into meaningful categories.
  • The study highlights the algorithm's effectiveness in handling diverse mortality data.

Conclusions:

  • The open-source, customizable algorithm facilitates mortality analyses using publicly available death certificate data.
  • This tool can bridge gaps in current mortality tracking efforts.
  • Researchers and journalists can utilize this algorithm for timely public health insights.