A novel use of a classification system to audit severe maternal morbidity
- Publication Type:
- Journal Article
- Midwifery, 2010, 26 (5), pp. 532 - 536
- Issue Date:
Objective: obstetric haemorrhage remains a significant cause of maternal morbidity and mortality worldwide and is significant in terms of patient safety and quality of care. One drastic outcome of haemorrhage is the need for peripartum hysterectomy. A classification system that can be used to audit severe events such as peripartum hysterectomy would be a useful adjunct to patient safety systems, but it would need to account for pre-existing risk factors, such as previous caesarean section. One system that accounts for important risk factors is the Robson Ten Group Classification System (TGCS). The aim of this study was to examine whether the TGCS could be extended in a novel way to classify who required peripartum hysterectomy. Setting: population-based matched case-control study data from the UK Obstetric Surveillance System was used. All eligible UK hospitals participated. Participants: women who underwent peripartum hysterectomy between February 2005 and February 2006 and their matched controls. Methods: cases and controls were categorised using the TGCS. The odds of having a peripartum hysterectomy in each classification group were calculated using logistic regression. An adjusted analysis was undertaken controlling for potential confounders. Findings: 307 of the 315 women who had a peripartum hysterectomy were classified into one of the 10 groups; 606 of the 608 control women were classified. Women who underwent a peripartum hysterectomy were predominantly from the more complex classification groups. After adjusting for age, ethnicity and socio-economic status, the groups with an increased odds of peripartum hysterectomy were those who had a previous caesarean section. Conclusions: the TGCS can be used in a novel way, that is, to examine an outcome other than caesarean section, and could be part of a new system to monitor patient safety. Population-based data were used as an example of how an existing classification system could be used in a different way from that for which it was created, and could make comparisons across institutions and countries while adjusting for case mix in a simple manner. The TGCS may not necessarily be a useful way to monitor other events in childbirth. Further work is needed to develop other classification systems which could be used as a benchmarking tools to monitor patient safety in maternity care. © 2010 Elsevier Ltd.
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