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Dandona R, Khan M. Engagement With Death Registration and Cause-of-Death Reporting to Strengthen Suicide Statistics. CRISIS 2024; 45:249-253. [PMID: 39138983 DOI: 10.1027/0227-5910/a000962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Affiliation(s)
- Rakhi Dandona
- Public Health Foundation of India, New Delhi, India
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Centre for Mental Health and Community Wellbeing, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Australia
| | - Murad Khan
- Department of Psychiatry and Brain and Mind Institute, Aga Khan University, Karachi, Pakistan
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Sainbayar A, Gombojav D, Lundeg G, Byambaa B, Meier J, Dünser MW, Mendsaikhan N. Out-of-hospital deaths in Mongolia: a nationwide cohort study on the proportion, causes, and potential impact of emergency and critical care services. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 39:100867. [PMID: 37927992 PMCID: PMC10625029 DOI: 10.1016/j.lanwpc.2023.100867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/30/2023] [Accepted: 07/17/2023] [Indexed: 11/07/2023]
Abstract
Background Little is known about the proportion and causes of out-of-hospital deaths in Mongolia. In this study, we aimed to determine the proportion and causes of out-of-hospital deaths in Mongolia during a six-month observation period before the COVID-19 pandemic. Methods In a retrospective study, the Mongolian National Death Registry was screened for all deaths occurring from 01 to 06/2020. The proportion and causes of out-of-hospital deaths, causes of out-of-hospital deaths likely treatable by emergency/critical care interventions, as well as sex, regional and seasonal differences in the proportion and causes of out-of-hospital deaths were determined. The primary endpoint was the proportion and causes of out-of-hospital death in children and adults. Descriptive statistical methods, the Fisher's Exact, multirow Chi2-or Mann-Whitney-U-rank sum tests were used for data analysis. Findings Five-thousand-five-hundred-fifty-three of 7762 deaths (71.5%) occurred outside of a hospital. The proportion of out-of-hospital deaths was lower in children than adults (39.3% vs. 74.8%, p < 0.001). Trauma, chronic neurological diseases, lower respiratory tract infections, congenital birth defects, and neonatal disorders were the causes of out-of-hospital deaths resulting in most years of life lost in children. In adults, chronic heart diseases, trauma, liver cancer, poisonings, and self-harm caused the highest burden of premature mortality. The proportion of out-of-hospital deaths did not differ between females and males (70.5% vs. 72.2%, p = 0.09). The proportion (all, p < 0.001; adults, p < 0.001; children, p < 0.001) and causes (adults, p < 0.001; children, p < 0.001) of out-of-hospital deaths differed between Mongolian regions and Ulaanbaatar. The proportion of out-of-hospital deaths was higher during winter than spring/summer months (72.3% vs. 69.9%, p = 0.03). An expert panel estimated that 49.3% of out-of-hospital deaths were likely treatable by emergency/critical care interventions. Interpretation With regional and seasonal variations, about 75% of Mongolian adults and 40% of Mongolian children died outside of a hospital. Heart diseases, trauma, cancer, and poisonings resulted in most years of life lost. About half of the causes of out-of-hospital deaths could be treated by emergency/critical care interventions. Funding Institutional funding.
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Affiliation(s)
- Altanchimeg Sainbayar
- Department of Critical Care and Anesthesia, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
- Intensive Care Unit, Mongolia Japan Hospital, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
| | - Davaa Gombojav
- Department of Epidemiology and Biostatistics, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
| | - Ganbold Lundeg
- Department of Critical Care and Anesthesia, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
- Intensive Care Unit, Mongolia Japan Hospital, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
| | - Boldbaatar Byambaa
- Department of Health Statistics, Centre for Health Development, Ulaanbaatar, Mongolia
| | - Jens Meier
- Department of Anesthesiology and Intensive Care Medicine, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Martin W. Dünser
- Department of Anesthesiology and Intensive Care Medicine, Kepler University Hospital and Johannes Kepler University, Linz, Austria
| | - Naranpurev Mendsaikhan
- Department of Critical Care and Anesthesia, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
- Intensive Care Unit, Mongolia Japan Hospital, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
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Mahesh BPK, Hart JD, Acharya A, Chowdhury HR, Joshi R, Adair T, Hazard RH. Validation studies of verbal autopsy methods: a systematic review. BMC Public Health 2022; 22:2215. [PMID: 36447199 PMCID: PMC9706899 DOI: 10.1186/s12889-022-14628-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 11/14/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Verbal autopsy (VA) has emerged as an increasingly popular technique to assign cause of death in parts of the world where the majority of deaths occur without proper medical certification. The purpose of this study was to examine the key characteristics of studies that have attempted to validate VA cause of death against an established cause of death. METHODS A systematic review was conducted by searching the MEDLINE, EMBASE, Cochrane-library, and Scopus electronic databases. Included studies contained 1) a VA component, 2) a validation component, and 3) original analysis or re-analysis. Characteristics of VA studies were extracted. A total of 527 studies were assessed, and 481 studies screened to give 66 studies selected for data extraction. RESULTS Sixty-six studies were included from multiple countries. Ten studies used an existing database. Sixteen studies used the World Health Organization VA questionnaire and 5 studies used the Population Health Metrics Research Consortium VA questionnaire. Physician certification was used in 36 studies and computer coded methods were used in 14 studies. Thirty-seven studies used high level comparator data with detailed laboratory investigations. CONCLUSION Most studies found VA to be an effective cause of death assignment method and compared VA cause of death to a high-quality established cause of death. Nonetheless, there were inconsistencies in the methodologies of the validation studies, and many used poor quality comparison cause of death data. Future VA validation studies should adhere to consistent methodological criteria so that policymakers can easily interpret the findings to select the most appropriate VA method. PROSPERO REGISTRATION CRD42020186886.
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Affiliation(s)
- Buddhika P. K. Mahesh
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - John D. Hart
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Ajay Acharya
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Hafizur Rahman Chowdhury
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Rohina Joshi
- grid.464831.c0000 0004 8496 8261The George Institute for Global Health, New Delhi, India ,grid.1005.40000 0004 4902 0432School of Population Health, University of New South Wales, Sydney, Australia
| | - Tim Adair
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Riley H. Hazard
- grid.1008.90000 0001 2179 088XMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
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Chen L, Xia T, Rampatige R, Li H, Adair T, Joshi R, Gu Z, Yu H, Fang B, McLaughlin D, Lopez AD, Wang C, Yuan Z. Assessing the Diagnostic Accuracy of Physicians for Home Death Certification in Shanghai: Application of SmartVA. Front Public Health 2022; 10:842880. [PMID: 35784257 PMCID: PMC9247331 DOI: 10.3389/fpubh.2022.842880] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
Approximately 30% of deaths in Shanghai either occur at home or are not medically attended. The recorded cause of death (COD) in these cases may not be reliable. We applied the Smart Verbal Autopsy (VA) tool to assign the COD for a representative sample of home deaths certified by 16 community health centers (CHCs) from three districts in Shanghai, from December 2017 to June 2018. The results were compared with diagnoses from routine practice to ascertain the added value of using SmartVA. Overall, cause-specific mortality fraction (CSMF) accuracy improved from 0.93 (93%) to 0.96 after the application of SmartVA. A comparison with a “gold standard (GS)” diagnoses obtained from a parallel medical record review investigation found that 86.3% of the initial diagnoses made by the CHCs were assigned the correct COD, increasing to 90.5% after the application of SmartVA. We conclude that routine application of SmartVA is not indicated for general use in CHCs, although the tool did improve diagnostic accuracy for residual causes, such as other or ill-defined cancers and non-communicable diseases.
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Affiliation(s)
- Lei Chen
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Tian Xia
- Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Rasika Rampatige
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Hang Li
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Tim Adair
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Rohina Joshi
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
- Faculty of Medicine, The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
- The George Institute for Global Health, New Delhi, India
| | - Zhen Gu
- Vital Strategies, New York, NY, United States
| | - Huiting Yu
- Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Bo Fang
- Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Deirdre McLaughlin
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Alan D. Lopez
- Department of Health Metrics Sciences, IHME, University of Washington, Seattle, WA, United States
| | - Chunfang Wang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Zheng'an Yuan
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- *Correspondence: Zheng'an Yuan
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Firth SM, Hart JD, Reeve M, Li H, Mikkelsen L, Sarmiento DC, Bo KS, Kwa V, Qi JL, Yin P, Segarra A, Riley I, Joshi R. Integrating community-based verbal autopsy into civil registration and vital statistics: lessons learnt from five countries. BMJ Glob Health 2021; 6:bmjgh-2021-006760. [PMID: 34728477 PMCID: PMC8565529 DOI: 10.1136/bmjgh-2021-006760] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/12/2021] [Indexed: 01/09/2023] Open
Abstract
This paper describes the lessons from scaling up a verbal autopsy (VA) intervention to improve data about causes of death according to a nine-domain framework: governance, design, operations, human resources, financing, infrastructure, logistics, information technologies and data quality assurance. We use experiences from China, Myanmar, Papua New Guinea, Philippines and Solomon Islands to explore how VA has been successfully implemented in different contexts, to guide other countries in their VA implementation. The governance structure for VA implementation comprised a multidisciplinary team of technical experts, implementers and staff at different levels within ministries. A staged approach to VA implementation involved scoping and mapping of death registration processes, followed by pretest and pilot phases which allowed for redesign before a phased scale-up. Existing health workforce in countries were trained to conduct the VA interviews as part of their routine role. Costs included training and compensation for the VA interviewers, information technology (IT) infrastructure costs, advocacy and dissemination, which were borne by the funding agency in early stages of implementation. The complexity of the necessary infrastructure, logistics and IT support required for VA increased with scale-up. Quality assurance was built into the different phases of the implementation. VA as a source of cause of death data for community deaths will be needed for some time. With the right technical and political support, countries can scale up this intervention to ensure ongoing collection of quality and timely information on community deaths for use in health planning and better monitoring of national and global health goals.
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Affiliation(s)
- Sonja Margot Firth
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - John D Hart
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Matthew Reeve
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Hang Li
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lene Mikkelsen
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Khin Sandar Bo
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Viola Kwa
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jin-Lei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Agnes Segarra
- Epidemiological Bureau, Republic of the Philippines Department of Health, Manila, Philippines
| | - Ian Riley
- School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Rohina Joshi
- The George Institute for Global Health, Newtown, New South Wales, Australia,The George Institute for Global Health India, New Delhi, Delhi, India
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