Springer Nature

Classification systems for causes of stillbirth and neonatal death, 2009–2014: an assessment of alignment with characteristics for an effective global system

Posted on 2016-09-15 - 05:00
Abstract Background To reduce the burden of 5.3 million stillbirths and neonatal deaths annually, an understanding of causes of deaths is critical. A systematic review identified 81 systems for classification of causes of stillbirth (SB) and neonatal death (NND) between 2009 and 2014. The large number of systems hampers efforts to understand and prevent these deaths. This study aimed to assess the alignment of current classification systems with expert-identified characteristics for a globally effective classification system. Methods Eighty-one classification systems were assessed for alignment with 17 characteristics previously identified through expert consensus as necessary for an effective global system. Data were extracted independently by two authors. Systems were assessed against each characteristic and weighted and unweighted scores assigned to each. Subgroup analyses were undertaken by system use, setting, type of death included and type of characteristic. Results None of the 81 systems were aligned with more than 9 of the 17 characteristics; most (82 %) were aligned with four or fewer. On average, systems were aligned with 19 % of characteristics. The most aligned system (Frøen 2009-Codac) still had an unweighted score of only 9/17. Alignment with individual characteristics ranged from 0 to 49 %. Alignment was somewhat higher for widely used as compared to less used systems (22 % v 17 %), systems used only in high income countries as compared to only in low and middle income countries (20 % vs 16 %), and systems including both SB and NND (23 %) as compared to NND-only (15 %) and SB-only systems (13 %). Alignment was higher with characteristics assessing structure (23 %) than function (15 %). Conclusions There is an unmet need for a system exhibiting all the characteristics of a globally effective system as defined by experts in the use of systems, as none of the 81 contemporary classification systems assessed was highly aligned with these characteristics. A particular concern in terms of global effectiveness is the lack of alignment with “ease of use” among all systems, including even the most-aligned. A system which meets the needs of users would have the potential to become the first truly globally effective classification system.


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Susannah Leisher
Zheyi Teoh
Hanna Reinebrant
Emma Allanson
Hannah Blencowe
Jan Erwich
J. Frøen
Jason Gardosi
Sanne Gordijn
A. Gülmezoglu
Alexander Heazell
Fleurisca Korteweg
Joy Lawn
Elizabeth McClure
Robert Pattinson
Gordon Smith
Ӧzge Tunçalp
Aleena Wojcieszek
Vicki Flenady
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