A shortened verbal autopsy instrument for use in routine mortality surveillance systems

Peter Serina; Ian Riley; Andrea Stewart; Abraham D. Flaxman; Rafael Lozano; Meghan D. Mooney; Richard Luning; Bernardo Hernandez; Robert Black; Ramesh Ahuja; Nurul Alam; Sayed Saidul Alam; Said Mohammed Ali; Charles Atkinson; Abdulla H. Baqui; Hafizur R. Chowdhury; Lalit Dandona; Rakhi Dandona; Emily Dantzer; Gary L. Darmstadt; Vinita Das; Usha Dhingra; Arup Dutta; Wafaie Fawzi; Michael Freeman; Saman Gamage; Sara Gomez; Dilip Hensman; Spencer L. James; Rohina Joshi; Henry D. Kalter; Aarti Kumar; Vishwajeet Kumar; Marilla Lucero; Saurabh Mehta; Bruce Neal; Summer Lockett Ohno; David Phillips; Kelsey Pierce; Rajendra Prasad; Devarsetty Praveen; Zul Premji; Dolores Ramirez-Villalobos; Rasika Rampatige; Hazel Remolador; Minerva Romero; Mwanaidi Said; Diozele Sanvictores; Sunil Sazawal; Peter K. Streatfield; Veronica Tallo; Alireza Vadhatpour; Nandalal Wijesekara; Christopher J.L. Murray; Alan D. Lopez

doi:10.1186/s12916-015-0528-8

A shortened verbal autopsy instrument for use in routine mortality surveillance systems

Peter Serina, Ian Riley, Andrea Stewart, Abraham D. Flaxman, Rafael Lozano, Meghan D. Mooney, Richard Luning, Bernardo Hernandez, Robert Black, Ramesh Ahuja, Nurul Alam, Sayed Saidul Alam, Said Mohammed Ali, Charles Atkinson, Abdulla H. Baqui, Hafizur R. Chowdhury, Lalit Dandona, Rakhi Dandona, Emily Dantzer, Gary L. DarmstadtVinita Das, Usha Dhingra, Arup Dutta, Wafaie Fawzi, Michael Freeman, Saman Gamage, Sara Gomez, Dilip Hensman, Spencer L. James, Rohina Joshi, Henry D. Kalter, Aarti Kumar, Vishwajeet Kumar, Marilla Lucero, Saurabh Mehta, Bruce Neal, Summer Lockett Ohno, David Phillips, Kelsey Pierce, Rajendra Prasad, Devarsetty Praveen, Zul Premji, Dolores Ramirez-Villalobos, Rasika Rampatige, Hazel Remolador, Minerva Romero, Mwanaidi Said, Diozele Sanvictores, Sunil Sazawal, Peter K. Streatfield, Veronica Tallo, Alireza Vadhatpour, Nandalal Wijesekara, Christopher J.L. Murray, Alan D. Lopez

Research output: Contribution to journal › Article › peer-review

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Abstract

Background: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. Methods: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. Results: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55 %. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4 %, 0.0 %, and 0.6 % for the adult, child, and neonatal modules, respectively. Conclusions: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50 % without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

Original language	English
Article number	302
Journal	BMC Medicine
Volume	13
Issue number	1
DOIs	https://doi.org/10.1186/s12916-015-0528-8
Publication status	Published - 16 Dec 2015
Externally published	Yes

Keywords

Causes of death
Mortality surveillance
Verbal autopsy questionnaire

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10.1186/s12916-015-0528-8

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Serina, P., Riley, I., Stewart, A., Flaxman, A. D., Lozano, R., Mooney, M. D., Luning, R., Hernandez, B., Black, R., Ahuja, R., Alam, N., Alam, S. S., Ali, S. M., Atkinson, C., Baqui, A. H., Chowdhury, H. R., Dandona, L., Dandona, R., Dantzer, E., ... Lopez, A. D. (2015). A shortened verbal autopsy instrument for use in routine mortality surveillance systems. BMC Medicine, 13(1), Article 302. https://doi.org/10.1186/s12916-015-0528-8

@article{ab63432e83c640d385e8366d2434ed5e,

title = "A shortened verbal autopsy instrument for use in routine mortality surveillance systems",

abstract = "Background: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. Methods: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. Results: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55 %. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4 %, 0.0 %, and 0.6 % for the adult, child, and neonatal modules, respectively. Conclusions: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50 % without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.",

keywords = "Causes of death, Mortality surveillance, Verbal autopsy questionnaire",

author = "Peter Serina and Ian Riley and Andrea Stewart and Flaxman, {Abraham D.} and Rafael Lozano and Mooney, {Meghan D.} and Richard Luning and Bernardo Hernandez and Robert Black and Ramesh Ahuja and Nurul Alam and Alam, {Sayed Saidul} and Ali, {Said Mohammed} and Charles Atkinson and Baqui, {Abdulla H.} and Chowdhury, {Hafizur R.} and Lalit Dandona and Rakhi Dandona and Emily Dantzer and Darmstadt, {Gary L.} and Vinita Das and Usha Dhingra and Arup Dutta and Wafaie Fawzi and Michael Freeman and Saman Gamage and Sara Gomez and Dilip Hensman and James, {Spencer L.} and Rohina Joshi and Kalter, {Henry D.} and Aarti Kumar and Vishwajeet Kumar and Marilla Lucero and Saurabh Mehta and Bruce Neal and Ohno, {Summer Lockett} and David Phillips and Kelsey Pierce and Rajendra Prasad and Devarsetty Praveen and Zul Premji and Dolores Ramirez-Villalobos and Rasika Rampatige and Hazel Remolador and Minerva Romero and Mwanaidi Said and Diozele Sanvictores and Sunil Sazawal and Streatfield, {Peter K.} and Veronica Tallo and Alireza Vadhatpour and Nandalal Wijesekara and Murray, {Christopher J.L.} and Lopez, {Alan D.}",

note = "Funding Information: The authors thank our collaborators Dr. Osvaldo Gonz{\'a}lez La Rivere, Dra. Araceli Mart{\'i}nez Gonz{\'a}lez, Dr. Miguel {\'A}ngel Mart{\'i}nez Guzm{\'a}n, Dr. Argemiro Jos{\'e} Genes Narr, Dr. Antonio Manrique Martin, Dr. Adri{\'a}n Ram{\'i}rez Alvear, Dr. Benjam{\'i}n M{\'e}ndez Pinto, Dr. Enrique Gardu{\~n}o Salvador, Dr. Rogelio P{\'e}rez Padilla, Dra. Cecilia Garc{\'i}a Sancho, Dr. Mauricio Moreno Portillo, and Dr. Eduardo Barrag{\'a}n 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. Publisher Copyright: {\textcopyright} 2015 Serina et al.",

year = "2015",

month = dec,

day = "16",

doi = "10.1186/s12916-015-0528-8",

language = "English",

volume = "13",

journal = "BMC Medicine",

publisher = "BioMed Central Ltd.",

number = "1",

}

Serina, P, Riley, I, Stewart, A, Flaxman, AD, Lozano, R, Mooney, MD, Luning, R, Hernandez, B, Black, R, Ahuja, R, Alam, N, Alam, SS, Ali, SM, Atkinson, C, Baqui, AH, Chowdhury, HR, Dandona, L, Dandona, R, Dantzer, E, Darmstadt, GL, Das, V, Dhingra, U, Dutta, A, Fawzi, W, Freeman, M, Gamage, S, Gomez, S, Hensman, D, James, SL, Joshi, R, Kalter, HD, Kumar, A, Kumar, V, Lucero, M, Mehta, S, Neal, B, Ohno, SL, Phillips, D, Pierce, K, Prasad, R, Praveen, D, Premji, Z, Ramirez-Villalobos, D, Rampatige, R, Remolador, H, Romero, M, Said, M, Sanvictores, D, Sazawal, S, Streatfield, PK, Tallo, V, Vadhatpour, A, Wijesekara, N, Murray, CJL & Lopez, AD 2015, 'A shortened verbal autopsy instrument for use in routine mortality surveillance systems', BMC Medicine, vol. 13, no. 1, 302. https://doi.org/10.1186/s12916-015-0528-8

TY - JOUR

T1 - A shortened verbal autopsy instrument for use in routine mortality surveillance systems

AU - Serina, Peter

AU - Riley, Ian

AU - Stewart, Andrea

AU - Flaxman, Abraham D.

AU - Lozano, Rafael

AU - Mooney, Meghan D.

AU - Luning, Richard

AU - Hernandez, Bernardo

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 - Gamage, Saman

AU - Gomez, Sara

AU - Hensman, Dilip

AU - James, Spencer L.

AU - Joshi, Rohina

AU - Kalter, Henry D.

AU - Kumar, Aarti

AU - Kumar, Vishwajeet

AU - Lucero, Marilla

AU - Mehta, Saurabh

AU - Neal, Bruce

AU - Ohno, Summer Lockett

AU - Phillips, David

AU - Pierce, Kelsey

AU - Prasad, Rajendra

AU - Praveen, Devarsetty

AU - Premji, Zul

AU - Ramirez-Villalobos, Dolores

AU - Rampatige, Rasika

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 - Wijesekara, Nandalal

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. Publisher Copyright: © 2015 Serina et al.

PY - 2015/12/16

Y1 - 2015/12/16

N2 - Background: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. Methods: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. Results: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55 %. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4 %, 0.0 %, and 0.6 % for the adult, child, and neonatal modules, respectively. Conclusions: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50 % without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

AB - Background: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. Methods: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. Results: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55 %. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4 %, 0.0 %, and 0.6 % for the adult, child, and neonatal modules, respectively. Conclusions: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50 % without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

KW - Causes of death

KW - Mortality surveillance

KW - Verbal autopsy questionnaire

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U2 - 10.1186/s12916-015-0528-8

DO - 10.1186/s12916-015-0528-8

M3 - Article

C2 - 26670275

AN - SCOPUS:84973410106

VL - 13

JO - BMC Medicine

JF - BMC Medicine

IS - 1

M1 - 302

ER -

A shortened verbal autopsy instrument for use in routine mortality surveillance systems

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