Maternal near miss among women admitted in major private hospitals in eastern Ethiopia: a retrospective study

Background: Since maternal mortality is a rare event, maternal near miss has been used as a proxy indicator for measuring maternal health. Maternal near miss (MNM) refers to a woman who nearly died but survived of complications during pregnancy, childbirth or within 42 days of termination of pregnancy. Although study of MNM in Ethiopia is becoming common, it is limited to public facilities leaving private facilities aside. The objective of this study was to assess MNM among women admitted in major private hospitals in eastern Ethiopia. Methods: An institution based retrospective study was conducted from March 05 to 31, 2020 in two major private hospitals in Harar and Dire Dawa, eastern Ethiopia. The records of all women who were admitted during pregnancy, delivery or within 42 days of termination of pregnancy was reviewed for the presence of MNM criteria as per the sub-Saharan African MNM criteria. Descriptive analysis was done by computing proportion, ratio and means. Factors associated with MNM were assessed using binary logistic regression with adjusted odds ratio (aOR) along with its 95% confidence interval (CI). Results: Of 1214 pregnant or postpartum women receiving care between January 09, 2019 and February 08, 2020, 111 women developed life-threatening conditions: 108 MNM and 3 maternal deaths. In the same period, 1173 live births were registered, resulting in an MNM ratio of 92.1 per 1000 live births. Anemia in the index pregnancy (aOR: 5.03; 95%CI: 3.12–8.13), having chronic hypertension (aOR: 3.13; 95% CI: 1.57–6.26), no antenatal care (aOR: 3.04; 95% CI: 1.58–5.83), being > 35 years old (aOR: 2.29; 95%CI: 1.22–4.29), and previous cesarean section (aOR: 4.48; 95% CI: 2.67–7.53) were significantly associated with MNM. Conclusions: Close to a tenth of women admitted to major private hospitals in eastern Ethiopia developed MNM. Women with anemia, history of cesarean section, and old age should be prioritized for preventing and managing MNM. Strengthening antenatal care and early screening of chronic conditions including hypertension is essential for preventing MNM. The study was conducted in the obstetrics and gynecology units of two major private hospitals in Harar and Dire Dawa towns, eastern Ethiopia: Harar General Hospital and Bilal General Hospital. Harar General Hospital is a 33 bedded (five ICU) hospital serving for both referred and self-referred women, especially for a better off woman. During the study period, the unit was run by five consultants and six midwives. An estimated 900 deliveries occur per annum [21]. Bilal Hospital is a general 12 bedded (four ICU) hospital in Dire Dawa run by one consultant and seven midwives [22]. Both hospitals have one major operation theatre shared for all types of surgery. Unlike the public facilities, where all maternity services are free, majority of the women in these hospitals are from better off population and urban residents paying for all hospital services. The study was conducted from March 5 to 31, 2020. Institution based cross sectional study was conducted among women admitted in the two hospitals during pregnancy, childbirth or within 42 days of termination of pregnancy during the period of January 9, 2019 to January 08, 2020 and fulfilled the validated sub-Saharan African MNM tool [8, 12, 13]. The sub-Saharan African MNM criteria contains 27 indicators (including 19 from WHO MNM tool) grouped in to clinical, laboratory and management-based approaches. The tool has already been tested in two studies from Ethiopia [8] and Namibia [13] and has been found to be effective for MNM studies in low resource settings. Incomplete medical records with missing of important variables were excluded. The minimum sample size was calculated using the WHO recommendation for calculating prevalence of severe maternal outcomes divided by the number of women giving birth within a given time period [23]. Considering the existing maternal mortality ratio and the annual number of deliveries, a total of 1000 live births were sufficient to identify 100 women with severe maternal outcomes. But considering the overall low deliveries in private facilities, we included all women who were admitted during the study period. Data were collected through review of all medical records using a standard checklist prepared for this purpose. Trained research assistants collected data on socio-demographic conditions of the woman, obstetrics history, pre-existing medical conditions, MNM events, underlying complications, and treatment received. Identification of MNM events was a two-step process. First, all medical records of women were screened for presence of any potentially life-threatening conditions (severe postpartum hemorrhage, severe pre-eclampsia, eclampsia, uterine rupture, severe complication of abortion and sepsis/ severe systemic infection), received critical interventions (use of blood products and laparotomy other than cesarean section) or admitted to the intensive care unit [5]. Then, women who developed life-threatening complications consisting MNM and maternal deaths according to the sub-Saharan Africa MNM criteria were identified. Details of the sub-Saharan Africa MNM criteria, and its development and validation are described elsewhere [8, 12]. Information regarding whether the near miss was present before arrival or developed during hospitalization was collected to determine quality of care or delays in reaching facilities. Data on total number of deliveries and live births occurring during the study period for each hospital was extracted from the monthly hospital reports. The dependent variable was MNM defined as presence of any of the sub-Saharan Africa MNM criteria [8]. Independent variables included demographic characteristics (residence, age), obstetrics history (parity, history of cesarean section, history of abortion, history of stillbirth, and ANC utilization), and pre-existing medical conditions (chronic hypertension, anemia). Data were coded; double entered and cleaned using EpiData 3.1 and exported to SPSS 20 for analysis. Descriptive statistics of study participants and MNM indicators were analyzed. MNM ratio, severe maternal outcome ratio, mortality index (proportion of women who died from all sustained severe maternal outcomes, MD/MNM + MD*100) and MNM to mortality ratios were calculated [5]. In addition, hospital access indicators, such as the number of women with an MNM condition before arrival at the hospital, and number of women with near-miss who developed conditions in the hospital were also calculated. Continuous variables like age and parity were recorded to discrete: age (< 20, 20–34, and > 35), parity (nullipara, 1–2, and > 3). Bivariate logistic regression analysis was performed to see the association between each independent variable and MNM. Independent variables with 푝-value of ≤0.25 were selected for multiple logistic regression after checking for multi-collinearity using the Variance Inflated Factor (VIF) and standard error. Association was described using adjusted odds ratio along with 95% CI and p-value < 0.05 was considered as statistically significant.