Document Detail


Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool.
MedLine Citation:
PMID:  22944365     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: Verbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and comparability. The World Health Organization (WHO) has led the development of the 2012 WHO VA instrument as a new standard, intended both as a research tool and for routine registration of deaths.
OBJECTIVE: A new public-domain probabilistic model for interpreting VA data, InterVA-4, is described, which builds on previous versions and is aligned with the 2012 WHO VA instrument.
DESIGN: The new model has been designed to use the VA input indicators defined in the 2012 WHO VA instrument and to deliver causes of death compatible with the International Classification of Diseases version 10 (ICD-10) categorised into 62 groups as defined in the 2012 WHO VA instrument. In addition, known shortcomings of previous InterVA models have been addressed in this revision, as well as integrating other work on maternal and perinatal deaths.
RESULTS: The InterVA-4 model is presented here to facilitate its widespread use and to enable further field evaluation to take place. Results from a demonstration dataset from Agincourt, South Africa, show continuity of interpretation between InterVA-3 and InterVA-4, as well as differences reflecting specific issues addressed in the design and development of InterVA-4.
CONCLUSIONS: InterVA-4 is made freely available as a new standard model for interpreting VA data into causes of death. It can be used for determining cause of death both in research settings and for routine registration. Further validation opportunities will be explored. These developments in cause of death registration are likely to substantially increase the global coverage of cause-specific mortality data.
Authors:
Peter Byass; Daniel Chandramohan; Samuel J Clark; Lucia D'Ambruoso; Edward Fottrell; Wendy J Graham; Abraham J Herbst; Abraham Hodgson; Sennen Hounton; Kathleen Kahn; Anand Krishnan; Jordana Leitao; Frank Odhiambo; Osman A Sankoh; Stephen M Tollman
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2012-09-03
Journal Detail:
Title:  Global health action     Volume:  5     ISSN:  1654-9880     ISO Abbreviation:  Glob Health Action     Publication Date:  2012  
Date Detail:
Created Date:  2012-09-04     Completed Date:  2013-01-10     Revised Date:  2014-04-25    
Medline Journal Info:
Nlm Unique ID:  101496665     Medline TA:  Glob Health Action     Country:  Sweden    
Other Details:
Languages:  eng     Pagination:  1-8     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Autopsy
Bayes Theorem
Caregivers*
Cause of Death*
Documentation / standards*
Humans
International Classification of Diseases
Interviews as Topic / methods
Models, Statistical
Reference Standards
Verbal Behavior
World Health Organization
Grant Support
ID/Acronym/Agency:
058893/Z/99/A//Wellcome Trust; 069683/Z/02/Z//Wellcome Trust; 085477/Z/08/Z//Wellcome Trust; 097410//Wellcome Trust; R24 HD042828/HD/NICHD NIH HHS
Comments/Corrections

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