TY - JOUR
T1 - Designing verbal autopsy studies
AU - King, Gary
AU - Lu, Ying
AU - Shibuya, Kenji
N1 - Funding Information:
Open source software that implements all the methods described herein is available at http://gking.harvard.edu/va. Our thanks to Alan Lopez and Shanon Peter for data access. The Tanzania data was provided by the University of Newcastle upon Tyne (UK) as an output of the Adult Morbidity and Mortality Project (AMMP). AMMP was a project of the Tanzanian Ministry of Health, funded by the UK Department for International Development (DFID), and implemented in partnership with the University of Newcastle upon Tyne. Additional funding for the preparation of the data was provided through MEASURE Evaluation, Phase 2, a USAID Cooperative Agreement (GPO-A-00-03-00003-00) implemented by the Carolina Population Center, University of North Carolina at Chapel Hill. This publication was also supported by Grant P10462-109/9903GLOB-2, The Global Burden of Disease 2000 in Aging Populations (P01 AG17625-01), from the United States National Institutes of Health (NIH) National Institute on Aging (NIA) and from the National Science Foundation (SES-0318275, IIS-9874747, DMS-0631652).
PY - 2010/6/23
Y1 - 2010/6/23
N2 - Background: Verbal autopsy analyses are widely used for estimating cause-specific mortality rates (CSMR) in the vast majority of the world without high-quality medical death registration. Verbal autopsies -- survey interviews with the caretakers of imminent decedents -- stand in for medical examinations or physical autopsies, which are infeasible or culturally prohibited.Methods and Findings: We introduce methods, simulations, and interpretations that can improve the design of automated, data-derived estimates of CSMRs, building on a new approach by King and Lu (2008). Our results generate advice for choosing symptom questions and sample sizes that is easier to satisfy than existing practices. For example, most prior effort has been devoted to searching for symptoms with high sensitivity and specificity, which has rarely if ever succeeded with multiple causes of death. In contrast, our approach makes this search irrelevant because it can produce unbiased estimates even with symptoms that have very low sensitivity and specificity. In addition, the new method is optimized for survey questions caretakers can easily answer rather than questions physicians would ask themselves. We also offer an automated method of weeding out biased symptom questions and advice on how to choose the number of causes of death, symptom questions to ask, and observations to collect, among others.Conclusions: With the advice offered here, researchers should be able to design verbal autopsy surveys and conduct analyses with greatly reduced statistical biases and research costs.
AB - Background: Verbal autopsy analyses are widely used for estimating cause-specific mortality rates (CSMR) in the vast majority of the world without high-quality medical death registration. Verbal autopsies -- survey interviews with the caretakers of imminent decedents -- stand in for medical examinations or physical autopsies, which are infeasible or culturally prohibited.Methods and Findings: We introduce methods, simulations, and interpretations that can improve the design of automated, data-derived estimates of CSMRs, building on a new approach by King and Lu (2008). Our results generate advice for choosing symptom questions and sample sizes that is easier to satisfy than existing practices. For example, most prior effort has been devoted to searching for symptoms with high sensitivity and specificity, which has rarely if ever succeeded with multiple causes of death. In contrast, our approach makes this search irrelevant because it can produce unbiased estimates even with symptoms that have very low sensitivity and specificity. In addition, the new method is optimized for survey questions caretakers can easily answer rather than questions physicians would ask themselves. We also offer an automated method of weeding out biased symptom questions and advice on how to choose the number of causes of death, symptom questions to ask, and observations to collect, among others.Conclusions: With the advice offered here, researchers should be able to design verbal autopsy surveys and conduct analyses with greatly reduced statistical biases and research costs.
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U2 - 10.1186/1478-7954-8-19
DO - 10.1186/1478-7954-8-19
M3 - Article
C2 - 20573233
AN - SCOPUS:77953709447
SN - 1478-7954
VL - 8
JO - Population Health Metrics
JF - Population Health Metrics
IS - 1
M1 - 19
ER -