| Literature DB >> 28874123 |
Signe Egenberg1, Gileard Masenga2, Lars Edvin Bru3, Torbjørn Moe Eggebø4,5, Cecilia Mushi2, Deodatus Massay6, Pål Øian7,8.
Abstract
BACKGROUND: Tanzania has a relatively high maternal mortality ratio of 410 per 100,000 live births. Severe postpartum hemorrhage (PPH) is a major cause of maternal deaths, but in most cases, it is preventable. However, most pregnant women that develop PPH, have no known risk factors. Therefore, preventive measures must be offered to all pregnant women. This study investigated the effects of multi-professional, scenario-based training on the prevention and management of PPH at a Tanzanian zonal consultant hospital. We hypothesized that scenario-based training could contribute to improved competence on PPH-management, which would result in improved team efficiency and patient outcome.Entities:
Keywords: Blood transfusion; Debriefing; Multi-professional; Postpartum hemorrhage; Scenario-based training; Teamwork
Mesh:
Year: 2017 PMID: 28874123 PMCID: PMC5584507 DOI: 10.1186/s12884-017-1478-2
Source DB: PubMed Journal: BMC Pregnancy Childbirth ISSN: 1471-2393 Impact factor: 3.007
Fig. 1Bimanual uterine compression displayed in the Helping Mothers Survive pamphlet, provided in the BAB learning materials from Jhpiego: Jhpiego.Helping Mothers Survive [www.helpingmotherssurvive.org]
Fig. 2Multi-professional scenario-based training on PPH at KCMC
Patient outcomes in random samples collected before (pre-training) and after (post-training) multi-professional, scenario-based training of the maternity staff
| Pre training (n = 1667) | Post training ( | p-value | |||
|---|---|---|---|---|---|
| Maternal and labor characteristics | |||||
| Maternal age (mean) | 27.9 | SD 6.5 | 27.9 | SD 6.2 | 0.48 |
| Multiple pregnancy | 54 | 3.2% | 67 | 4.1% | 0.19* |
| Antepartum hemorrhage | 19 | 1.1% | 33 | 2% | 0.04* |
| Preeclampsia | 42 | 2.5% | 84 | 5.1% | <0.01* |
| Malaria | 128 | 7.7% | 78 | 4.8% | <0.01* |
| Induced labor | 346 | 20.8% | 513 | 31.3% | <0.01* |
| Female genital mutilation and cutting | 216 | 13% | 192 | 11.7% | 0.31* |
| Transfers from another hospital during labor | 442 | 26.5% | 455 | 27.7% | 0.43* |
| Patient outcome | |||||
| Whole blood transfusions | 53 | 3.2% | 28 | 1.7% | <0.01* |
| Estimated blood loss, ml (mean) | 237 | SD 244 | 243 | SD 246 | 0.19 |
| Postpartum hemorrhage | 15 | 0.9% | 22 | 1.3% | 0.23* |
| Cesarean section | 570 | 34.2% | 669 | 40.8% | <0.01* |
| Vacuum delivery | 8 | 0.5% | 20 | 1.2% | 0.02* |
| Episiotomy | 27 | 1.6% | 19 | 1.2% | 0.26* |
| Child characteristics | |||||
| Gestational age, days (mean) | 282 | SD 15 | 283 | SD 13 | 0.46 |
| Birth weight, grams; 1st child (mean) | 3076 | SD 583 | 3126 | SD 600 | 0.01 |
| Apgar score < 7 after 5 min; 1st child (n) | 30 | 1.8% | 42 | 2.6% | 0.13* |
Values represent the number (%) or the mean (SD) of the indicated birth cohort. The p-values indicate differences between medians, obtained with the Mann-Whitney U test
*The chi-square test or Fisher’s exact test was used to test for differences between proportions
Results of logistic regression analysis show factors significantly related to the need (no/yes) for whole blood transfusions (dependent variable; n = 81)
| Independent variables | Unadjusted OR | (95% CI) | p-value | Adjusted OR | (95% CI) | p-value |
|---|---|---|---|---|---|---|
| Time periods of data collection (2012 vs. Nov 2013 to Oct 2014) | 0.52 | 0.33–0.82 | <0.01 | 0.45 | 0.28–0.73 | <0.01 |
| Total cesarean section (no/yes) | 4.71 | 2.89–7.68 | <0.01 | 4.16 | 2.51–6.89 | <0.01 |
| Transfers from another hospital during labor (no/yes) | 1.96 | 1.25–3.01 | <0.01 | 1.68 | 1.05–2.69 | 0.03 |
| Maternal age (years) | 1.04 | 1.01–1.07 | 0.01 | 1.03 | 1.00–1.07 | 0.04 |
| Female genital mutilation and cutting (no/yes) | 0.45 | 0.27–0.76 | 0.03 | 0.52 | 0.30–0.89 | 0.02 |
| Induced labor (no/yes) | 1.55 | 1.02–2.36 | 0.04 | 1.11 | 0.61–2.04 | 0.73 |