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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., Competing Interests: The authors have declared that no competing interests exist.

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.

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.

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., Competing Interests: The authors have declared that no competing interests exist.

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.

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.

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.

Objective: To systematically review the reliability of hospital data on cause of death and encourage periodic reviews of these data using a standard method., Methods: We searched Google Scholar, Pubmed and Biblioteca Virtual de la Salud for articles in English, Spanish and Portuguese that reported validation studies of data on cause of death. We analysed the results of 199 studies that had used medical record reviews to validate the cause of death reported on death certificates or by the vital registration system., Findings: The screened studies had been published between 1983 and 2013 and their results had been reported in English (n = 124), Portuguese (n = 25) or Spanish (n = 50). Only 29 of the studies met our inclusion criteria. Of these, 13 had examined cause of death patterns at the population level - with a view to correcting cause-specific mortality fractions - while the other 16 had been undertaken to identify discrepancies in the diagnosis for specific diseases before and after medical record review. Most of the selected studies reported substantial misdiagnosis of causes of death in hospitals. There was wide variation in study methodologies. Many studies did not describe the methods used in sufficient detail to be able to assess the reproducibility or comparability of their results., Conclusion: The assumption that causes of death are being accurately reported in hospitals is unfounded. To improve the reliability and usefulness of reported causes of death, national governments should do periodic medical record reviews to validate the quality of their hospital cause of death data, using a standard.

Good public-health decisionmaking is dependent on reliable and timely statistics on births and deaths (including the medical causes of death). All high-income countries, without exception, have national civil registration systems that record these events and generate regular, frequent, and timely vital statistics. By contrast, these statistics are not available in many low-income and lower-middle-income countries, even though it is in such settings that premature mortality is most severe and the need for robust evidence to back decisionmaking most critical. Civil registration also has a range of benefits for individuals in terms of legal status, and the protection of economic, social, and human rights. However, over the past 30 years, the global health and development community has failed to provide the needed technical and financial support to countries to develop civil registration systems. There is no single blueprint for establishing and maintaining such systems and ensuring the availability of sound vital statistics. Each country faces a different set of challenges, and strategies must be tailored accordingly. There are steps that can be taken, however, and we propose an approach that couples the application of methods to generate better vital statistics in the short term with capacity-building for comprehensive civil registration systems in the long run.