@article{21938, author = {Joshi Rohina and Dandona R. and Dandona L. and Serina P. and Stewart A. and Riley I. and Hernandez B. and Freeman M. and Sanvictores D. and Tallo V. and Kumar V. and Murray C. and Lozano R. and Flaxman A. and Phillips D. and James S. and Atkinson C. and Ohno S. and Black R. and Ali S. and Baqui A. and Dantzer E. and Das V. and Dhingra U. and Dutta A. and Fawzi W. and Gómez S. and Mehta S. and Lopez A. and Alam S. and Mooney M. and Kumar A. and Luning R. and Ahuja R. and Alam N. and Chowdhury H. and Darmstadt G. and Kalter H. and Lucero M. and Pierce K. and Prasad R. and Premji Z. and Ramirez-Villalobos D. and Remolador H. and Romero M. and Said M. and Sazawal S. and Streatfield P. and Vadhatpour A. and Gamage S. and Hensman D. and Rampatige R. and Wijesekara N. and Praveen Devarsetty and Neal Bruce}, 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.

}, year = {2015}, journal = {BMC Medicine}, volume = {13}, edition = {2015/12/17}, pages = {302}, isbn = {1741-7015 (Electronic)
1741-7015 (Linking)}, note = {Serina, Peter
Riley, Ian
Stewart, Andrea
Flaxman, Abraham D
Lozano, Rafael
Mooney, Meghan D
Luning, Richard
Hernandez, Bernardo
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
Gamage, Saman
Gomez, Sara
Hensman, Dilip
James, Spencer L
Joshi, Rohina
Kalter, Henry D
Kumar, Aarti
Kumar, Vishwajeet
Lucero, Marilla
Mehta, Saurabh
Neal, Bruce
Ohno, Summer Lockett
Phillips, David
Pierce, Kelsey
Prasad, Rajendra
Praveen, Devarsetty
Premji, Zul
Ramirez-Villalobos, Dolores
Rampatige, Rasika
Remolador, Hazel
Romero, Minerva
Said, Mwanaidi
Sanvictores, Diozele
Sazawal, Sunil
Streatfield, Peter K
Tallo, Veronica
Vadhatpour, Alireza
Wijesekara, Nandalal
Murray, Christopher J L
Lopez, Alan D
Research Support, Non-U.S. Gov't
England
BMC Med. 2015 Dec 16;13:302. doi: 10.1186/s12916-015-0528-8.}, language = {eng}, }