TY - JOUR
T1 - Improving performance of the Tariff Method for assigning causes of death to verbal autopsies
AU - Serina, Peter
AU - Riley, Ian
AU - Stewart, Andrea
AU - James, Spencer L.
AU - Flaxman, Abraham D.
AU - Lozano, Rafael
AU - Hernandez, Bernardo
AU - Mooney, Meghan D.
AU - Luning, Richard
AU - Black, Robert
AU - Ahuja, Ramesh
AU - Alam, Nurul
AU - Alam, Sayed Saidul
AU - Ali, Said Mohammed
AU - Atkinson, Charles
AU - Baqui, Abdulla H.
AU - Chowdhury, Hafizur R.
AU - Dandona, Lalit
AU - Dandona, Rakhi
AU - Dantzer, Emily
AU - Darmstadt, Gary L.
AU - Das, Vinita
AU - Dhingra, Usha
AU - Dutta, Arup
AU - Fawzi, Wafaie
AU - Freeman, Michael
AU - Gomez, Sara
AU - Gouda, Hebe N.
AU - Joshi, Rohina
AU - Kalter, Henry D.
AU - Kumar, Aarti
AU - Kumar, Vishwajeet
AU - Lucero, Marilla
AU - Maraga, Seri
AU - Mehta, Saurabh
AU - Neal, Bruce
AU - Ohno, Summer Lockett
AU - Phillips, David
AU - Pierce, Kelsey
AU - Prasad, Rajendra
AU - Praveen, Devarsatee
AU - Premji, Zul
AU - Ramirez-Villalobos, Dolores
AU - Rarau, Patricia
AU - Remolador, Hazel
AU - Romero, Minerva
AU - Said, Mwanaidi
AU - Sanvictores, Diozele
AU - Sazawal, Sunil
AU - Streatfield, Peter K.
AU - Tallo, Veronica
AU - Vadhatpour, Alireza
AU - Vano, Miriam
AU - Murray, Christopher J.L.
AU - Lopez, Alan D.
N1 - Funding Information:
The authors thank our collaborators, Dr Osvaldo González La Rivere, Dra Araceli Martínez González, Dr Miguel Ángel Martínez Guzmán, Dr Argemiro José Genes Narr, Dr Antonio Manrique Martin, Dr Adrián Ramírez Alvear, Dr Benjamín Méndez Pinto, Dr Enrique Garduño Salvador, Dr Rogelio Pérez Padilla, Dra Cecilia García Sancho, Dr Mauricio Moreno Portillo, and Dr Eduardo Barragán Padilla. The authors also thank the Secretary of Health of the Federal District in Mexico City, Dr Armando Ahued, and the coordinator of high specialty hospitals of the Ministry of Health, Dr Bernardo Bidart, for their help in accessing medical records needed for this study. This analysis was made possible by the series of studies produced by the Population Health Metrics Research Consortium. The work was funded by a grant from the Bill & Melinda Gates Foundation through the Grand Challenges in Global Health initiative. This work was also supported by a National Health and Medical Research Council project grant, improving methods to measure comparable mortality by cause (grant no. 631494). The funders had no role in study design, data collection and analysis, interpretation of data, decision to publish, or preparation of the manuscript. The corresponding author had full access to all data analyzed and had final responsibility for the decision to submit this original research paper for publication.
Funding Information:
The development of Tariff 1.0 had been based on the PHMRC validation database and thus all deaths had occurred in hospital. Our initial aim in developing Tariff 2.0 was to review the cause distributions of deaths in community VAs using Tariff 1.0 and to see whether these distributions were plausible. This review was based on the examination of 12,528 VAs, not linked to gold standard hospital data, collected from community samples using the PHMRC VAI. VAs of 3,067 deaths, occurring within 5 years of interview, were collected from household surveys in Mexico City in Mexico, Andhra Pradesh in India, Pemba in Tanzania, and Bohol in the Philippines, as part of the PHMRC study [13]. A further 9,461 VAs were collected in Chandpur and Comilla Districts in Bangladesh, in Central and Eastern Highlands Provinces in Papua New Guinea, and in Bohol Province in the Philippines, as part of a study funded by the National Health and Medical Research Council (NMHRC) of Australia. The age-site distribution of these deaths is shown in Table 2. The performance of Tariff 2.0 could only be compared with that of Tariff 1.0 by using the PHMRC gold standard database.
Publisher Copyright:
© 2015 Serina et al.
PY - 2015/12/8
Y1 - 2015/12/8
N2 - Background: 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. Methods: 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. Results: 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. Conclusions: 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.
AB - Background: 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. Methods: 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. Results: 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. Conclusions: 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.
KW - Causes of death
KW - Mortality surveillance
KW - Verbal autopsy questionnaire
UR - http://www.scopus.com/inward/record.url?scp=84949238405&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84949238405&partnerID=8YFLogxK
U2 - 10.1186/s12916-015-0527-9
DO - 10.1186/s12916-015-0527-9
M3 - Article
C2 - 26644140
AN - SCOPUS:84949238405
SN - 1741-7015
VL - 13
JO - BMC medicine
JF - BMC medicine
IS - 1
M1 - 291
ER -