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

BMC Pregnancy and Childbirth

Research Article

J. Frederik Frøen¹  A. Metin Gülmezoglu²  Ӧzge Tunçalp²  Emma Allanson³  Fleurisca Korteweg⁴  Alexander E. P. Heazell⁵  Elizabeth M. McClure⁶  Sanne Gordijn⁷  Jan Jaap Erwich⁷  Joy Lawn⁸  Hannah Blencowe⁸  Zheyi Teoh⁹  Vicki Flenady^1,10  Hanna Reinebrant^1,10  Aleena M. Wojcieszek^1,10  Susannah Hopkins Leisher^1,10  Gordon C. S. Smith^1,11  Jason Gardosi^1,12  Robert Pattinson^1,13 

[1] Department of International Public Health, Norwegian Institute of Public Health, Oslo, Norway;Center for Intervention Science for Maternal and Child Health, University of Bergen, Bergen, Norway;Department of Reproductive Health and Research including UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), World Health Organization, Geneva, Switzerland;Department of Reproductive Health and Research including UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), World Health Organization, Geneva, Switzerland;School of Women’s and Infants’ Health, Faculty of Medicine, Dentistry and Health Sciences, University of Western Australia, Perth, Australia;International Stillbirth Alliance, Millburn, USA;Department of Obstetrics and Gynaecology, Martini Hospital, Groningen, The Netherlands;International Stillbirth Alliance, Millburn, USA;Maternal and Fetal Health Research Centre, University of Manchester, Manchester, UK;St. Mary’s Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK;International Stillbirth Alliance, Millburn, USA;Research Triangle Institute, North Carolina, USA;International Stillbirth Alliance, Millburn, USA;University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands;London School of Hygiene & Tropical Medicine, London, UK;Mater Research Institute, The University of Queensland (MRI-UQ), Brisbane, Australia;Mater Research Institute, The University of Queensland (MRI-UQ), Brisbane, Australia;International Stillbirth Alliance, Millburn, USA;NIHR Biomedical Research Centre & Department of Obstetrics & Gynaecology, Cambridge University, Cambridge, UK;Perinatal Institute, Birmingham, UK;South Africa Medical Research Council Maternal and Infant Health Care Strategies Unit, University of Pretoria, Pretoria, South Africa;

关键词: Stillbirth;    Neonatal death;    Perinatal death;    Classification;    Classification system;    Cause;   

DOI  :  10.1186/s12884-016-1040-7

 received in 2015-10-02, accepted in 2016-08-11,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundTo 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.MethodsEighty-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.ResultsNone 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 %).ConclusionsThere 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.

【 授权许可】

CC BY   
© The Author(s). 2016