Validating the InterVA Model to Estimate the Burden of Mortality from Verbal Autopsy Data: A Population-Based Cross-Sectional Study

Sebsibe Tadesse,Thomas A Smith

doi:10.1371/journal.pone.0073463

Abstract

BackgroundIn countries with incomplete or no vital registration systems, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. But in addition to being time and energy consuming, the method is liable to produce inconsistent results. The aim of this study is to validate the InterVA model for estimating the burden of mortality from verbal autopsy data by using physician review as a reference standard.Methods and FindingsA population-based cross-sectional study was conducted from March to April, 2012. All adults aged ≥14 years and died between 01 January, 2010 and 15 February, 2012 were included in the study. The verbal autopsy interviews were reviewed by the InterVA model and physicians to estimate cause-specific mortality fractions. Cohen’s kappa statistic, sensitivity, specificity, positive predictive value, and negative predictive value were applied to compare the agreement between the InterVA model and the physician review. A total of 408 adult deaths were studied. There was a general similarity and just slight differences between the InterVA model and the physicians in assigning cause-specific mortality. Both approaches showed an overall agreement in 298 (73%) cases [kappa = 0.49, 95% CI: 0.37-0.60]. The observed sensitivities and specificities across causes of death categories varied from 13.3% to 81.9% and 77.7% to 99.5%, respectively.ConclusionsIn understanding the burden of disease and setting health intervention priorities in areas that lack reliable vital registration systems, an accurate analysis of verbal autopsies is essential. Therefore, users should be aware of the suboptimal performance of the InterVA model. Similar validation studies need to be undertaken considering the limitation of the physician review as gold standard since physicians may misinterpret some of the verbal autopsy data and finally reach a wrong conclusion of the cause of death.

Highlights

Developing countries generally lack consistent, timely, and reliable information on the level of cause-specific mortality fractions (CSMFs) in their populations [1]
Any meaningful health intervention policy and/or program must be informed by the cause of deaths (CODs) that are of the greatest importance locally
A direct comparison of the CODs assigned by the physicians to the first CODs assigned by the InterVA model showed that there was an overall agreement in 298 (73%) cases [kappa = 0.49, 95% CI: 0.37-0.60]

Summary

Introduction

Developing countries generally lack consistent, timely, and reliable information on the level of cause-specific mortality fractions (CSMFs) in their populations [1]. There may be inter and intra-reviewer variability among physicians that may lead to inconsistencies in COD data, hindering reliable temporal and spatial comparisons of mortality They mostly use open history to reach a decision and may not account consistently for all indicators. In countries with incomplete or no vital registration systems, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. The aim of this study is to validate the InterVA model for estimating the burden of mortality from verbal autopsy data by using physician review as a reference standard. Similar validation studies need to be undertaken considering the limitation of the physician review as gold standard since physicians may misinterpret some of the verbal autopsy data and reach a wrong conclusion of the cause of death

Objectives

Methods

Conclusion