Obstetrics and Gynecology International

Obstetrics and Gynecology International / 2021 / Article

Research Article | Open Access

Volume 2021 |Article ID 8875560 | https://doi.org/10.1155/2021/8875560

Margo S. Harrison, Ephrem Kirub, Tewodros Liyew, Biruk Teshome, Andrea Jimenez-Zambrano, Margaret Muldrow, Teklemariam Yarinbab, "Performance of Integrated Emergency Surgical Officers at Mizan-Tepi University Teaching Hospital, Mizan-Aman, Ethiopia: A Retrospective Cohort Study", Obstetrics and Gynecology International, vol. 2021, Article ID 8875560, 10 pages, 2021. https://doi.org/10.1155/2021/8875560

Performance of Integrated Emergency Surgical Officers at Mizan-Tepi University Teaching Hospital, Mizan-Aman, Ethiopia: A Retrospective Cohort Study

Academic Editor: Ixora Kamisan Atan
Received10 Aug 2020
Revised29 Oct 2020
Accepted22 Dec 2020
Published05 Jan 2021

Abstract

Introduction. Surgical physician extenders are used in Ethiopia and sub-Saharan Africa where there is a lack of surgical providers. Methods. We tested characteristics associated with and outcomes of births attended by an integrated emergency surgical officers (IESOs) as compared to midwives and physician providers. Results. Of 1,000 women in our convenience sample, data on birth attendant was missing on 5 women (0.5%). Of the remaining women, almost three-fourths (73.6%, n = 732) of women were attended by a midwife, almost a quarter were attended by an IESO (24.4%, n = 243), 10 women were attended by a physician with a General Practitioner level of training (1.0%), 5 women were delivered by an Ob/Gyn resident (0.5%), and 5 women were attended by an Ob/Gyn (0.5%). Women had a higher likelihood of being attended by an IESO than a midwife if they underwent forceps-assisted (RR 88.4, ), vacuum-assisted (RR 45.2, ), or cesarean birth (RR 161.8, ) as compared to an unassisted vaginal birth. IESOs are performing more operative vaginal and cesarean births than other delivery providers. Outcomes of their deliveries are worse than those of midwives, but this is likely due to the acuity level of the patients and not the provider type.

1. Introduction

While cesarean birth rates are increasing globally, many regions still experience unacceptably low cesarean birth rates [1, 2]. Overuse and underuse of cesarean birth can often coexist within countries and even communities [3, 4]. Though many urban areas in sub-Saharan Africa may report acceptable cesarean birth rates, many regions remain at risk for low cesarean birth rates [57]. One issue cited as a contributing factor to low cesarean birth rates in sub-Saharan Africa is lack of a sufficiently trained and available surgical work force [8]. One innovative solution to this crisis has been surgical task-shifting, or the training of nonphysician providers to deliver emergency surgery, including cesarean birth [911]. In Ethiopia, a cadre of midlevel providers referred to as Integrated Emergency Surgical Officers (IESOs) has been trained to fill the gap in availability of surgical providers [12].

Ethiopia has already increased surgical staff nationally through task-shifting emergency surgery to IESOs [9, 10, 1215]. The program was introduced in 2009; IESOs pursue a three-year course in emergency obstetrics and general surgery. [12] From 2012–2014, 4,075 operations were performed by IESOs, 63% of which were cesarean births. During this timeframe the cesarean birth rate was 12.5% (within the WHO recommended 10–15% range) [12, 1618]. Qualitative results reported that staff “stressed that maternal and child health improved significantly after the IESOs were assigned” and that IESOs “made emergency surgery services accessible to the majority, and their clinical decision-making and surgical skills were remarkable” [12]. Minimal literature exists on the performance of IESOs beyond this initial evaluation [12]. As such, we wished to observe the contribution and performance of IESOs at Mizan-Tepi University Teaching Hospital as a contribution to the literature.

2. Methodology

We conducted a hospital-based, prospective cross-sectional study at Mizan-Tepi University Teaching Hospital (MTUTH), which is located in Mizan-Aman in the Southern Nations, Nationalities, and People’s Region (SNNPR), Ethiopia [19]. The study population was a convenience sample of all women who delivered at MTUTH between May 6 and October 21, 2019, which was the point at which 1,000 women were included in the cohort [19]. Only mothers who delivered after 28 weeks gestational age were included [19]. Deidentified data was collected by highly trained physicians with the objective of planning future quality improvement and research interventions [19]. Physicians were involved in study design, but patients were not [19]. A combination of structured interview and chart review was used to collect patient information upon admission, delivery, and discharge [19]. Data was collected on paper forms, which were reviewed for completeness prior to data entry into REDCap [19]. Data was then electronically transmitted for secure storage on a password protected server at the University of Colorado, Aurora, Colorado, USA [19, 20].

STATA software version 15.2 (StataCorp LP, College Station, TX, USA) was used for analysis [19]. Bivariate comparisons of sociodemographic, obstetric, labor, delivery, and pregnancy outcomes of women delivered by midwives versus IESOs and women delivered by IESOs versus physician providers were performed [19]. We utilized Fisher’s exact, Chi-squared, and Kruskal–Wallis tests depending on the variables [19]. All covariates significant to in bivariate comparisons were included in a multivariable Poisson model with robust error variance (because IESO attendance was prevalent) to determine which covariates were independently associated with IESO delivery [19]. Subsequently, individual logistic regressions (because the outcomes were not as prevalent) of maternal and perinatal outcomes (significant in the bivariate comparisons) were run with the outcomes as the dependent variable and IESO attendant as the independent variable, adjusted for all covariates significant in the multivariable Poisson model, to describe the association between IESO attendance and adverse pregnancy outcomes [19].

This quality improvement survey was given an exempt from human subjects’ research approval (COMIRB # 18-2738) by the University of Colorado and approval [19]. Despite the quality improvement nature of the work and the fact that only deidentified data was collected, oral consent was obtained from each woman before any of her data was recorded [19].

3. Results

As shown in Figure 1, of 1,000 women on whom data was collected, 995 included information on delivery attendant (who delivered the mother). Almost three-fourths (73.6%, n = 732) of women were attended by a midwife, almost a quarter were attended by an IESO (24.4%, n = 243), 10 women were attended by a physician with a General Practitioner level of training (1.0%), 5 women delivered by an Ob/Gyn resident (0.5%), and 5 women were attended by an Ob/Gyn (0.5%).

Table 1 initially describes the overall population of women delivered by a midwife or an IESO and then compares the two groups by these provider types. The median age of women was 24 years (interquartile range [IQR] 20, 28), the largest subgroup (39.6%) has a primary school level of education, a majority of women were of Protestant religion (54.3%), 96.4% were not single, over half (54.0%) lived in an urban setting, many were nulliparous (43.4%), the majority had an interpregnancy interval of at least 24 months (52.1%), human immunodeficiency virus (HIV) was not very prevalent (2.1%), and median number of prenatal visits was 4 (IQR 3, 5). In bivariate comparisons of women who delivered by a midwife versus an IESO, women who delivered by an IESO were more likely to live in an urban area, be nulliparous, and have a history of cesarean birth; they were less likely to have HIV, .


CharacteristicN (%) N = 975Midwife (n = 732, 75.1%)IESO (n = 243, 24.9%) value

Sociodemographic & obstetric history characteristics
Age in years, median (IQR)24 [20, 28]24 [20, 28]25 [21, 28]0.12a
Missing1 (%)10

Education0.54c
 Unable to read & write229 (23.5%)165 (22.5%)64 (26.3%)
 Read & write only52 (5.3%)44 (6.0%)8 (3.3%)
 Primary school386 (39.6%)290 (39.6%)96 (39.5%)
 Secondary school138 (14.2%)105 (14.4%)33 (13.6%)
 Higher education169 (17.3%)127 (17.4%)42 (17.3%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Religion0.58b
 Muslim111 (11.4%)77 (10.4%)34 (14.0%)
 Orthodox christian331 (34.0%)252 (34.4%)79 (32.5%)
 Catholic christian0 (0.0%)0 (0.0%)0 (0.0%)
 Protestant530 (54.3%)400 (54.6%)130 (53.5%)
 Jehovah’s witness2 (0.2%)2 (0.3%)0 (0.0%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Relationship status0.67b
 Single27 (2.8%)22 (3.0%)5 (2.1%)
 Not single940 (96.4%)703 (96.0%)237 (97.5%)
 Missing8 (0.8%)7 (1.0%)1 (0.4%)

Woreda<0.001c
 Urban527 (54.0%)368 (50.3%)159 (65.4%)
 Rural448 (46.0%)364 (49.7%)84 (34.6%)

Parity0.03c
 0423 (43.4%)312 (42.6%)111 (45.7%)
 1253 (26.0%)191 (26.1%)62 (25.5%)
 2140 (14.3%)118 (16.1%)22 (9.0%)
 3+158 (16.2%)110 (15.1%)48 (19.8%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Months since last delivery (parity 1+ n = 552)0.37c
0.99a
 <24 months44 (4.5%)36 (4.9%)8 (3.3%)
 24+ months508 (52.1%)385 (52.6%)123 (50.6%)
 Missing423 (43.4%)311 (42.5%)112 (46.1%)
 Median (IQR)60 [36, 84]60 [36, 84]48 [36, 84]

History of cesarean birth<0.001b
 0930 (95.4%)716 (97.8%)214 (88.1%)
 138 (3.9%)13 (1.8%)25 (10.3%)
 2+5 (0.5%)1 (0.1%)4 (1.6%)
 Missing2 (0.2%)2 (0.3%)0 (0.0%)

HIV+0.04b
 Yes20 (2.1%)19 (2.6%)1 (0.4%)
 No947 (97.1%)707 (96.6%)240 (98.8%)
 Missing8 (0.8%)6 (0.8%)2 (0.8%)

Number of prenatal visits0.54a
0.08c
 020 (2.1%)11 (1.5%)9 (3.7%)
 <8895 (91.8%)677 (92.5%)218 (89.7%)
 8+55 (5.6%)39 (5.3%)16 (6.6%)
 Missing5 (0.5%)5 (0.7%)0 (0.0%)
 Median (IQR)4 [3, 5]4 [3, 5]4 [3, 5]

Antepartum, labor and delivery characteristics
Onset of labor<0.001b
 Spontaneous831 (85.2%)638 (87.2%)193 (79.4%)
 Augmented/Induced121 (12.4%)90 (12.3%)31 (12.8%)
 Not applicable22 (2.3%)3 (0.4%)19 (7.8%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Transferred during labor<0.001b
 No496 (50.9%)408 (55.8%)88 (36.2%)
 Yes478 (49.0%)323 (44.1%)155 (63.8%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Cervical exam on admission0.56c
0.46a
 <4 cm (latent labor)486 (49.8%)365 (49.9%)121 (49.8%)
 4+ cm (active labor)460 (47.2%)353 (48.2%)107 (44.0%)
 Missing or “not done” or “not applicable”29 (3.0%)14 (1.9%)15 (6.2%)
 Median (IQR)3 [2, 7]3 [2, 7]3 [2, 7]

Duration of labor<0.001c
 Not applicable28 (2.9%)6 (0.8%)22 (9.1%)
 <12 hours502 (51.5%)413 (56.4%)89 (36.6%)
 12–24hours394 (40.4%)290 (39.6%)104 (42.8%)
 24+ hours51 (5.2%)23 (3.2%)28 (11.5%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Antepartum hemorrhage0.003b
 No953 (97.7%)721 (98.5%)232 (95.5%)
 Yes21 (2.2%)10 (1.4%)11 (4.5%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Chorioamnionitis0.64b
 No969 (99.4%)728 (99.5%)241 (99.2%)
 Yes6 (0.6%)4 (0.5%)2 (0.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Antepartum preeclampsia/eclampsia/chronic hypertension0.53b
 No929 (95.3%)699 (95.5%)230 (94.7%)
 Yes45 (4.6%)32 (4.4%)13 (5.3%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Chorioamnionitis0.64b
 No969 (99.4%)728 (99.5%)241 (99.2%)
 Yes6 (0.6%)4 (0.5%)2 (0.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Antepartum preeclampsia/eclampsia/chronic hypertension0.53b
 No929 (95.3%)699 (95.5%)230 (94.7%)
 Yes45 (4.6%)32 (4.4%)13 (5.3%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Mode of delivery<0.001b
 Unassisted vaginal708 (72.6%)702 (95.9%)6 (2.5%)
 Forceps-assisted12 (1.2%)6 (0.8%)6 (2.5%)
 Vacuum-assisted29 (3.0%)21 (2.9%)8 (3.3%)
 Cesarean223 (22.9%)1 (0.1%)222 (91.3%)
 Missing3 (0.3%)2 (0.3%)1 (0.4%)

Gestational age at delivery0.19c
0.03a
 Preterm102 (10.5%)82 (11.2%)20 (8.2%)
 Term870 (89.2%)648 (88.5%)222 (91.4%)
 Missing3 (0.3%)2 (0.3%)1 (0.4%)
 Median (IQR)39 [38, 40]38 [38, 40]39 [38, 40]

Birthweight (grams)0.50c
<0.001a
 <250068 (7.0%)54 (7.4%)14 (5.8%)
 ≥2500858 (88.0%)650 (88.8%)208 (85.6%)
 Missing49 (5.0%)28 (3.8%)21 (8.6%)
 Median (IQR)3100 [2900, 3500]3000 [2900, 3400]3200 [3000, 3600]

Multiple gestation0.008b
 Yes928 (95.2%)705 (96.3%)223 (91.8%)
 No47 (4.8%)27 (3.7%)47 (8.2%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Postpartum maternal complicationsd
Postpartum blood transfusion<0.001b
 No960 (98.5%)729 (99.6%)231 (95.1%)
 Yes13 (1.3%)3 (0.4%)10 (4.1%)
 Missing2 (0.2%)0 (0.0%)2 (0.8%)

Postpartum antibiotics<0.001c
 No884 (90.7%)716 (97.8%)168 (69.2%)
 Yes86 (8.8%)14 (1.9%)72 (29.6%)
 Missing5 (0.5%)2 (0.3%)3 (1.2%)

Maternal length of hospitalization median (IQR)1 [1, 2]1 [1, 1]3 [3, 4]<0.001a
Missing4 (0.0%)3 (0.0%)1 (0.0%)

Postpartum neonatal complicationse
 Five-minute apgar score median (IQR)9 [8, 9]9 [8, 9]8 [7, 9]<0.001a
 Missing47 (4.5%)27 (3.0%)20 (1.8%)

Stillbirth0.001b
 Yes, fresh29 (3.0%)11 (1.5%)18 (7.4%)
 Yes, macerated12 (1.2%)11 (1.5%)1 (0.4%)
 No886 (91.0%)682 (93.3%)204 (84.0%)
 Missing48 (4.8%)28 (3.7%)20 (8.2%)

Neonate status on day of discharge<0.001c
 Dead55 (5.6%)29 (4.0%)26 (10.7%)
 Alive915 (93.9%)699 (95.5%)216 (88.9%)
 Missing5 (0.5%)4 (0.5%)1 (0.4%)

Neonatal length of hospitalization, median (IQR)1 [1, 3]1 [1, 1]3 [3, 4]<0.001a
Missing20 (2.0%)13 (1.7%)7 (3.0%)

aKruskall–Wallis test. bFisher’s Exact test. cChi-squared test. dNo difference in postpartum hemorrhage, uterotonic use. eNo difference in bag-and-mask, intranasal oxygen, continuous positive airway pressure, intravenous fluid administration, neonatal antibiotic administration, and neonatal blood transfusion.

The table then goes on to show these same comparison groups but with reference to antepartum, labor, and delivery characteristics. Overall the majority of group went into spontaneous labor (85.2%), were not transferred during labor (50.9%), were in labor less than 12 hours (51.5%), and did not experience antepartum hemorrhage (97.7%), chorioamnionitis (99.4%), or hypertensive diseases of pregnancy (95.3%). The largest subgroup was admitted in latent labor (49.8%) as compared to active, which is defined in this setting as 4 centimeters (47.2%), and the majority of births were unassisted vaginal deliveries (72.6%). Most women were term at birth (89.2%) and most babies weighed at least 2500 grams (88.0%) and were singleton gestations (95.2%). In bivariate comparisons, women who delivered by an IESO were more likely to have their labor be augmented and induced, or labor was “not applicable” (suggesting cesarean birth); they were more likely to have been transferred to MTUTH, to have a labor over 12 hours in duration, to experience antepartum hemorrhage, to undergo cesarean birth, to have a larger median size of their infant in grams, and to deliver singleton gestations, .

In the final section of Table 1, postpartum complications of the overall cohort as well as the comparison groups are presented. Though more complications were tested (see table notes), all adverse outcomes shown to be statistically significantly different by attendant time are tabulated. Women who delivered by an IESO had higher rates of maternal blood transfusion, a higher need for postpartum antibiotics, and a longer maternal hospitalization, . Regarding neonatal outcomes, delivery by an IESO resulted in higher rates of fresh stillbirth, higher rates of neonatal demise, and a longer neonatal hospitalization, .

Table 2 shows the results of our multivariable modeling. Of all significant antepartum covariates, only mode of delivery was associated with delivery attendant. Women had a higher relative risk of being attended by an IESO if they underwent forceps-assisted (RR 88.4, ), vacuum-assisted (RR 45.2, ), or cesarean birth (RR 161.8, ) as compared to an unassisted vaginal birth. When individual logistic regressions of all postpartum complications significant in Table 1 adjusted for mode of delivery were performed, odds of need maternal postpartum antibiotics (OR 13.4, ), odds of having a lower neonatal Apgar score (OR 0.1, ), and odds having a live neonate on discharge from the hospital (OR 0.1, ) were associated with IESO delivery as compared to a midwife attendant.


CharacteristicRRCI-value

(A) Multivariable poisson model with robust error variance of characteristics associated with IESO as attendanta
Mode of delivery (unassisted vaginal birth reference)
 Forceps-assisted88.428.7, 271.7<0.001
 Vacuum-assisted45.214.3, 142.3<0.001
 Cesarean161.859.9, 437.2<0.001

(B) Individual logistic regressions, adjusted for significant findings in Table 4, to determine association of cesarean birth with outcomes significant in bivariate comparisons (Table 3)
Maternal outcomesb
 Odds of postpartum hemorrhageModel did not converge
 Odds of needing postpartum antibiotics13.43.0, 60.20.001
 Odds of longer hospitalizationModel did not converge

Neonatal outcomesb
 Odds of having a higher apgar score0.10.1, 0.70.02
 Odds of live birth0.20.1, 1.30.09
 Odds of being alive at discharge from the hospital0.10.1, 0.50.005
 Odds of longer neonatal hospitalization0.20.1, 2.10.18

aVariables included in the model without an association with the outcome: urban/rural residence, parity, history of cesarean birth, HIV status, onset of labor (spontaneous or not), duration of labor, antepartum hemorrhage, birthweight, and multiple gestation. bAdjusted for mode of delivery.

Table 3 is formatted the same way as Table 1 but compares deliveries by IESOs to those performed by a physician provider (General Practitioner [GP] or Ob/Gyn (MD)). In bivariate comparisons, the groups were not different by sociodemographic or obstetrical history characteristics although there was borderline difference in religion with a higher proportion of women delivered by physicians identifying as Protestant (). In the second section, the groups were also borderline different in terms of the onset of labor of patients with patients delivered by IESOs more likely to be spontaneous or augmented/induced compared to “not applicable,” which likely represents cesarean birth (). The groups were different on antepartum hemorrhage with more women who delivered by IESOs experiencing this complication and by mode of delivery with more women who delivered by IESO experiencing cesarean birth, . Though many postpartum complications were tested (see table notes) only the lengths of maternal and neonatal hospitalization were different between groups with women who delivered by IESOs having a longer hospitalization, .


CharacteristicN (%) N = 263GP/MD 20 (n = 7.6%)IESO (n = 243, 92.4%) value

Sociodemographic and obstetric characteristics
Age in years, median (IQR)25 [21, 28]25 [21.5, 26.5]25 [21, 28]0.98a
Missing0 (0.0%)0 (0.0%)0 (0.0%)0 (0.0%)

Education0.55b
 Unable to read & write68 (25.9%)4 (20.0%)64 (26.3%)
 Read & write only10 (3.8%)2 (10.0%)8 (3.3%)
 Primary school105 (39.9%)9 (45.0%)96 (39.5%)
 Secondary school35 (13.3%)2 (10.0%)33 (13.6%)
 Higher education45 (17.1%)3 (15.0%)42 (17.3%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Religion0.05b
 Muslim34 (12.9%)0 (0.0%)34 (14.0%)
 Orthodox christian83 (31.6%)4 (20.0%)79 (32.5%)
 Catholic christian0 (0.0%)0 (0.0%)0 (0.0%)
 Protestant146 (55.5%)16 (80.0%)130 (53.5%)
 Jehovah’s witness0 (0.0%)0 (0.0%)0 (0.0%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Relationship status1.0b
 Single5 (1.9%)0 (0.0%)5 (2.1%)
 Not single257 (97.7%)20 (100.0%)237 (97.5%)
 Missing1 (0.4%)0 (0.0%)1 (0.4%)

Woreda0.22b
 Urban175 (66.5%)16 (80.0%)159 (65.4%)
 Rural88 (33.5%)4 (20.0%)84 (34.6%)

Parity0.11b
 0116 (44.1%)5 (25.0%)111 (45.7%)
 170 (26.6%)8 (40.0%)62 (25.5%)
 226 (9.9%)4 (20.0%)22 (9.0%)
 3+51 (19.4%)3 (15.0%)48 (19.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Months since last delivery (parity 1+ n = 147)0.27b
0.10a
<24 months10 (6.8%)2 (13.3%)8 (6.1%)
24+ months136 (92.5%)13 (86.7%)123 (93.2%)
Missing1 (0.7%)0 (0.0%)1 (0.7%)
Median (IQR)48 [36, 84]48 [24, 60]48 [36, 84]

History of cesarean birth0.14b
 0229 (95.4%)15 (75.0%)214 (88.1%)
 130 (3.9%)5 (25.0%)25 (10.3%)
 2+4 (0.5%)0 (0.0%)4 (1.6%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

HIV+0.15b
 Yes2 (0.8%)1 (5.0%)1 (0.4%)
 No259 (98.4%)19 (95.0%)240 (98.8%)
 Missing2 (0.8%)0 (0.0%)2 (0.8%)

Number of prenatal visits0.08c
0.88a
 09 (2.1%)0 (0.0%)9 (3.7%)
 <8238 (91.8%)20 (100.0%)218 (89.7%)
 8+16 (5.6%)0 (0.0%)16 (6.6%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)
 Median (IQR)4 [3, 5]4 [4, 4.5]4 [3, 5]

Antepartum, labor and delivery characteristics
Onset of labor0.05b
 Spontaneous206 (78.3%)13 (65.0%)193 (79.4%)
 Augmented/Induced33 (12.6%)2 (10.0%)31 (12.8%)
 Not applicable24 (9.1%)5 (25.0%)19 (7.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Transferred during labor0.74b
 No96 (36.5%)8 (40.0%)88 (36.2%)
 Yes167 (63.5%)12 (60.0%)155 (63.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Cervical exam on admission0.48c
0.82a
 <4 cm (latent labor)129 (49.1%)8 (40.0%)121 (49.8%)
 4+ cm (active labor)117 (44.5%)10 (50.0%)107 (44.0%)
 Missing or “not done” or “not applicable”17 (6.5%)2 (10.0%)15 (6.2%)
 Median (IQR)3 [2, 7]4 [2, 8]3 [2, 7]

Duration of labor0.19b
 Not applicable26 (9.9%)4 (20.0%)22 (9.1%)
 < 12 hours97 (36.9%)8 (40.0%)89 (36.6%)
 12–24 hours112 (42.6%)8 (40.0%)104 (42.8%)
 24+ hours28 (10.6%)0 (0.0%)28 (11.5%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Antepartum hemorrhage0.003b
 No953 (97.7%)721 (98.5%)232 (95.5%)
 Yes21 (2.2%)10 (1.4%)11 (4.5%)
 Missing1 (0.1%)1 (0.1%)0 (0.0%)

Chorioamnionitis0.64b
 No969 (99.4%)728 (99.5%)241 (99.2%)
 Yes6 (0.6%)4 (0.5%)2 (0.8%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Antepartum preeclampsia/eclampsia/chronic hypertension1.0b
 No251 (95.4%)19 (95.0%)232 (95.5%)
 Yes12 (4.6%)1 (5.0%)11 (4.5%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Mode of delivery<0.001b
 Unassisted vaginal14 (5.3%)8 (40.0%)6 (2.5%)
 Forceps-assisted8 (3.0%)2 (10.0%)6 (2.5%)
 Vacuum-assisted8 (3.0%)0 (0.0%)8 (3.3%)
 Cesarean232 (88.2%)10 (50.0%)222 (91.3%)
 Missing1 (0.4%)0 (0.0%)1 (0.4%)

Gestational age at delivery0.68b
0.03a
 Preterm22 (8.4%)2 (10.0%)20 (8.2%)
 Term240 (91.2%)18 (90.0%)222 (91.4%)
 Missing1 (0.4%)0 (0.0%)1 (0.4%)
 Median (IQR)39 [38, 40]38 [38, 40]39 [38, 40]

Birthweight (grams)0.14b
0.57a
 <250017 (6.4%)3 (15.0%)14 (5.8%)
 ≥2500224 (85.2%)16 (80.0%)208 (85.6%)
 Missing22 (8.4%)1 (5.0%)21 (8.6%)
 Median (IQR)3200 [3000, 3600]3200 [2700, 3500]3200 [3000, 3600]

Multiple gestation1.0b
 Yes242 (95.2%)19 (95.0%)223 (91.8%)
 No21 (4.8%)1 (5.0%)20 (8.2%)
 Missing0 (0.0%)0 (0.0%)0 (0.0%)

Postpartum maternal complicationsd
 Maternal length of hospitalization median (IQR)3 [3, 4]3 [1, 4]3 [3, 4]0.02a
 Missing1 (0.X%)0 (0.0%)1 (0.X%)

Postpartum neonatal complicationse
 Neonatal length of hospitalization, median (IQR)3 [3, 4]2 [1, 3.5]3 [3, 4]0.01a
 Missing8 (x.0%)0 (0.0%)8 (x.0%)

aKruskall–Wallis test. bFisher’s Exact test. cChi-squared test. dNo difference in postpartum hemorrhage, uterotonic use, maternal postpartum blood transfusion, and maternal postpartum antibiotics. eNo difference in bag-and-mask, intranasal oxygen, continuous positive airway pressure, intravenous fluid administration, neonatal antibiotic administration, neonatal blood transfusion, neonate status on day of discharge, neonatal status at birth, and neonatal Apgar score.

Table 4 shows the results of multivariable modeling. As compared to Muslim women, Catholic women were less likely to deliver by an IESO as compared to a physician (RR 0.9, ). Compared to women whose onset of labor was “not applicable,” those in spontaneous labor (RR 1.3, ) were more likely to deliver by an IESO. With respect to mode of delivery, women with vacuum-assisted (RR 2.4, ) or cesarean birth (RR 2.3, ) were more likely to have an IESO attendant than a physician attendant. In a logistic regression adjusted for religion, labor onset, and mode of delivery, being delivered by an IESO was not associated with length of neonatal hospitalization as compared to delivery by a physician provider.


CharacteristicRRCI value

(A) Poisson regression of characteristics associated with IESO as attendant as compared to GP or Ob/Gyn resident or attending
Religion (compared to muslim)0.90.9, 0.90.01
Catholic christian

Labor onset (compared to “not applicable”
 Spontaneous1.31.1, 1.60.03
 Augmented/Induced1.21.0, 1.50.07
Risk of antepartum hemorrhage1.10.1, 2.00.2

Mode of delivery (unassisted vaginal birth reference)
 Forceps-assisted1.80.9, 3.70.11
 Vacuum-assisted2.41.3, 4.40.003
 Cesarean2.31.3, 4.20.006

(B) Individual logistic regressions, adjusted for significant findings in Table 4, to determine association of cesarean birth with outcomes significant in bivariate comparisons (Table 3)a
 Maternal outcomes
 Odds of longer hospitalizationModel did not converge
 Neonatal outcomes
 Odds of longer neonatal hospitalization1.20.1, 9.80.87

aAdjusted for religion, labor onset, and mode of delivery.

4. Discussion

Most women at MTUTH are delivered by a midwife, but those requiring a higher level of care are majority attended to by IESOs, with very few women in our cohort delivered by physicians. Compared to midwives, IESOs are experiencing a higher need for postpartum antibiotics and are more likely to have neonates with lower median Apgars, who are more likely to demise before discharge from the hospital. As compared to physician birth attendants, IESOs did not experience any more postpartum complications and interestingly were more likely to provide cesarean and vacuum delivery than physicians.

The fact that IESOs delivered women with complications such as transfer during the labor course, prolonged labor, and antepartum hemorrhage suggests that they are functioning as a higher acuity labor and delivery provider than midwives, which is consistent with their training. It also implies that appropriate risk stratification is happening on the labor and delivery service at MTUTH and that when women experience complications, their care is being escalated. We find this reassuring and consistent with prior research findings [12]. Further observational research would be interesting to observe this transition of care and whether it is protocol-based or determined mostly by clinical decision-making as this would be an important process to disseminate to settings training and leveraging midlevel providers to extend surgical care.

Outcomes, including severe adverse neonatal outcomes like neonatal demise, were worse among IESOs as compared to midwives. Likely, as per above, this has to do with IESOs taking care of sicker patients who are experiencing antepartum complications and are more likely to require operative or surgical delivery, which may result in adverse neonatal outcomes. As this analysis is limited by the covariates collected, secondary analysis is unlikely to give a full understanding of what accounts for this finding. This would be an area where quality improvement work could likely significantly contribute to understanding this outcome and provide additional information on how to improve neonatal outcomes related to labor and delivery care and what risk is attributable to the delivery provider versus other factors.

In our analysis of IESOs versus physician providers, there were minimal clinically significant characteristics in the patient populations served by these providers (IESOs did seem to take care of more complicated patients) and no discernable difference in pregnancy outcomes. This finding may be due to the fact that the IESOs are providing a high-quality level of care or may be explained by the fact that very few deliveries were performed by physicians and as such there was not sufficient sample size to determine any differences. It was curious that there was a difference in the populations based on religion; this may be a spurious association, but it would be worth further quality improvement review to ensure that care in the facility is not variable by religious affiliation of the woman.

This analysis was limited in that we could only consider the variables that were assessed in our dataset, and the dataset was designed to look at many pregnancy outcomes, not just delivery attendant. There is more that needs to be understood about poor neonatal outcomes related to births by IESOs that cannot be determined with this dataset and requires further evaluation. It should be noted that the poor neonatal outcomes may be explained by other factors other than delivery attendant.

In summary, IESOs appear to be extending care at MTUTH beyond a midwifery level of care, and their care is associated with good maternal and neonatal outcomes. Work on improving the postpartum infection rate in the facility and better understanding adverse neonatal outcomes are areas requiring further research. Additional observational data on the role of the IESO in the labor course would also be of interest for dissemination purposes.

Data Availability

Data are available upon request.

Disclosure

The findings presented in this paper represent the views of the named authors only and not the views of their institutions or organizations.

Conflicts of Interest

The authors have no conflicts of interest reported in this work.

Authors’ Contributions

MSH conceived the research question, performed the analysis, and wrote the manuscript. TL, EK, and BT collected data and provided feedback on analysis and interpretation. AJZ managed data. MM arranged the study liaising between MSH and TL, EK, BT, and TY. TY approved the study and provided support and oversight of data collection. All authors read and provided feedback and edits on the manuscript.

Acknowledgments

The authors appreciate the significant time and effort involved with data collection for this project. The authors thank all the women who volunteered to participate in this study and provided evidence of their birth experience. Funding for this project comes primarily from the Doris Duke Charitable Foundation with additional support from the Eunice Kennedy Shriver National Institutes of Child Health and Human Development Women’s Reproductive Health Research K12 award of the primary author (5K12HD001271).

References

  1. A. P. Betrán, M. Temmerman, C. Kingdon et al., “Interventions to reduce unnecessary caesarean sections in healthy women and babies,” The Lancet, vol. 392, no. 10155, pp. 1358–1368, 2018. View at: Publisher Site | Google Scholar
  2. A. P. Betran, J. Ye, A. B. Moller, J. Zhang, A. M. Gulmezoglu, and M. R. Torloni, “The increasing trend in caesarean section rates: global, regional and national estimates: 1990-2014,” PLoS One, vol. 11, no. 2, Article ID e0148343, 2016. View at: Publisher Site | Google Scholar
  3. A. A. Boatin, A. Schlotheuber, A. P. Betran et al., “Within country inequalities in caesarean section rates: observational study of 72 low and middle income countries,” BMJ, vol. 360, p. k55, 2018. View at: Publisher Site | Google Scholar
  4. L. Gibbons, J. M. Belizan, J. A. Lauer, A. P. Betran, M. Merialdi, and F. Althabe, “Inequities in the use of cesarean section deliveries in the world,” American Journal of Obstetrics and Gynecology, vol. 206, no. 4, pp. 331e1–331e19, 2012. View at: Publisher Site | Google Scholar
  5. M. S. Harrison and R. L. Goldenberg, “Cesarean section in sub-Saharan Africa,” Maternal Health, Neonatology and Perinatology, vol. 2, no. 1, 2016. View at: Publisher Site | Google Scholar
  6. M. S. Harrison, O. Pasha, S. Saleem et al., “A prospective study of maternal, fetal and neonatal outcomes in the setting of cesarean section in low- and middle-income countries,” Acta Obstetricia et Gynecologica Scandinavica, vol. 96, no. 4, pp. 410–420, 2017. View at: Publisher Site | Google Scholar
  7. A. Shah, B. Fawole, J. M. M’Imunya et al., “Cesarean delivery outcomes from the WHO global survey on maternal and perinatal health in Africa,” International Journal of Gynecology & Obstetrics, vol. 107, no. 3, pp. 191–197, 2009. View at: Publisher Site | Google Scholar
  8. D. Ozgediz, S. Kijjambu, M. Galukande et al., “Africa's neglected surgical workforce crisis,” The Lancet, vol. 371, no. 9613, pp. 627-628, 2008. View at: Publisher Site | Google Scholar
  9. K. Chu, P. Rosseel, P. Gielis, and N. Ford, “Surgical task shifting in sub-saharan Africa,” PLoS Med, vol. 6, no. 5, Article ID e1000078, 2009. View at: Publisher Site | Google Scholar
  10. U. Lehmann, W. Van Damme, F. Barten, and D. Sanders, “Task shifting: the answer to the human resources crisis in Africa?” Human Resources for Health, vol. 7, p. 49, 2009. View at: Publisher Site | Google Scholar
  11. S. Luboga, S. B. Macfarlane, J. Von Schreeb et al., “Increasing access to surgical services in sub-saharan Africa: priorities for national and international agencies recommended by the Bellagio essential surgery group,” PLoS Med, vol. 6, no. 12, Article ID e1000200, 2009. View at: Publisher Site | Google Scholar
  12. A. A. Gobeze, Z. Kebede, Y. Berhan, and B. Ghosh, “Clinical performance of emergency surgical officers in southern Ethiopia,” Ethiopian Journal of Health Sciences, vol. 26, no. 5, 2016. View at: Publisher Site | Google Scholar
  13. T. Ashengo, A. Skeels, E. J. H. Hurwitz, E. Thuo, and H. Sanghvi, “Bridging the human resource gap in surgical and anesthesia care in low-resource countries: a review of the task sharing literature,” Human Resources for Health, vol. 15, no. 1, 2017. View at: Publisher Site | Google Scholar
  14. A. Gessessew, G. A. Barnabas, N. Prata, and K. Weidert, “Task shifting and sharing in Tigray, Ethiopia, to achieve comprehensive emergency obstetric care,” International Journal of Gynecology & Obstetrics, vol. 113, no. 1, pp. 28–31, 2011. View at: Publisher Site | Google Scholar
  15. M Koblinsky, T. Francis, A. Gaym, A. Karim, M. Carnell, and S. Tesfaye, “Responding to the maternal health care challenge: the Ethiopian health extension program,” Ethiopian Journal of Health Development, vol. 24, no. 1, pp. 105–109, 2010. View at: Publisher Site | Google Scholar
  16. A. P. Betran, M. R. Torloni, J. Zhang et al., “What is the optimal rate of caesarean section at population level? A systematic review of ecologic studies,” Reproductive Health, vol. 12, p. 57, 2015. View at: Publisher Site | Google Scholar
  17. A. Betran, M. Torloni, J. Zhang et al., “WHO statement on caesarean section rates,” BJOG: An International Journal of Obstetrics & Gynaecology, vol. 123, no. 5, pp. 667–670, 2016. View at: Publisher Site | Google Scholar
  18. J. Ye, A. P. Betrán, M. Guerrero Vela, J. P. Souza, and J. Zhang, “Searching for the optimal rate of medically necessary cesarean delivery,” Birth, vol. 41, no. 3, pp. 237–244, 2014. View at: Publisher Site | Google Scholar
  19. M. S. Harrison, T. Liyew, E. Kirub et al., “Use of cesarean birth among robson groups 2 and 4 at mizan-tepi university hospital, Ethiopia,” Obstetrics and Gynecology International, vol. 2020, Article ID 5620987, 9 pages, 2020. View at: Publisher Site | Google Scholar
  20. REDCap. REDCap. https://redcapinfo.ucdenver.edu/. Published 2019. Accessed July 5, 2019.

Copyright © 2021 Margo S. Harrison et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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