Background: National vital registration systems are the principal source of cause specific mortality statistics, and require periodic validation to guide use of their outputs for health policy and programme purposes, and epidemiological research. We report results from a validation of cause of death statistics from health facilities in urban China.
Methods: 2917 deaths from health facilities located in six cities in China constituted the study sample. A reference diagnosis of the underlying cause was derived for each death, based on expert review of available medical records, and compared with that filed at registration. Sensitivity, specificity and positive predictive value were computed for specific causes/cause categories according to the International Classification of Diseases (ICD), including analyses based on quality of evidence scores for each cause. Patterns of misclassification by the registration system were studied for individual causes of death.
Results: The registration system had good sensitivity in diagnosing cerebrovascular disease and several site specific cancers (lung, liver, stomach, colorectal, breast and pancreas). Sensitivity was average (50-75%) for some major causes of adult death in China, namely ischaemic heart disease (IHD), chronic obstructive lung disease (COPD), diabetes, and liver and kidney diseases, with compensatory misclassification patterns observed between several of them. Sensitivity was particularly low for hypertensive disease.
Conclusions: Although diagnostic misclassification is not uncommon in urban death registration data, they appear to balance each other at the population level. Compensating misclassification errors suggest that caution is required when drawing conclusions about particular chronic causes of adult death in China. Investment is required to improve the quality of cause attribution for health facility deaths, and to assess the validity of cause attribution for home deaths. Periodic assessments of the quality of cause of death statistics will enhance their usability for health policy and epidemiological research.