Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies

Population Health Metrics

Research

Christopher JL Murray¹  Spencer L James¹  Abraham D Flaxman¹ 

[1] Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave., 98121, Seattle, WA, USA;

关键词: Verbal autopsy;    validation;    gold standard;    Tariff Method;    cause of death;    mortality;    cause-specific mortality fractions;   

DOI  :  10.1186/1478-7954-9-31

 received in 2011-04-14, accepted in 2011-08-04,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundVerbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data.MethodsTariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data.ResultsTariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates.ConclusionsVerbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science.

【 授权许可】

Unknown   
© James et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.