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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring
Global Health Action, Volume 6, No. 1, Article 21518, Year 2013
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Description
Objective: Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. Methods: A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. Findings: A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. Conclusions: The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians. © 2013 Jordana Leitao et al.
Authors & Co-Authors
Leitao, Jordana
Unknown Affiliation
Chandramohan, Daniel
Unknown Affiliation
Byass, P.
Unknown Affiliation
Jakob, Robert
Unknown Affiliation
Bundhamcharoen, Kanitta
Unknown Affiliation
Choprapawon, Chanpen
Unknown Affiliation
de Savigny, Don H.
Unknown Affiliation
Fottrell, Edward F.
Unknown Affiliation
França, Elisabeth Barboza
Unknown Affiliation
Frøen, J. Frederik
Unknown Affiliation
Gewaifel, Gihan Ismael
Unknown Affiliation
Hodgson, Abraham V.O.
Unknown Affiliation
Hounton, Sennen Houessey
Unknown Affiliation
Kahn, Kathleen
Unknown Affiliation
Krishnan, Anand
Unknown Affiliation
Kumar, Vishwajeet U.
Unknown Affiliation
Masanja, Honorati M.
Unknown Affiliation
Nichols, Erin K.
Unknown Affiliation
Notzon, Francis Sam
Unknown Affiliation
Rasooly, Mohammad Hafiz
Unknown Affiliation
Sankoh, Osman A.
Unknown Affiliation
Spiegel, Paul B.
Unknown Affiliation
AbouZahr, Carla
Unknown Affiliation
Amexo, Marc
Unknown Affiliation
Kebede, Derege
Unknown Affiliation
Alley, William Soumbey
Unknown Affiliation
Marinho, Maria De Fátima
Unknown Affiliation
Ali, Mohammed Ayub
Unknown Affiliation
Loyola, Enrique
Unknown Affiliation
Chikersal, Jyotsna
Unknown Affiliation
Gao, Jun
Unknown Affiliation
Annunziata, Giuseppe
Unknown Affiliation
Bahl, Rajiv
Unknown Affiliation
Bartolomeus, Kidist
Unknown Affiliation
Boerma, Ties
Unknown Affiliation
Üstün, Tevfik Bedirhan Bedirhan
Unknown Affiliation
Chou, Doris
Unknown Affiliation
Muhe, Lulu Mussa
Unknown Affiliation
Mathai, Matthews
Unknown Affiliation
Statistics
Citations: 131
Authors: 39
Affiliations: 26
Identifiers
Doi:
10.3402/gha.v6i0.21518
Study Design
Cross Sectional Study
Study Approach
Systematic review