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D'Ambruoso L, Price J, Cowan E, Goosen G, Fottrell E, Herbst K, van der Merwe M, Sigudla J, Davies J, Kahn K. Refining circumstances of mortality categories (COMCAT): a verbal autopsy model connecting circumstances of deaths with outcomes for public health decision-making. Glob Health Action 2021; 14:2000091. [PMID: 35377291 PMCID: PMC8986216 DOI: 10.1080/16549716.2021.2000091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Recognising that the causes of over half the world's deaths pass unrecorded, the World Health Organization (WHO) leads development of Verbal Autopsy (VA): a method to understand causes of death in otherwise unregistered populations. Recently, VA has been developed for use outside research environments, supporting countries and communities to recognise and act on their own health priorities. We developed the Circumstances of Mortality Categories (COMCATs) system within VA to provide complementary circumstantial categorisations of deaths. OBJECTIVES Refine the COMCAT system to (a) support large-scale population assessment and (b) inform public health decision-making. METHODS We analysed VA data for 7,980 deaths from two South African Health and Socio-Demographic Surveillance Systems (HDSS) from 2012 to 2019: the Agincourt HDSS in Mpumalanga and the Africa Health Research Institute HDSS in KwaZulu-Natal. We assessed the COMCAT system's reliability (consistency over time and similar conditions), validity (the extent to which COMCATs capture a sufficient range of key circumstances and events at and around time of death) and relevance (for public health decision-making). RESULTS Plausible results were reliably produced, with 'emergencies', 'recognition, 'accessing care' and 'perceived quality' characterising the majority of avoidable deaths. We identified gaps and developed an additional COMCAT 'referral', which accounted for a significant proportion of deaths in sub-group analysis. To support decision-making, data that establish an impetus for action, that can be operationalised into interventions and that capture deaths outside facilities are important. CONCLUSIONS COMCAT is a pragmatic, scalable approach enhancing functionality of VA providing basic information, not available from other sources, on care seeking and utilisation at and around time of death. Continued development with stakeholders in health systems, civil registration, community and research environments will further strengthen the tool to capture social and health systems drivers of avoidable deaths and promote use in practice settings.
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Affiliation(s)
- Lucia D'Ambruoso
- Aberdeen Centre for Health Data Science (ACHDS), Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland.,Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden.,MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Public Healtlh, National Health Service (NHS), Scotland
| | - Jessica Price
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Eilidh Cowan
- Aberdeen Centre for Health Data Science (ACHDS), Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland.,School of Geosciences, College of Science and Engineering, University of Edinburgh, Scotland
| | | | | | - Kobus Herbst
- Africa Health Research Institute, Durban, South Africa.,DSI-MRC South African Population Research Infrastructure Network (SAPRIN), South Africa
| | - Maria van der Merwe
- Aberdeen Centre for Health Data Science (ACHDS), Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland.,MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Independent Consultant, South Africa
| | | | - Justine Davies
- Institute for Applied Health Research, University of Birmingham, UK
| | - Kathleen Kahn
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,International Network for the Demographic Evaluation of Populations and Their Health (Indepth), Accra, Ghana
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