Validating hierarchical verbal autopsy expert algorithms in a large data set with known causes of death
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 i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Edinburgh University Global Health Society
2016-06-01
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| Series: | Journal of Global Health |
| Subjects: | |
| Online Access: | http://www.jogh.org/documents/issue201601/jogh-06-010601.pdf |
| Summary: | 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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| ISSN: | 2047-2978 2047-2986 |