Mpimbaza A., Filler S., Katureebe A., Quick L., Chandramohan D., Staedke S.G.
Child Health and Development Centre, College of Health Sciences, Makerere University, Kampala, Uganda; Infectious Diseases Research Collaboration, Kampala, Uganda; Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland; Centers for Disease Control and Prevention, Atlanta, GA, United States; London School of Hygiene and Tropical Medicine, London, United Kingdom
Mpimbaza, A., Child Health and Development Centre, College of Health Sciences, Makerere University, Kampala, Uganda, Infectious Diseases Research Collaboration, Kampala, Uganda; Filler, S., Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland; Katureebe, A., Infectious Diseases Research Collaboration, Kampala, Uganda; Quick, L., Centers for Disease Control and Prevention, Atlanta, GA, United States; Chandramohan, D., London School of Hygiene and Tropical Medicine, London, United Kingdom; Staedke, S.G., Infectious Diseases Research Collaboration, Kampala, Uganda, London School of Hygiene and Tropical Medicine, London, United Kingdom
To assess different methods for determining cause of death from verbal autopsy (VA) questionnaire data, the intra-rater reliability of Physician-Certified Verbal Autopsy (PCVA) and the accuracy of PCVA, expert-derived (non-hierarchical) and data-driven (hierarchal) algorithms were assessed for determining common causes of death in Ugandan children. A verbal autopsy validation study was conducted from 2008-2009 in three different sites in Uganda. The dataset included 104 neonatal deaths (0-27 days) and 615 childhood deaths (1-59 months) with the cause(s) of death classified by PCVA and physician review of hospital medical records (the 'reference standard'). Of the original 719 questionnaires, 141 (20%) were selected for a second review by the same physicians; the repeat cause(s) of death were compared to the original,and agreement assessed using the Kappa statistic.Physician reviewers' refined non-hierarchical algorithms for common causes of death from existing expert algorithms, from which, hierarchal algorithms were developed. The accuracy of PCVA, non-hierarchical, and hierarchical algorithms for determining cause(s) of death from all 719 VA questionnaires was determined using the reference standard. Overall, intra-rater repeatability was high (83% agreement, Kappa 0.79 [95% CI 0.76-0.82]). PCVA performed well, with high specificity for determining cause of neonatal (>67%), and childhood (>83%) deaths, resulting in fairly accurate cause-specific mortality fraction (CSMF) estimates. For most causes of death in children, non-hierarchical algorithms had higher sensitivity, but correspondingly lower specificity, than PCVA and hierarchical algorithms, resulting in inaccurate CSMF estimates. Hierarchical algorithms were specific for most causes of death, and CSMF estimates were comparable to the reference standard and PCVA. Inter-rater reliability of PCVA was high, and overall PCVA performed well. Hierarchical algorithms performed better than non-hierarchical algorithms due to higher specificity and more accurate CSMF estimates. Use of PCVA to determine cause of death from VA questionnaire data is reasonable while automated data-driven algorithms are improved. © 2015, Public Library of Science. All rights reserved. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
CDC, United States Agency for International Development; USAID, United States Agency for International Development