Dataset Information

A composite metric for assessing data on mortality and causes of death: the vital statistics performance index.

ABSTRACT: BACKGROUND: Timely and reliable data on causes of death are fundamental for informed decision-making in the health sector as well as public health research. An in-depth understanding of the quality of data from vital statistics (VS) is therefore indispensable for health policymakers and researchers. We propose a summary index to objectively measure the performance of VS systems in generating reliable mortality data and apply it to the comprehensive cause of death database assembled for the Global Burden of Disease (GBD) 2013 Study. METHODS: We created a Vital Statistics Performance Index, a composite of six dimensions of VS strength, each assessed by a separate empirical indicator. The six dimensions include: quality of cause of death reporting, quality of age and sex reporting, internal consistency, completeness of death reporting, level of cause-specific detail, and data availability/timeliness. A simulation procedure was developed to combine indicators into a single index. This index was computed for all country-years of VS in the GBD 2013 cause of death database, yielding annual estimates of overall VS system performance for 148 countries or territories. RESULTS: The six dimensions impacted the accuracy of data to varying extents. VS performance declines more steeply with declining simulated completeness than for any other indicator. The amount of detail in the cause list reported has a concave relationship with overall data accuracy, but is an important driver of observed VS performance. Indicators of cause of death data quality and age/sex reporting have more linear relationships with simulated VS performance, but poor cause of death reporting influences observed VS performance more strongly. VS performance is steadily improving at an average rate of 2.10% per year among the 148 countries that have available data, but only 19.0% of global deaths post-2000 occurred in countries with well-performing VS systems. CONCLUSIONS: Objective and comparable information about the performance of VS systems and the utility of the data that they report will help to focus efforts to strengthen VS systems. Countries and the global health community alike need better intelligence about the accuracy of VS that are widely and often uncritically used in population health research and monitoring.

SUBMITTER: Phillips DE

PROVIDER: S-EPMC4060759 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A composite metric for assessing data on mortality and causes of death: the vital statistics performance index.

Phillips David E DE Lozano Rafael R Naghavi Mohsen M Atkinson Charles C Gonzalez-Medina Diego D Mikkelsen Lene L Murray Christopher Jl CJ Lopez Alan D AD

Population health metrics 20140514

<h4>Background</h4>Timely and reliable data on causes of death are fundamental for informed decision-making in the health sector as well as public health research. An in-depth understanding of the quality of data from vital statistics (VS) is therefore indispensable for health policymakers and researchers. We propose a summary index to objectively measure the performance of VS systems in generating reliable mortality data and apply it to the comprehensive cause of death database assembled for th ...[more]

PMID: 24982595

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Project description:BackgroundDetailed cause of death data by age group and sex are critical to identify key public health issues and target interventions appropriately. In this study the quality of local routinely collected cause of death data from medical certification is reviewed, and a cause of death profile for Tonga based on amended data is presented.MethodsMedical certificates of death for all deaths in Tonga for 2001 to 2008 and medical records for all deaths in the main island Tongatapu for 2008 were sought from the national hospital. Cause of death data for 2008 were reviewed for quality through (a) a review of current tabulation procedures and (b) a medical record review. Data from each medical record were extracted and provided to an independent medical doctor to assign cause of death, with underlying cause from the medical record tabulated against underlying cause from the medical certificate. Significant associations in reporting patterns were evaluated and final cause of death for each case in 2008 was assigned based on the best quality information from the medical certificate or medical record. Cause of death data from 2001 to 2007 were revised based on findings from the evaluation of certification of the 2008 data and added to the dataset. Proportional mortality was calculated and applied to age- and sex-specific mortality for all causes from 2001 to 2008. Cause of death was tabulated by age group and sex, and age-standardized (all ages) mortality rates for each sex by cause were calculated.ResultsReported tabulations of cause of death in Tonga are of immediate cause, with ischemic heart disease and diabetes underrepresented. In the majority of cases the reported (immediate) cause fell within the same broad category as the underlying cause of death from the medical certificate. Underlying cause of death from the medical certificate, attributed to neoplasms, diabetes, and cardiovascular disease were assigned to other underlying causes by the medical record review in 70% to 77% of deaths. Of the 28 (6.5%) deaths attributed to nonspecific or unknown causes on the medical certificate, 17 were able to be attributed elsewhere following review of the medical record. Final cause of death tabulations for 2001 to 2008 demonstrate that noncommunicable diseases are leading adult mortality, and age-standardized rates for cardiovascular diseases, neoplasms, and diabetes increased significantly between 2001 to 2004 and 2005 to 2008. Cause of death data for 2001 to 2008 show increasing cause-specific mortality (deaths per 100,000) from 2001-2004 to 2005-2008 from cardiovascular (194-382 to 423-644 in 2005-2008 for males and 108-227 to 194-321 for females) and other noncommunicable diseases that cannot be accounted for by changes in the age structure of the population. Mortality from diabetes for 2005 to 2008 is estimated at 94 to 222 deaths per 100,000 population for males and 98 to 190 for females (based on the range of plausible all-cause mortality estimates) compared with 2008 estimates from the global burden of disease study of 40 (males) and 53 (females) deaths per 100,000 population.DiscussionCertification of death was generally found to be the most reliable data on cause of death in Tonga available for Tonga, with 93% of the final assigned causes following review of the 2008 data matching those listed on the medical certificate of death. Cause of death data available in Tonga can be improved by routinely tabulating data by underlying cause and ensuring contributory causes are not recorded in Part I of the certificate during data entry to the database. There is significantly more data on cause of death available in Tonga than are routinely reported or known to international agencies.

Project description:Objectives: Both the National Vital Statistics System (NVSS) and the Fatality Analysis Reporting System (FARS) can be used to examine motor vehicle crash (MVC) deaths. These 2 data systems operate independently, using different methods to collect and code information about the type of vehicle (e.g., car, truck, bus) and road user (e.g., occupant, motorcyclist, pedestrian) involved in an MVC. A substantial proportion of MVC deaths in NVSS are coded as "unspecified" road user, which reduces the utility of the NVSS data for describing burden and identifying prevention measures. This study aimed to describe characteristics of unspecified road user deaths in NVSS to further our understanding of how these groups may be similar to occupant road user deaths. Methods: Using data from 1999 to 2015, we compared NVSS and FARS MVC death counts by road user type, overall and by age group, gender, and year. In addition, we examined factors associated with the categorization of an MVC death as unspecified road user such as state of residence of decedent, type of medical death investigation system, and place of death. Results: The number of MVC occupant deaths in NVSS was smaller than that in FARS in each year and the number of unspecified road user deaths in NVSS was greater than that in FARS. The sum of the number of occupant and unspecified road user deaths in NVSS, however, was approximately equal to the number of FARS occupant deaths. Age group and gender distributions were roughly equivalent for NVSS and FARS occupants and NVSS unspecified road users. Within NVSS, the number of MVC deaths listed as unspecified road user varied across states and over time. Other categories of road users (motorcyclists, pedal cyclists, and pedestrians) were consistent when comparing NVSS and FARS. Conclusions: Our findings suggest that the unspecified road user MVC deaths in NVSS look similar to those of MVC occupants according to selected characteristics. Additional study is needed to identify documentation and reporting challenges in individual states and over time and to identify opportunities for improvement in the coding of road user type in NVSS.

Project description:INTRODUCTION:The All Causes of Death Surveillance (ACDS) system was used to measure smoking-attributed mortality by inserting questions on smoking on death certificates. Smoking status information of the deceased has been routinely collected in death certificates since 2010. We describe a death registry-based case-control study using smoking and cause-of-death data for the period 2010-15. METHODS:From 2010, three questions about the smoking status of the deceased were inserted in a revised death certificate: 1) Smoking status (current smoker, quit smoking, never smoker); 2) Number of cigarettes per day smoked; and 3) Number of years of smoking. A data-accuracy survey of 1788 telephone interviews of the family of the deceased was also conducted. Smoking habits (current/ex-smoker vs non-smoker) were compared in study cases (persons who died of lung cancer and other diseases known to be caused by smoking) and the controls (never smokers). Multivariate logistic regression analysis was conducted to estimate relative risks, RR (odds ratios) for smoking-attributed mortality, for lung cancer and all causes of death related to smoking, adjusted for 5-year interval age groups, education, marital status, and year of death. RESULTS:During the study period (2010-15), the annual crude death reporting rates ranged from 6.5‰ to 7.0‰. The reporting rates of smoking status, smoking history and the number of cigarettes smoked daily were 95.5%, 98.6% and 98.6%, respectively. Compared to never smokers, the RR of ever smoking in males was 1.38 (95% CI: 1.33-1.43) for all causes of smoking-related deaths and 3.07 (95% CI: 2.91-3.24) for lung cancer, while in females the values were 1.46 (95% CI: 1.39-1.54) for all causes of smoking-related deaths and 4.07 (95% CI: 3.81-4.35) for lung cancer. The results in Tianjin are in accord with published results from previous studies. CONCLUSIONS:Levels and trends in smoking attributed mortality can be measured at low cost by using the stable, complete and effective ACDS system in Tianjin.

Dataset Information

A composite metric for assessing data on mortality and causes of death: the vital statistics performance index.

Publications

A composite metric for assessing data on mortality and causes of death: the vital statistics performance index.

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