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

Phillips DE, Lozano R, Naghavi M, Atkinson C, Gonzalez-Medina D, Mikkelsen L, Murray CJ, Lopez AD - Popul Health Metr (2014)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave. Suite 600, Seattle, WA 98121, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Simulated CSMF accuracy associated with each indicator by region. *Subtracted from one so that higher values are preferable to lower, as with other indicators.
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Figure 2: Simulated CSMF accuracy associated with each indicator by region. *Subtracted from one so that higher values are preferable to lower, as with other indicators.

Mentions: Hypothetical sets of CSMFs were computed at progressively worse levels of a given dimension, from zero (e.g., no unspecified ages or sexes) to one (e.g., all deaths reported without age or sex) in increments of 0.01. At each simulated level, CSMF Accuracy was computed based on CSMFpred and CSMFtrue. This procedure was repeated for each dimension separately. Due to the instability of CSMFs based on small death counts, CSMF Accuracy was observed to actually increase as a consequence of a worse level of a given dimension at extreme values. In such cases, the minimum CSMF Accuracy from higher levels of the same dimension was imposed to restrict CSMF Accuracy estimates from paradoxically increasing. FigureĀ 2 displays the CSMF Accuracy associated with varying levels of each indicator for each of the seven GBD regions as well as the global mean of all regions.


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

Phillips DE, Lozano R, Naghavi M, Atkinson C, Gonzalez-Medina D, Mikkelsen L, Murray CJ, Lopez AD - Popul Health Metr (2014)

Simulated CSMF accuracy associated with each indicator by region. *Subtracted from one so that higher values are preferable to lower, as with other indicators.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4060759&req=5

Figure 2: Simulated CSMF accuracy associated with each indicator by region. *Subtracted from one so that higher values are preferable to lower, as with other indicators.
Mentions: Hypothetical sets of CSMFs were computed at progressively worse levels of a given dimension, from zero (e.g., no unspecified ages or sexes) to one (e.g., all deaths reported without age or sex) in increments of 0.01. At each simulated level, CSMF Accuracy was computed based on CSMFpred and CSMFtrue. This procedure was repeated for each dimension separately. Due to the instability of CSMFs based on small death counts, CSMF Accuracy was observed to actually increase as a consequence of a worse level of a given dimension at extreme values. In such cases, the minimum CSMF Accuracy from higher levels of the same dimension was imposed to restrict CSMF Accuracy estimates from paradoxically increasing. FigureĀ 2 displays the CSMF Accuracy associated with varying levels of each indicator for each of the seven GBD regions as well as the global mean of all regions.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave. Suite 600, Seattle, WA 98121, USA.

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.

No MeSH data available.


Related in: MedlinePlus