Assessing the policy utility of routine mortality statistics: a global classification of countries.

Objective: To evaluate the utility and quality of death registration data across countries. Methods: We compiled routine death and cause of death statistics data from 2015-2019 from national authorities. We estimated completeness of death registration using the Adair-Lopez empirical method. The quality of cause of death data was assessed by evaluating the assignment of usable causes of death among people younger than 80 years. We grouped data into nine policy utility categories based on data availability, registration completeness and diagnostic precision. Findings: Of an estimated 55 million global deaths in 2019, 70% of deaths were registered across 156 countries, but only 52% had medically certified causes and 42% of deaths were assigned a usable cause. In 54 countries, which are mostly high-income, there is complete and high-quality mortality data. In a further 29 countries, located across different regions, death registration is complete, but cause of death data quality remains suboptimal. Additionally, 37 countries possess functional death registration systems with cause of death data of poor to moderate quality. In 30 countries, death registration ranges from limited to nascent completeness, accompanied by poor or unavailable cause of death data. Furthermore, 38 countries lack accessible data altogether. Conclusion: By implementing more proactive death notification processes, expanding the use of digitized data collection platforms, streamlining data compilation procedures and improving data quality assessment, governments could enhance the policy utility of mortality data. Encouraging the routine application of automated verbal autopsy methods is crucial for accurately determining the causes of deaths occurring at home.

Comparative performance of national civil registration and vital statistics systems: a global assessment.

Objective: To assess the current state of the world's civil registration and vital statistics systems based on publicly available data and to propose strategic development pathways, including priority interventions, for countries at different levels of civil registration and vital statistics performance. Methods: We applied a performance assessment framework to publicly available data, using a composite indicator highly correlated with civil registration and vital statistics performance which we then adjusted for data incomparability and missing values. Findings: Globally, civil registration and vital statistics systems score on average 0.70 (0-1 scale), with substantial variations across countries and regions. Scores ranged from less than 0.50 in emerging systems to nearly 1.00 in the most developed systems. Approximately one fifth of the world's population live in the 43 countries with low system performance (< 0.477). Irrespective of system development, health sector indicators consistently scored lower than other determinants of civil registration and vital statistics performance. Conclusion: From our assessment, we provide three main recommendations for how the health sector can contribute to improving civil registration and vital statistics systems: (i) enhanced health sector engagement in birth and death notification; (ii) a more systematic approach to training cause of death diagnostics; and (iii) leadership in the implementation of verbal autopsy methods. Four different civil registration and vital statistics improvement pathways for countries at different levels of system development are proposed, that can constitute a blueprint for regional civil registration and vital statistics strengthening activities that countries can adapt and refine to suit their capabilities, resources, and particular challenges.

Global analysis of birth statistics from civil registration and vital statistics systems.

Objective: To assess civil registration and vital statistics completeness for births in World Health Organization's Member States and identify data completeness gaps. Methods: For the 194 Member States, we sourced birth registration data from the United Nations Children's Fund database of national surveys, and, where available, vital registration reports. We acquired publicly available vital statistics compiled by national authorities. We determined civil registration completeness as the percentage of living children younger than five years whose births have been reported as registered. We evaluated vital statistics completeness against the United Nations World Population Prospects' live birth estimates, and grouped countries into seven categories based on their civil registration and vital statistics completeness. Findings: Globally, civil registration completeness for births was 77%, exceeding vital statistics completeness for births at 63%. Twenty countries had limited civil registration (25% to 74% completeness) and had nascent or no vital statistics data (completeness < 25%) for births. Five countries had nascent or no civil registration and vital statistics for births. Twenty countries had functional civil registration (75% to 94% completeness) but nascent or no available vital statistics. Approximately half (96) of the countries had complete civil registration and vital statistics for births, but contributed to only 22% of global births. Conclusion: The gap in completeness between civil registration data and vital statistics for births is most pronounced in countries with lower civil registration completeness. Enhancing data transfer processes for birth registration, along with targeted investments to elevate registration rates, is crucial for yielding comprehensive fertility statistics for governmental planning.

Improving the quality of external cause of death data in Brazil: evaluation and validation of a new form to investigate garbage codes.

Garbage codes, such as external causes with no specific information, indicate poor quality cause of death data. Investigation of garbage codes via an effective instrument is necessary to convert them into useful data for public health. This study analyzed the performance and suitability of the new investigation of deaths from external causes (IDEC) form to improve the quality of external cause of death data in Brazil. The performance of the IDEC form on 133 external garbage codes deaths was compared with a stratified matched sample of 992 (16%) investigated deaths that used the standard garbage codes form. Consistency between these two groups was checked. The percentage of garbage codes from external causes reclassified into valid causes with a 95% confidence interval (95%CI) was analyzed. Reclassification for specific causes has been described. Qualitative data on the feasibility of the form were recorded by field investigators. Investigation using the new form reduced all external garbage codes by -92.5% (95%CI: -97.0; -88.0), whereas the existing form decreased garbage codes by -60.5% (95%CI: -63.5; -57.4). The IDEC form presented higher effectivity for external-cause garbage codes of determined intent. Deaths that remained garbage codes mainly lacked information about the circumstances of poisoning and/or vehicle accidents. Despite the fact that field investigators considered the IDEC form feasible, they suggested modifications for further improvement. The new form was more effective than the current standard form in improving the quality of defined external causes.

Is training doctors in medical certification effective? Evidence from a prospective study in the Philippines.

BACKGROUND: Correct certification of causes of death by physicians according to International Classification of Diseases (ICD) rules is essential to generate mortality statistics of the quality needed to guide public health policy debates and reliably monitor the impact of health interventions. Several efforts to train doctors have been undertaken in the Philippines to improve Medical Certification of Causes of Death (MCCOD). However, there is very little evidence about the long-term effects of training interventions for medical certification. OBJECTIVE: To test whether there were measurable long-term impacts of this large-scale training intervention for improving medical certification and reducing different types of certification errors. METHOD: We assessed the quality of 2100 MCCOD completed before face-to-face training with those written by the same doctors 6 months after the training. An assessment tool was used to evaluate the quality of MCCOD. RESULTS: Less than 1% of the 2100 MCCOD assessed prior to the training were completely error-free, increasing to 19.2% 6 months after the training. On average, the number of errors per certificate fell from 2.2 pre-training to 1.3, six months after training. Importantly, there was a 38% decrease in writing ill-defined causes on the last line, which is particularly important for the policy utility of data. CONCLUSION: Training doctors in correct medical certification can have a long-term impact on medical certification practices. IMPLICATIONS: Shorter, more focused, trainings that address the most common medical certification errors could have an even greater impact on medical certification practices.

Improving the quality of external cause of death data in Brazil: evaluation and validation of a new form to investigate garbage codes / Melhorando a qualidade dos dados de causa externa de morte no Brasil: avaliação e validação de um novo formulário para investigar códigos garbage / Mejora en la calidad de los datos de causa externa de muerte en Brasil: evaluación y validación de un nuevo formulario para investigar códigos garbage

Garbage codes, such as external causes with no specific information, indicate poor quality cause of death data. Investigation of garbage codes via an effective instrument is necessary to convert them into useful data for public health. This study analyzed the performance and suitability of the new investigation of deaths from external causes (IDEC) form to improve the quality of external cause of death data in Brazil. The performance of the IDEC form on 133 external garbage codes deaths was compared with a stratified matched sample of 992 (16%) investigated deaths that used the standard garbage codes form. Consistency between these two groups was checked. The percentage of garbage codes from external causes reclassified into valid causes with a 95% confidence interval (95%CI) was analyzed. Reclassification for specific causes has been described. Qualitative data on the feasibility of the form were recorded by field investigators. Investigation using the new form reduced all external garbage codes by -92.5% (95%CI: -97.0; -88.0), whereas the existing form decreased garbage codes by -60.5% (95%CI: -63.5; -57.4). The IDEC form presented higher effectivity for external-cause garbage codes of determined intent. Deaths that remained garbage codes mainly lacked information about the circumstances of poisoning and/or vehicle accidents. Despite the fact that field investigators considered the IDEC form feasible, they suggested modifications for further improvement. The new form was more effective than the current standard form in improving the quality of defined external causes.

Códigos garbage (códigos inespecíficos ou incompletos), como causas externas sem informações específicas, indicam dados de má qualidade sobre a causa da morte. É necessário investigar os códigos garbage com um instrumento efetivo para convertê-los em dados úteis para a saúde pública. Este estudo analisou o desempenho e a adequação do novo formulário de investigação de óbitos por causas externas (IDEC) para melhorar a qualidade dos dados de causa externa de morte no Brasil. O desempenho deste formulário em 133 óbitos com códigos garbage de causas externas foi comparado com uma amostra estratificada e pareada de 992 (16%) óbitos investigados que utilizaram o formulário padrão de códigos garbage existente. A consistência entre esses dois grupos foi verificada. Analisou-se o percentual de códigos garbage de causas externas reclassificados em causas válidas com um intervalo de 95% de confiança (IC95%). A reclassificação para causas específicas foi descrita. Dados qualitativos sobre a viabilidade do formulário foram registrados por pesquisadores de campo. A investigação com o novo formulário reduziu todos os códigos garbage de causas externas em -92,5% (IC95%: -97,0; -88,0) enquanto o formulário existente diminuiu os códigos garbage em -60,5% (IC95%: -63,5; -57,4). O formulário IDEC foi mais eficaz para os códigos garbage de causa externa sem intenção indeterminada. As mortes que permaneceram como códigos garbage careciam principalmente de informações detalhadas sobre as circunstâncias do envenenamento e dos acidentes de trânsito. O formulário IDEC foi considerado viável pelos investigadores de campo, no entanto, eles sugeriram modificações para um maior aperfeiçoamento. O novo formulário foi mais eficaz do que o formulário padrão atual na melhoria da qualidade das causas externas definidas.

Códigos garbage (códigos inespecíficos o incompletos), como causas externas inespecíficas, son los indicadores de datos de mala calidad sobre la causa de muerte. Es necesario investigar los códigos garbage con un instrumento eficaz para convertirlos en datos útiles para la salud pública. Este estudio analizó el desempeño y la adecuación del nuevo formulario de investigación de muertes por causas externas (IDEC) para mejorar la calidad de los datos de causa externa de muerte en Brasil. El desempeño de este formulario en 133 muertes con códigos garbage de causas externas se comparó con una muestra estratificada y emparejada de 992 (16%) muertes investigadas que usaron el formulario estándar de códigos garbage existente. Se comprobó la consistencia entre estos dos grupos. Se analizó el porcentaje de códigos garbage por causas externas reclasificados en causas válidas con un intervalo del 95% de confianza (IC95%). Se procedió a una reclasificación por causas específicas. Los datos cualitativos sobre la viabilidad del formulario fueron registrados por investigadores de campo. La investigación con el nuevo formulario tuvo una reducción de todos los códigos garbage de causas externas en -92,5% (IC95%: -97,0; -88,0), mientras que el formulario existente redujo todos los códigos garbage de causas externas en -60,5% (IC95%: -63,5; -57,4). El formulario IDEC fue el más efectivo para códigos garbage de causa externa sin intención indeterminada. Las muertes que quedaron como códigos garbage carecían principalmente de información detallada sobre las circunstancias de envenenamiento y de accidentes de tránsito. Los investigadores de campo confirmaron la viabilidad del formulario IDEC, además de sugerir modificaciones para mejorarlo. El nuevo formulario fue el más efectivo que el formulario estándar actual en cuanto a la mejora de la calidad de las causas externas definidas.

The impact of errors in medical certification on the accuracy of the underlying cause of death.

BACKGROUND: Correct certification of cause of death by physicians (i.e. completing the medical certificate of cause of death or MCCOD) and correct coding according to International Classification of Diseases (ICD) rules are essential to produce quality mortality statistics to inform health policy. Despite clear guidelines, errors in medical certification are common. This study objectively measures the impact of different medical certification errors upon the selection of the underlying cause of death. METHODS: A sample of 1592 error-free MCCODs were selected from the 2017 United States multiple cause of death data. The ten most common types of errors in completing the MCCOD (according to published studies) were individually simulated on the error-free MCCODs. After each simulation, the MCCODs were coded using Iris automated mortality coding software. Chance-corrected concordance (CCC) was used to measure the impact of certification errors on the underlying cause of death. Weights for each error type and Socio-demographic Index (SDI) group (representing different mortality conditions) were calculated from the CCC and categorised (very high, high, medium and low) to describe their effect on cause of death accuracy. FINDINGS: The only very high impact error type was reporting an ill-defined condition as the underlying cause of death. High impact errors were found to be reporting competing causes in Part 1 [of the death certificate] and illegibility, with medium impact errors being reporting underlying cause in Part 2 [of the death certificate], incorrect or absent time intervals and reporting contributory causes in Part 1, and low impact errors comprising multiple causes per line and incorrect sequence. There was only small difference in error importance between SDI groups. CONCLUSIONS: Reporting an ill-defined condition as the underlying cause of death can seriously affect the coding outcome, while other certification errors were mitigated through the correct application of mortality coding rules. Training of physicians in not reporting ill-defined conditions on the MCCOD and mortality coders in correct coding practices and using Iris should be important components of national strategies to improve cause of death data quality.

Integrating community-based verbal autopsy into civil registration and vital statistics: lessons learnt from five countries.

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.

Are there sex differences in completeness of death registration and quality of cause of death statistics? Results from a global analysis.

INTRODUCTION: Recent studies suggest that more male than female deaths are registered and a higher proportion of female deaths are certified as 'garbage' causes (ie, vague or ill-defined causes of limited policy value). This can reduce the utility of sex-specific mortality statistics for governments to address health problems. To assess whether there are sex differences in completeness and quality of data from civil registration and vital statistics systems, we analysed available global death registration and cause of death data. METHODS: Completeness of death registration for females and males was compared in 112 countries, and in subsets of countries with incomplete death registration. For 64 countries with medical certificate of cause of death data, the level, severity and type of garbage causes was compared between females and males, standardised for the older age distribution and different cause composition of female compared with male deaths. RESULTS: For 42 countries with completeness of less than 95% (both sexes), average female completeness was 1.2 percentage points (p.p.) lower (95% uncertainty interval (UI) -2.5 to -0.2 p.p.) than for males. Aggregate female completeness for these countries was 7.1 p.p. lower (95% UI -12.2 to -2.0 p.p.; female 72.9%, male 80.1%), due to much higher male completeness in nine countries including India. Garbage causes were higher for females than males in 58 of 64 countries (statistically significant in 48 countries), but only by an average 1.4 p.p. (1.3-1.6 p.p.); results were consistent by severity and type of garbage. CONCLUSION: Although in most countries analysed there was no clear bias against females in death registration, there was clear evidence in a few countries of systematic undercounting of female deaths which substantially reduces the utility of mortality data. In countries with cause of death data, it was only of marginally poorer quality for females than males.

Improving the Policy Utility of Cause of Death Statistics in Sri Lanka: An Empirical Investigation of Causes of Out-of-Hospital Deaths Using Automated Verbal Autopsy Methods.

Background: Setting public health policies and effectively monitoring the impact of health interventions requires accurate, timely and complete cause of death (CoD) data for populations. In Sri Lanka, almost half of all deaths occur outside hospitals, with questionable diagnostic accuracy, thus limiting their information content for policy. Objectives: To ascertain whether SmartVA is applicable in improving the specificity of cause of death data for out-of-hospital deaths in Sri Lanka, and hence enhance the value of these routinely collected data for informing public policy debates. Methods: SmartVA was applied to 2610 VAs collected between January 2017 and March 2019 in 22 health-unit-areas clustered in six districts. Around 350 community-health-workers and 50 supervisory-staffs were trained. The resulting distribution of Cause-Specific-Mortality-Fractions (CSMFs) was compared to data from the Registrar-General's-Department (RGD) for out-of-hospital deaths for the same areas, and to the Global-Burden-of-Disease (GBD) estimates for Sri Lanka. Results: Using SmartVA, for only 15% of deaths could a specific-cause not be assigned, compared with around 40% of out-of-hospital deaths currently assigned garbage codes with "very high" or "high" severity. Stroke (M: 31.6%, F: 35.4%), Ischaemic Heart Disease (M: 13.5%, F: 13.0%) and Chronic Respiratory Diseases (M: 15.4%, F: 10.8%) were identified as the three leading causes of home deaths, consistent with the ranking of GBD-Study for Sri Lanka for all deaths, but with a notably higher CSMF for stroke. Conclusions: SmartVA showed greater diagnostic specificity, applicability, acceptability in the Sri Lankan context. Policy formulation in Sri Lanka would benefit substantially with national-wide implementation of VAs.

Effectiveness of training interventions to improve quality of medical certification of cause of death: systematic review and meta-analysis.

BACKGROUND: Valid cause of death data are essential for health policy formation. The quality of medical certification of cause of death (MCCOD) by physicians directly affects the utility of cause of death data for public policy and hospital management. Whilst training in correct certification has been provided for physicians and medical students, the impact of training is often unknown. This study was conducted to systematically review and meta-analyse the effectiveness of training interventions to improve the quality of MCCOD. METHODS: This review was registered in the International Prospective Register of Systematic Reviews (PROSPERO; Registration ID: CRD42020172547) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. CENTRAL, Ovid MEDLINE and Ovid EMBASE databases were searched using pre-defined search strategies covering the eligibility criteria. Studies were selected using four screening questions using the Distiller-SR software. Risk of bias assessments were conducted with GRADE recommendations and ROBINS-I criteria for randomised and non-randomised interventions, respectively. Study selection, data extraction and bias assessments were performed independently by two reviewers with a third reviewer to resolve conflicts. Clinical, methodological and statistical heterogeneity assessments were conducted. Meta-analyses were performed with Review Manager 5.4 software using the 'generic inverse variance method' with risk difference as the pooled estimate. A 'summary of findings' table was prepared using the 'GRADEproGDT' online tool. Sensitivity analyses and narrative synthesis of the findings were also performed. RESULTS: After de-duplication, 616 articles were identified and 21 subsequently selected for synthesis of findings; four underwent meta-analysis. The meta-analyses indicated that selected training interventions significantly reduced error rates among participants, with pooled risk differences of 15-33%. Robustness was identified with the sensitivity analyses. The findings of the narrative synthesis were similarly suggestive of favourable outcomes for both physicians and medical trainees. CONCLUSIONS: Training physicians in correct certification improves the accuracy and policy utility of cause of death data. Investment in MCCOD training activities should be considered as a key component of strategies to improve vital registration systems given the potential of such training to substantially improve the quality of cause of death data.

Are cause of death data fit for purpose? evidence from 20 countries at different levels of socio-economic development.

BACKGROUND AND OBJECTIVE: Many countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country's level of socio-economic development. METHODS: We have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country's mortality surveillance system. FINDINGS: The proportion of 'garbage codes' varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not. CONCLUSIONS: There is an inverse relationship between a country's socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

Improving medical certification of cause of death: effective strategies and approaches based on experiences from the Data for Health Initiative.

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.

ANACONDA: a new tool to improve mortality and cause of death data.

BACKGROUND: The need to monitor the Sustainable Development Goals (SDGs) and to have access to reliable and timely mortality data has created a strong demand in countries for tools that can assist them in this. ANACONDA (Analysis of National Causes of Death for Action) is a new tool developed for this purpose which allows countries to assess how accurate their mortality and cause of death are. Applying ANACONDA will increase confidence and capacity among data custodians in countries about their mortality data and will give them insight into quality problems that will assist the improvement process. METHODS: ANACONDA builds on established epidemiological and demographic concepts to operationalise a series of 10 steps and numerous sub-steps to perform data checks. Extensive use is made of comparators to assess the plausibility of national mortality and cause of death statistics. The tool calculates a composite Vital Statistics Performance Index for Quality (VSPI(Q)) to measure how fit for purpose the data are. Extracts from analyses of country data are presented to show the types of outputs. RESULTS: Each of the 10 steps provides insight into how well the current data is describing different aspects of the mortality situation in the country, e.g. who dies of what, the completeness of the reporting, and the amount and types of unusable cause of death codes. It further identifies the exact codes that should not be used by the certifying physicians and their frequency, which makes it possible to institute a focused correction procedure. Finally, the VSPI(Q) allows periodic monitoring of data quality improvements and identifies priorities for action to strengthen the Civil Registration and Vital Statistics (CRVS) system. CONCLUSIONS: ANACONDA has demonstrated the potential to dramatically improve knowledge about disease patterns as well as the functioning of CRVS systems and has served as a platform for galvanising wider CRVS reforms in countries.

Assessing the quality of cause of death data in six high-income countries: Australia, Canada, Denmark, Germany, Japan and Switzerland.

OBJECTIVES: To assess the policy utility of national cause of death (COD) data of six high-income countries with highly developed health information systems. METHODS: National COD data sets from Australia, Canada, Denmark, Germany, Japan and Switzerland for 2015 or 2016 were assessed by applying the ANACONDA software tool. Levels, patterns and distributions of unusable and insufficiently specified "garbage" codes were analysed. RESULTS: The average proportion of unusable COD was 18% across the six countries, ranging from 14% in Australia and Canada to 25% in Japan. Insufficiently specified codes accounted for a further 8% of deaths, on average, varying from 6% in Switzerland to 11% in Japan. The most commonly used garbage codes were Other ill-defined and unspecified deaths (R99), Heart failure (I50.9) and Senility (R54). CONCLUSIONS: COD certification errors are common, even in countries with very advanced health information systems, greatly reducing the policy value of mortality data. All countries should routinely provide certification training for hospital interns and raise awareness among doctors of their public health responsibility to certify deaths correctly and usefully for public health policy.

Assessment of the quality of cause-of-death data in Greenland, 2006-2015.

Background: While the system of registration of mortality and cause of death (COD) in Greenland was established several decades ago, reporting procedures follow a complicated administrative process. Timely and reliable reporting on mortality and COD is of high importance for the usability of the collected data for research, health planning and decision making. Methods: COD data collected by the Chief Medical Office in Greenland from 2006 to 2015 (4490 registered deaths) were analysed with the software Analysis of National Causes of Death for Action (ANACONDA) v4.0. Unusable or insufficiently specified ICD codes are identified. The Vital Statistics Performance Index for Quality (VSPI(Q)) is estimated for the overall quality conclusions of the register's usability. Results: Sixty-eight per cent of the input data for Greenland was coded with a usable underlying COD, 24% with an unusable cause and 8% of deaths with an insufficiently specified cause. Almost 700 deaths were coded to an unusable code of 'very high impact'. The most prevalent unusable underlying causes were other ill-defined and unspecified causes, including no death certificate available, followed by senility, heart failure, sepsis and shock and cardiac arrest. The VSPI(Q) score was 66%, representing medium quality. Conclusions: In the 10 years' worth of data analysed, the true underlying COD in many cases was unknown. Several likely explanations for this include lack of systematic COD training for physicians, logistic and capacity challenges in Greenland that potentially could reduce the quality of the collected data and its usability in providing essential information about the true pattern of mortality in Greenland.