Premium
Pitfalls of National Routine Death Statistics for Maternal Mortality Study
Author(s) -
Saucedo Monica,
BouvierColle MarieHélène,
Chantry Anne A.,
LamarcheVadel Agathe,
Rey Grégoire,
DeneuxTharaux Catherine
Publication year - 2014
Publication title -
paediatric and perinatal epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.667
H-Index - 88
eISSN - 1365-3016
pISSN - 0269-5022
DOI - 10.1111/ppe.12153
Subject(s) - medicine , statistics , maternal death , cause of death , health statistics , false positive paradox , demography , population , environmental health , disease , mathematics , sociology
Background The lessons learned from the study of maternal deaths depend on the accuracy of data. Our objective was to assess time trends in the underestimation of maternal mortality ( MM ) in the national routine death statistics in F rance and to evaluate their current accuracy for the selection and causes of maternal deaths. Methods National data obtained by enhanced methods in 1989, 1999, and 2007–09 were used as the gold standard to assess time trends in the underestimation of MM ratios ( MMR s) in death statistics. Enhanced data and death statistics for 2007–09 were further compared by characterising false negatives ( FN s) and false positives ( FP s). The distribution of cause‐specific MMR s, as assessed by each system, was described. Results Underestimation of MM in death statistics decreased from 55.6% in 1989 to 11.4% in 2007–09 ( P < 0.001). In 2007–09, of 787 pregnancy‐associated deaths, 254 were classified as maternal by the enhanced system and 211 by the death statistics; 34% of maternal deaths in the enhanced system were FN s in the death statistics, and 20% of maternal deaths in the death statistics were FP s. The hierarchy of causes of MM differed between the two systems. The discordances were mainly explained by the lack of precision in the drafting of death certificates by clinicians. Conclusion Although the underestimation of MM in routine death statistics has decreased substantially over time, one third of maternal deaths remain unidentified, and the main causes of death are incorrectly identified in these data. Defining relevant priorities in maternal health requires the use of enhanced methods for MM study.