Improving performance of the Tariff Method for assigning causes of death to verbal autopsies

Serina, Peter, Riley, Ian, Stewart, Andrea, James, Spencer L., Flaxman, Abraham D., Lozano, Rafael, Hernandez, Bernardo, Mooney, Meghan D., Luning, Richard, Black, Robert, Ahuja, Ramesh, Alam, Nurul, Alam, Sayed Saidul, Ali, Said Mohammed, Atkinson, Charles, Baqui, Abdulla H., Chowdhury, Hafizur R., Dandona, Lalit, Dandona, Rakhi, Dantzer, Emily, Darmstadt, Gary L., Das, Vinita, Dhingra, Usha, Dutta, Arup, Fawzi, Wafaie, Freeman, Michael, Gomez, Sara, Gouda, Hebe N., Joshi, Rohina, Kalter, Henry D., Kumar, Aarti, Kumar, Vishwajeet, Lucero, Marilla, Maraga, Seri, Mehta, Saurabh, Neal, Bruce, Ohno, Summer Lockett, Phillips, David, Pierce, Kelsey, Prasad, Rajendra, Praveen, Devarsatee, Premji, Zul, Ramirez-Villalobos, Dolores, Rarau, Patricia, Remolador, Hazel, Romero, Minerva, Said, Mwanaidi, Sanvictores, Diozele, Sazawal, Sunil, Streatfield, Peter K., Tallo, Veronica, Vadhatpour, Alireza, Vano, Miriam, Murray, Christopher J. L. and Lopez, Alan D. (2015) Improving performance of the Tariff Method for assigning causes of death to verbal autopsies. BMC Medicine, 13 291: 1-13. doi:10.1186/s12916-015-0527-9

Author Serina, Peter
Riley, Ian
Stewart, Andrea
James, Spencer L.
Flaxman, Abraham D.
Lozano, Rafael
Hernandez, Bernardo
Mooney, Meghan D.
Luning, Richard
Black, Robert
Ahuja, Ramesh
Alam, Nurul
Alam, Sayed Saidul
Ali, Said Mohammed
Atkinson, Charles
Baqui, Abdulla H.
Chowdhury, Hafizur R.
Dandona, Lalit
Dandona, Rakhi
Dantzer, Emily
Darmstadt, Gary L.
Das, Vinita
Dhingra, Usha
Dutta, Arup
Fawzi, Wafaie
Freeman, Michael
Gomez, Sara
Gouda, Hebe N.
Joshi, Rohina
Kalter, Henry D.
Kumar, Aarti
Kumar, Vishwajeet
Lucero, Marilla
Maraga, Seri
Mehta, Saurabh
Neal, Bruce
Ohno, Summer Lockett
Phillips, David
Pierce, Kelsey
Prasad, Rajendra
Praveen, Devarsatee
Premji, Zul
Ramirez-Villalobos, Dolores
Rarau, Patricia
Remolador, Hazel
Romero, Minerva
Said, Mwanaidi
Sanvictores, Diozele
Sazawal, Sunil
Streatfield, Peter K.
Tallo, Veronica
Vadhatpour, Alireza
Vano, Miriam
Murray, Christopher J. L.
Lopez, Alan D.
Title Improving performance of the Tariff Method for assigning causes of death to verbal autopsies
Journal name BMC Medicine   Check publisher's open access policy
ISSN 1741-7015
Publication date 2015-12-08
Year available 2015
Sub-type Article (original research)
DOI 10.1186/s12916-015-0527-9
Open Access Status DOI
Volume 13
Issue 291
Start page 1
End page 13
Total pages 13
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method.

This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database.

For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5 %, 7.4 %, and 14.9 % for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0 %, 13.5 %, and 21.2 %, respectively. Similar levels of improvement are seen in analyses without HCE.

Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.
Keyword Verbal autopsy questionnaire
Mortality surveillance
Causes of death
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Public Health Publications
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