Implementation of a modified obstetric early warning system to improve the quality of obstetric care in Zimbabwe

Abigail Merriel, Bobb Tariro Murove, Samuel Merriel, Thabani Sibanda, Sikangezile Moyo, Joanna Crofts

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
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Abstract

Objective: To implement the Modified Obstetric Early Warning System(MOEWS) to promote identification and stabilization of unwell women.

Methods: This before and after study of MOEWS implementation took place between April 2013 and January 2014, in a Government referral hospital in Zimbabwe. After piloting MOEWS, caesarean section case files were retrospectively assessed to ascertain pre-operative stabilization. A longitudinal ‘spot-check’ study, measured the use of MOEWS and action taken on abnormal results. A quality indicator was introduced to assess ongoing implementation. Results were analyzed using chi-squared and logistic regression techniques.

Results: The caesarean section study included 78 women before and 80 after MOEWS implementation. There was a significant improvement in pre-operative stabilization post-intervention(OR 2.78 95% CI 1.39, 5.54). The longitudinal study included 43 women at baseline and 85 post-implementation. A significant improvement was recorded in action taken after MOEWS (1/24(4.17%) vs 28/45(60%) p=0.001). The six-month aggregated quality indicator revealed 78/125(62%) completed MOEWS, with appropriate stabilization in 65/70(92.86%).

Conclusions: Implementation of MOEWS improved women’s care through action being taken on abnormal observations. Before whole-scale adoption of MOEWS in low resource settings, this study should be scaled up and repeated to ensure replicable findings.
Original languageEnglish
Pages (from-to)175-179
JournalInternational Journal of Gynecology & Obstetrics
Volume136
Issue number2
Early online date21 Nov 2016
DOIs
Publication statusPublished - Feb 2017

Keywords

  • Decision support tools
  • Early Warning Scores
  • Recognition of deteriorating patients
  • Maternal Health
  • Low-resource settings

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