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Published in: BMC Medical Research Methodology 1/2019

Open Access 01-12-2019 | Autopsy | Research article

Robustness of the Tariff method for diagnosing verbal autopsies: impact of additional site data on the relationship between symptom and cause

Authors: Hafizur Rahman Chowdhury, Abraham D. Flaxman, Jonathan C. Joseph, Riley H. Hazard, Nurul Alam, Ian Douglas Riley, Alan D. Lopez

Published in: BMC Medical Research Methodology | Issue 1/2019

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Abstract

Background

Verbal autopsy (VA) is increasingly being considered as a cost-effective method to improve cause of death information in countries with low quality vital registration. VA algorithms that use empirical data have an advantage over expert derived algorithms in that they use responses to the VA instrument as a reference instead of physician opinion. It is unclear how stable these data driven algorithms, such as the Tariff 2.0 method, are to cultural and epidemiological variations in populations where they might be employed.

Methods

VAs were conducted in three sites as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Similar diagnostic criteria and cause lists as the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. We assessed changes in Tariffs by examining the proportion of Tariffs that changed significantly after the addition of the IMMCMC dataset to the PHMRC dataset.

Results

The IMMCMC study added 3512 deaths to the GS VA database (2491 adults, 320 children, and 701 neonates). Chance-corrected cause specific mortality fractions for Tariff improved with the addition of the IMMCMC dataset for adults (+ 5.0%), children (+ 5.8%), and neonates (+ 1.5%). 97.2% of Tariffs did not change significantly after the addition of the IMMCMC dataset.

Conclusions

Tariffs generally remained consistent after adding the IMMCMC dataset. Population level performance of the Tariff method for diagnosing VAs improved marginally for all age groups in the combined dataset. These findings suggest that cause-symptom relationships of Tariff 2.0 might well be robust across different population settings in developing countries. Increasing the total number of GS deaths improves the validity of Tariff and provides a foundation for the validation of other empirical algorithms.
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Metadata
Title
Robustness of the Tariff method for diagnosing verbal autopsies: impact of additional site data on the relationship between symptom and cause
Authors
Hafizur Rahman Chowdhury
Abraham D. Flaxman
Jonathan C. Joseph
Riley H. Hazard
Nurul Alam
Ian Douglas Riley
Alan D. Lopez
Publication date
01-12-2019
Publisher
BioMed Central
Keyword
Autopsy
Published in
BMC Medical Research Methodology / Issue 1/2019
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-019-0877-7

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