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1.
Popul Health Metr ; 19(1): 25, 2021 05 04.
Article in English | MEDLINE | ID: mdl-33947434

ABSTRACT

BACKGROUND: Most deaths in China occur at home, making it difficult to collect reliable cause of death (CoD) information. Verbal autopsy (VA) was applied using the SmartVA tool to a sample of home deaths in China to explore its feasibility as a means of improving the quality of CoD data. METHODS: The study was carried out in 22 districts in 9 provinces, located in north-east, central, and western areas of China during 2017 and 2018. Trained interviewers selected suitable respondents in each household to collect information using the Population Health Metrics Research Consortium (PHMRC) shortened and validated electronic VA questionnaire on tablets. The CoD was diagnosed from the interview data using the SmartVA-Analyze 2.0 software (Tariff 2.0). RESULTS: Non-communicable diseases (NCDs) dominated the leading causes of death in all age groups and for both sexes. After redistribution of undetermined causes, stroke (24%), ischemic heart diseases (IHD) (21%), chronic respiratory diseases (11%), and lung cancer (6%) were the leading causes of death. The cause fractions for level-one cause categories and ranking of specific causes were similar between SmartVA and results from the Global Burden of Disease (GBD) study. CONCLUSION: Evidence from this large pilot study suggests that SmartVA is a feasible and plausible tool and could be a valuable tool to improve the quality and standardization of CoD information across China.


Subject(s)
Hospitals , Autopsy , Cause of Death , China/epidemiology , Female , Humans , Male , Pilot Projects
2.
BMC Med ; 18(1): 74, 2020 03 09.
Article in English | MEDLINE | ID: mdl-32146900

ABSTRACT

BACKGROUND: Accurate and timely cause of death (COD) data are essential for informed public health policymaking. Medical certification of COD generally provides the majority of COD data in a population and is an essential component of civil registration and vital statistics (CRVS) systems. Accurate completion of the medical certificate of cause of death (MCCOD) should be a relatively straightforward procedure for physicians, but mistakes are common. Here, we present three training strategies implemented in five countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative at the University of Melbourne (UoM) and evaluate the impact on the quality of certification. METHODS: The three training strategies evaluated were (1) training of trainers (TOT) in the Philippines, Myanmar, and Sri Lanka; (2) direct training of physicians by the UoM D4H in Papua New Guinea (PNG); and (3) the implementation of an online and basic training strategy in Peru. The evaluation involved an assessment of MCCODs before and after training using an assessment tool developed by the University of Melbourne. RESULTS: The TOT strategy led to reductions in incorrectly completed certificates of between 28% in Sri Lanka and 40% in the Philippines. Following direct training of physicians in PNG, the reduction in incorrectly completed certificates was 30%. In Peru, the reduction in incorrect certificates was 30% after implementation and training on an online system only and 43% after training on both the online system and basic medical certification principles. CONCLUSIONS: The results of this study indicate that a variety of training strategies can produce benefits in the quality of certification, but further improvements are possible. The experiences of D4H suggest several aspects of the strategies that should be further developed to improve outcomes, particularly key stakeholder engagement from early in the intervention and local committees to oversee activities and support an improved culture in hospitals to support better diagnostic skills and practices.


Subject(s)
Cause of Death , Death Certificates , Vital Statistics , Data Accuracy , Education, Medical , Humans , Myanmar , Papua New Guinea , Peru , Philippines , Sri Lanka
3.
BMC Med ; 18(1): 67, 2020 03 09.
Article in English | MEDLINE | ID: mdl-32146901

ABSTRACT

BACKGROUND: Despite attempts to apply standard methods proven to work in high-income nations, nearly all civil registration and vital statistics (CRVS) systems in low- and middle-income countries are failing to achieve adequate levels of registration completeness or produce the high-quality vital statistics needed to support better health outcomes and monitor progress towards the 2030 Sustainable Development Goals. This suggests that, rather than simple technical issues, these countries are facing additional or different systemic challenges, including duplication of roles and responsibilities, inefficient methods of data collection, and a reluctance to change. APPLYING PROCESS MANAGEMENT: Process management is a valuable tool that strengthens the production of vital statistics by providing a visualisation of data flow from start to finish. It helps identify gaps and bottlenecks in the process, allowing stakeholders to work collaboratively to find solutions and target interventions. As part of the Bloomberg Philanthropies Data for Health Initiative at the University of Melbourne, 16 countries were supported in mapping the varied processes required in registering a birth or death. Comparative analysis exposed several limitations in the design of CRVS systems that hinder their performance - from 'passive' systems, to overly complex and fragmented system design, through to poor collaboration and duplication of efforts. CONCLUSIONS: The experiences from Myanmar, Papua New Guinea and Rwanda reported in this paper illustrate the benefits of process management to improve CRVS. While these three countries are at different stages of system development, each uniquely benefited. Process management is a useful tool for all CRVS systems, from the most rudimentary to the most developed. It can strengthen CRVS systems and improve the quality and completeness of vital statistics, resulting in more robust, reliable and timely vital statistics for health planning and better monitoring of the 2030 Sustainable Development Goal agenda.


Subject(s)
Data Accuracy , Vital Statistics , Data Collection , Humans , Income , Myanmar , Papua New Guinea , Registries/standards , Rwanda , Sustainable Development
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