Comparison of the Causes of Death Identified Using Automated Verbal Autopsy and Complete Autopsy among Brought-in-Dead Cases at a Tertiary Hospital in Sub-Sahara Africa

Author:

Yokobori Yuta12,Matsuura Jun1,Sugiura Yasuo1,Mutemba Charles34,Julius Peter35,Himwaze Cordelia35,Nyahoda Martin6,Mwango Chomba7,Kazhumbula Lloyd3,Yuasa Motoyuki2,Munkombwe Brian8,Mucheleng'anga Luchenga9

Affiliation:

1. National Center for Global Health and Medicine, Shinjuku-ku, Japan

2. Department of Public Health, Graduate School of Medicine, Juntendo University, Tokyo, Japan

3. Ministry of Health, Lusaka, Zambia

4. Adult Hospital, University Teaching Hospital, Lusaka, Zambia

5. Department of Pathology and Microbiology, School of Medicine, The University of Zambia, Lusaka, Zambia

6. Department of National Registration of Home Passport & Citizenship, Ministry Affairs, Lusaka, Zambia

7. Bloomberg Data for Health Initiative, Lusaka, Zambia

8. National Center for Health Statistics, Center for Disease Control and Prevention, Atlanta, United States

9. Office of the State Forensic Pathologist, Ministry of Home Affairs and Internal Security, Lusaka, Zambia

Abstract

Abstract Background Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated. Objectives To compare the CODs identified by automated VA with those by complete autopsy to examine the validity of a VA tool. Methods The study site was the tertiary hospital in the capital city of Zambia. From September 2019 to January 2020, all BID cases aged 13 years and older brought to the hospital during the daytime on weekdays were enrolled in this study. External COD cases were excluded. The deceased's relatives were interviewed using the 2016 World Health Organization VA questionnaire. The data were analyzed using InterVA, an automated VA tool, to determine the CODs, which were compared with the results of complete autopsies. Results A total of 63 cases were included. The CODs of 50 BID cases were determined by both InterVA and complete autopsies. The positive predictive value of InterVA was 22%. InterVA determined the CODs correctly in 100% cases of maternal CODs, 27.5% cases of noncommunicable disease CODs, and 5.3% cases of communicable disease CODs. Using the three broader disease groups, 56.0% cases were classified in the same groups by both methods. Conclusion While the positive predictive value was low, more than half of the cases were categorized into the same broader categories. However, there are several limitations in this study, including small sample size. More research is required to investigate the factors leading to discrepancies between the CODs determined by both methods to optimize the use of automated VA in Zambia.

Funder

NCGM Intramural research Fund

Publisher

Georg Thieme Verlag KG

Subject

Health Information Management,Computer Science Applications,Health Informatics

Reference47 articles.

1. Counting the dead and what they died from: an assessment of the global status of cause of death data;C D Mathers;Bull World Health Organ,2005

2. Civil registration systems and vital statistics: successes and missed opportunities;P Mahapatra;Lancet,2007

3. Gaps in the civil registration and vital statistics systems of low- and middle-income countries and the health sector's role in improving the situation;Y Yokobori;Glob Health Med,2021

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