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What is verbal autopsy?Two women talking as one takes notes on a laptop

Critical information on population health is needed to inform planning, resource allocation, program implementation, monitoring, and evaluation. Since many countries lack complete vital registration systems, one of the key pieces of information about population health is missing – causes of death. Understanding what the most prevalent causes of death are in a given population can help target preventive interventions and provide health services.

Verbal autopsy (VA) is a method of determining individuals’ causes of death and cause-specific mortality fractions in populations without a complete vital registration system. Verbal autopsies consist of a trained interviewer using a questionnaire to collect information about the signs, symptoms, and demographic characteristics of a recently deceased person from an individual familiar with the deceased. A standard VA instrument paired with easy-to-implement and effective analytic methods can help bridge significant gaps in information about causes of death, particularly in resource-poor settings.

Tools for interviewers

The Verbal Autopsy research team’s gold standard VA dataset, instruments, analysis tools, and protocols for implementing it are available to the public online, enabling policymakers and researchers to help address persistent inequities in health outcomes.

SmartVA-Analyze Application

SmartVA-Analyze is an application that implements the Tariff 2.0 Method1 for computer certification of verbal autopsies. It takes verbal autopsy interview data as input and produces cause of death estimates at the individual and population levels. The SmartVA cause of death assignment system was designed and validated with the Population Health Metrics Research Consortium (PHMRC) Gold Standard VA database collected as part of the PHMRC Gold Standard VA Validation Study.2

Downloads:

Questionnaires

The PHMRC Shortened Questionnaire is a standardized VA questionnaire developed by the Population Health Metrics Research Consortium, based on World Health Organization (WHO) standards.3 The SmartVA system is designed for analyzing VA data collected electronically using the PHMRC Full and Shortened Questionnaires with the Open Data Kit (ODK) Collect system on Android devices. Paper-based versions of the PHMRC Full and Shortened Questionnaires are also available.

Database

The Population Health Metrics Research Consortium (PHMRC) Gold Standard VA Validation database is in the public domain. Download it from the Global Health Data Exchange.

Source Code

The SmartVA-Analyze Application source code can be found on GitHub.

Want to stay up to date on the latest developments in SmartVA? Subscribe to the SmartVA Announcement Mailing List.

IHME's research activities

The verbal autopsy research team’s activities provide data and resources that will be the basis for rapid and effective field assessment of population-level causes of death.

Health Metrics Science lecture series

Drs. Abraham Flaxman and Bernardo Hernández Prado present on using verbal autopsy tools to automate the cause of death certification process.

 

Watch more videos on verbal autopsy.

Develop high-performing methods to analyze verbal autopsy data

IHME was the lead institution in the Population Health Metrics Research Consortium (PHMRC) project, which aimed to develop methods and instruments to quantitatively assess population health. IHME collaborated with the Harvard School of Public Health, Johns Hopkins Bloomberg School of Public Health, the University of Queensland, the Research Institute for Tropical Medicine (the Philippines), the George Institute (India), King George Medical College (India), the Pemba Public Health Laboratory (Tanzania), and the Muhimbili University of Health and Allied Sciences (Tanzania) to collect over 12,500 gold standard verbal autopsies in multiple cultural and linguistic settings.

In order to validate verbal autopsy analysis methods, data were collected in hospital and clinical environments for decedents with known causes of death. The Consortium developed a list of stringent gold standard definitions for each cause of death, detailing the diagnostic criteria required to qualify for the study. Cases that met the criteria were followed with blinded VA interviews with a relative of the deceased. The VA questionnaire was used to collect information about the symptoms of the deceased, demographic characteristics, possible risk factors (such as tobacco use), and other potentially contributing characteristics.

The most commonly used approach to analyzing VA data is physician review. However, this approach can prove both time-consuming and costly. All of the gold standard cases collected as part of the PHMRC have been physician-reviewed to provide a comparison to the current standard procedures in the field. In parallel with collecting the results of the physician coding, we have been testing a suite of different methods. Three of them were previously in existence: InterVA (a program that incorporates commonly applied physician decision points by coding them into algorithms), the King-Lu method (previously developed by the PHMRC), and the Symptom Pattern Method (also previously developed by the PHMRC). In addition, we have developed a number of other methods that utilize either a tariff or a machine learning approach.

The tariff and machine learning methods outperform physician review and offer an analysis solution that is more cost-effective and less time-consuming than physician review, which could in turn result in more timely and accessible cause of death data in resource-poor settings.

Analyze community verbal autopsy data

Multiple projects, including the PHMRC and the Improving Methods to Measure Comparable Mortality by Cause project, have collected community verbal autopsies in Bangladesh, India, Mexico, Papua New Guinea, the Philippines, Sri Lanka, and Tanzania. The research team has applied multiple existing and recently developed methods to these datasets to produce population-level cause of death estimates for these sites.

Scientific publications

April 19, 2018
Performance of InSilicoVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards
Research Article
We perform a standard procedure for analyzing the predictive accuracy of verbal autopsy classification methods using the same data and the publicly available implementation of the algorithm released by the authors. We extend the original analysis to include children and neonates, instead of only adults, and test accuracy using different sets of predictors, including the set used in the original paper and a set that matches the released software.
December 15, 2015
A shortened verbal autopsy instrument for use in routine mortality surveillance systems
Research Article
Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. In this paper we describe a shortened version of the VA instrument developed for the Population Health Metrics Research Consortium Gold Standard Verbal Autopsy Validation Study using a systematic approach.
December 8, 2015
Improving performance of the Tariff Method for assigning causes of death to verbal autopsies
Research Article
In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium to ascertain causes of death from VA information. We describe the further development of the Tariff Method.
January 9, 2014
Using verbal autopsy to measure causes of death: the comparative performance of existing methods
Research Article
Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability.
August 31, 2011
Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies
Research Article
Choosing the best method for verbal autopsy (VA) requires the appropriate metrics to assess a given method’s performance, and researchers from IHME and the University of Queensland undertook a study to determine these metrics.
August 31, 2011
Assessing quality of medical death certification: concordance between gold standard diagnoses and underlying cause of death in selected Mexican hospitals
Research Article
The vital registration system in Mexico relies on information collected from death certificates to generate official mortality figures. A study by researchers at IHME and the National Institute of Public Health in Mexico set out to test the validity of this system.
August 31, 2011
Random forests for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards
Research Article
An innovative method of computer-coded verbal autopsy, the Random Forest (RF) Method from machine learning, was found to outperform physician-certified verbal autopsy (PCVA) in almost all settings, according to a study by researchers from IHME and the Bill & Melinda Gates Foundation as part of the Population Health Metrics Research Consortium (PHMRC).
August 31, 2011
Performance of InterVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards
Research Article
InterVA, an automated and widely available tool for assigning cause of death using verbal autopsies (VAs), does not perform as well as other methods, such as physician-certified verbal autopsy (PCVA) and the Simplified Symptom Pattern (SSP) method, according to a study published by researchers at IHME and the University of Queensland, as part of the Population Health Metrics Research Consortium (PHMRC).
August 31, 2011
Direct estimation of cause-specific mortality fractions from verbal autopsies: multisite validation study using clinical diagnostic gold standards
Research Article
The King and Lu (KL) method for directly estimating the fraction of all deaths in a population due to a given cause has been used to interpret verbal autopsies (VAs) in areas with incomplete vital registration systems.
August 31, 2011
Performance of physician-certified verbal autopsies: multisite validation study using clinical diagnostic gold standards
Research Article
Physician certification is the most widely used method for interpreting verbal autopsy (VA), yet physicians correctly determine cause of death less than half of the time, according to new research by IHME and the University of Queensland as part of the Population Health Metrics Research Consortium (PHMRC).
August 31, 2011
Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets
Research Article
The creation of the first strictly defined gold standard database of diagnoses for causes of death will help strengthen verbal autopsy (VA) methods in low-resource settings, according to a study published by a global group of researchers, the Population Health Metrics Research Consortium (PHMRC), which includes researchers from IHME.
August 31, 2011
Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies.
Research Article
The Tariff method, an easy-to-use tool developed by researchers at IHME for turning verbal autopsy (VA) results into meaningful cause of death data for health workers and policymakers, is capable of outperforming the more costly physician-certified verbal autopsy (PCVA) approach in most cases, according to new research by IHME as part of the Population Health Metrics Research Consortium (PHMRC).
August 31, 2011
Simplified Symptom Pattern Method for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards
Research Article
New research from IHME, the Department of Health Services at the University of Washington, and the University of Queensland as part of the Population Health Metrics Research Consortium (PHMRC) shows that the Simplified Symptom Pattern (SSP) method can be used to accurately interpret verbal autopsies (VAs).
July 27, 2011
Verbal autopsy: innovations, applications, opportunities
Research Article
“Verbal autopsy: innovations, applications, opportunities” is a collection of the most up-to-date research to help decision-makers choose the best and most cost-effective techniques to identify causes of death in their populations.
November 20, 2007
Validation of the symptom pattern method for analyzing verbal autopsy data
Research Article
Research published in PLoS Medicine  in November 2007 validated a novel method for analyzing verbal autopsy data (the symptom pattern method, developed at IHME) and found that this method outperformed another common verbal autopsy analytical method (physician-coded verbal autopsy, or PCVA).