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.

The Health Resources Allocation Model (HRAM) for the 21st century

The Health Resources Allocation Model (HRAM) is an eLearning tool for health cadres and scientists introducing basic concepts of sub-national, rational district-based health planning and systems thinking under resources constraint. HRAM allows the evaluation of resource allocation strategies in relation to key outcome measures such as coverage, equity of services achieved and number of deaths and disability-adjusted life years (DALYs) prevented. In addition, the model takes into account geographical and demographic characteristics and populations' health seeking behaviour. It can be adapted to different socio-ecological and health system settings.