%0 Journal Article
%T Direct estimation of cause-specific mortality fractions from verbal autopsies: multisite validation study using clinical diagnostic gold standards
%A Abraham D Flaxman
%A Alireza Vahdatpour
%A Spencer L James
%A Jeanette K Birnbaum
%A Christopher JL Murray
%A the Population Health Metrics Research Consortium (PHMRC)
%J Population Health Metrics
%D 2011
%I BioMed Central
%R 10.1186/1478-7954-9-35
%X We applied the KL method to adult, child, and neonatal VA datasets from the Population Health Metrics Research Consortium gold standard verbal autopsy validation study, a multisite sample of 12,542 VAs where gold standard cause of death was established using strict clinical diagnostic criteria. To emulate real-world populations with varying CSMFs, we evaluated the KL estimations for 500 different test datasets of varying cause distribution. We assessed the quality of these estimates in terms of CSMF accuracy as well as linear regression and compared this with the results of PCVA.KL performance is similar to PCVA in terms of CSMF accuracy, attaining values of 0.669, 0.698, and 0.795 for adult, child, and neonatal age groups, respectively, when health care experience (HCE) items were included. We found that the length of the cause list has a dramatic effect on KL estimation quality, with CSMF accuracy decreasing substantially as the length of the cause list increases. We found that KL is not reliant on HCE the way PCVA is, and without HCE, KL outperforms PCVA for all age groups.Like all computer methods for VA analysis, KL is faster and cheaper than PCVA. Since it is a direct estimation technique, though, it does not produce individual-level predictions. KL estimates are of similar quality to PCVA and slightly better in most cases. Compared to other recently developed methods, however, KL would only be the preferred technique when the cause list is short and individual-level predictions are not needed.In settings where a non-negligible proportion of the population dies outside of the hospital system, verbal autopsies (VAs) are emerging as a vital tool for understanding the population-level patterns of cause-specific mortality fractions (CSMFs). By combining this with robust information on levels of age-specific all-cause mortality (also collected through household surveys, e.g., of sibling survivorship), it is possible to estimate age- and cause-specific mortality rat
%K Verbal autopsy
%K cause of death certification
%K validation
%K direct estimation
%U http://www.pophealthmetrics.com/content/9/1/35