Journal of Global Health (Jun 2016)

Validating hierarchical verbal autopsy expert algorithms in a large data set with known causes of death

  • Henry D Kalter,
  • Jamie Perin,
  • Robert E Black

DOI
https://doi.org/10.7189/jogh.06.010601
Journal volume & issue
Vol. 6, no. 1

Abstract

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Physician assessment historically has been the most common method of analyzing verbal autopsy (VA) data. Recently, the World Health Organization endorsed two automated methods, Tariff 2.0 and InterVA–4, which promise greater objectivity and lower cost. A disadvantage of the Tariff method is that it requires a training data set from a prior validation study, while InterVA relies on clinically specified conditional probabilities. We undertook to validate the hierarchical expert algorithm analysis of VA data, an automated, intuitive, deterministic method that does not require a training data set.

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