Hospital Delivery Research Articles

Intersectional Inequities in Maternal Mortality: Examining the Compounded Risks for Black Birthing Individuals with Physical Disabilities

BackgroundPeople who are Black and have physical disabilities likely face a dual burden of risk for maternal mortality due to enduring systemic oppression rooted in racism and ableism. ObjectiveTo investigate maternal mortality risks among Black birthing individuals with physical disabilities in the United States and assess the potential compounding effect when these marginalized identities intersect. MethodsWe conducted a historical cohort study using the 2004-2021 Healthcare Cost and Utilization Project Nationwide Inpatient Sample. The study included 8,263,997 delivery hospitalizations. We used modified Poisson regression to estimate unadjusted and adjusted relative risks (RR) of maternal mortality by race and physical disability status. We calculated the Relative Excess Risk due to Interaction (RERI) and Attributable Proportion (AP) to assess additive interaction between Black race and physical disability status. ResultsAfter adjusting for covariates, compared to their White birthing individuals, their Black peers experienced about 2.5 times (RR=1.48,95%CI:2.08-2.96) the risk of maternal mortality. Compared to birthing individuals without physical disabilities, those with physical disabilities experienced nearly 11 times the (RR=10.72,95%CI:8.15-14.10) risk of maternal mortality. Our adjusted additive interaction analysis revealed a significant super-additive effect (RERI=11.3;AP=0.47); suggesting that the combined effect of having both marginalized identities was greater than the sum of the individual effects of each identity. ConclusionsOur findings provide evidence for substantial inequities in maternal mortality by Black race and physical disability status, with evidence of a compounding effect when these marginalized identities intersect. These results underscore the urgent need for intersectional approaches in maternal health interventions and policies.

Trends and disparities in violence-related injury morbidity among pregnant and postpartum individuals

PurposeViolence against pregnant and postpartum individuals is a major public health problem. Homicides during the perinatal period have recently increased, yet these deaths reflect only the most extreme manifestation of violence. Far less is known about trends and disparities in pregnancy-associated violence morbidity. Examining emergency department (ED) utilization for violence-related injuries in this population can shed light on overall incidence and patterns of risk. MethodsWe used longitudinal, all-payer, statewide data from California, comprising all individuals with a live-birth hospital delivery in each year from 2010-2018 (N = 3,068,921). We followed annual cohorts of women before and after their delivery hospitalizations to identify ED visits for violent injury. We analyzed trends and disparities in annual incidence rates. ResultsThe cumulative incidence of any pregnancy-associated ED visit for violence was 0.84% overall; incidence increased slightly over the study period (annual ORadj = 1.01, 95% CI=1.01,1.02). The highest risk of pregnancy-associated violence was observed in younger individuals, non-Hispanic Black individuals, and Medicaid users. ConclusionOur findings suggest risk of pregnancy-associated violence morbidity has increased over the past decade and is amplified for structurally vulnerable populations. The emergency department may be a critical opportunity for screening and providing resources to at-risk individuals.

Cesarean Delivery and its Determining Factors: A Hospital-Based Study in Jashore District, Bangladesh

BackgroundThe rising prevalence of cesarean deliveries (CD) is a major public health problem worldwide, especially in Bangladesh. This study aims to investigate the prevalence and factors associated with cesarean deliveries in the Jashore district of Bangladesh. Study designThis cross-sectional study, conducted from December 2022 to February 2023 in Jashore district, Bangladesh, involved face-to-face interviews with 662 mothers during hospital visits. MethodsA pretested, structured, and validated questionnaire was employed to gather information on socioeconomic characteristics, obstetric history, maternal healthcare utilization, and factors influencing the choice of delivery method. Multinomial logistic regression models were employed to assess and predict determining factors influencing cesarean delivery. ResultsThe study revealed a high cesarean delivery (CD) prevalence of 70.5 %, exceeding the WHO-recommended threshold. Key socioeconomic factors associated with increased CD rates included rural residence, younger maternal age (15–20 years), nuclear family structure, and husbands in business. Additionally, private hospital deliveries, a history of previous CD, maternal self-preference, and doctor's influence were significant predictors of CD. The majority of participants believed CD enhances maternal safety (74.6 %) and alleviates pain (74.8 %). ConclusionThe high rate of cesarean deliveries in Jashore highlights the need for public health interventions that improve access to quality maternal care and promote evidence-based decision-making. Reducing unnecessary cesarean procedures, particularly in private hospitals, and enhancing patient education can significantly improve maternal and neonatal health outcomes.

Hospital Discharge Codes and Overestimating Severe Maternal Morbidity During Delivery Hospitalization

(Obstet Gynecol. 2024;143(4):582–584. doi: 10.1097/AOG.0000000000005537) Administrative data play a crucial role in understanding severe maternal morbidity (SMM) events, yet their interpretation heavily relies on coding quality. Overestimation of SMM during birth hospitalizations might occur due to International Classification of Diseases, Tenth Revision (ICD-10) codes being carried forward from predelivery events. This study aimed to describe SMM distribution across the antepartum, birth, and postpartum periods and to assess the potential false discovery rate of SMM events, hypothesizing that some events are subject to carry-forward coding. Following IRB approval and data-use agreements, a shared, deidentified database was created using the PCORnet Common Data Model at the University of North Carolina and Duke University.

The effects of an educational intervention on women's contraceptive preferences in the immediate postpartum period: A cross-sectional study.

To assess postpartum women's contraceptive preferences and the impact of an educational intervention on these preferences, identifying factors motivating method choices. This cross-sectional quantitative study included women within 48 h after delivery in a public Brazilian hospital. Participants were asked about their contraceptive preferences before and after an educational intervention, which aimed to inform women about the importance of early postpartum contraception, available methods, mechanisms of action, effectiveness, proper use, and side effects. A nursing professional explained contraceptives to postpartum women in individual sessions, demonstrating their use on simulators interactively for about 15 min. Statistical analyses were performed using JAMOVI version 2.3.28 and Microsoft Excel 2016. A total of 402 women (226 adolescents and 176 adults) were included. After the intervention, preference for long-acting reversible contraceptives (LARCs) increased significantly from 157 (39.1%) to 279 (68.7%) (P < 0.001). At the initial assessment, contraceptive preferences were injectable hormonal contraceptives (159 [39.6%]), intrauterine devices (IUDs) (109 [27.1%]), and implants (48 [11.9%]). After the educational intervention, IUDs became the most popular method, at 143 (35.6%), followed by implants (133 [33.1%]) and injectables (81 [20.1%]). Among adolescents, there was a significant increase in implant choice (P < 0.001) and a decrease in injectables and pills (P < 0.001; P = 0.006). Adults showed increased preference for implants (P < 0.001) and IUDs (P < 0.001), with a reduction in injectable hormonal contraceptives (P = 0.005) and tubal ligation (P = 0.006). An educational intervention during postpartum period can influence women's contraceptive choices. Timely education was associated with a significant increase in LARC preference.

Racial and Ethnic Disparities in Epidural Blood Patch Utilization Among Obstetric Patients in the United States: A Nationwide Analysis, 2016–2020

BACKGROUND: Racial and ethnic disparities in health care delivery can lead to inadequate peripartum pain management and associated adverse maternal outcomes. An epidural blood patch (EBP) is the definitive treatment for moderate to severe postdural puncture headache (PDPH), a potentially debilitating neuraxial anesthesia complication associated with significant maternal morbidity if undertreated. In this nationwide study, we examine the racial and ethnic disparities in the inpatient utilization of EBP after obstetric PDPH in the United States. METHODS: In this retrospective observational study, we used the National Inpatient Sample, a nationally representative database of discharge records for inpatient admissions in the United States, from 2016 to 2020. We analyzed delivery hospitalizations of women of childbearing age (15–49 years) diagnosed with PDPH. Adjusting for maternal and hospitalization characteristics as confounders, we used a multilevel mixed-effects logistic regression model to compare the rates of EBP utilization by race and ethnicity. Secondarily, among hospitalizations with an EBP, we examined the association between race and ethnicity and the timing of the EBP procedure. RESULTS: We analyzed 49,300 delivery hospitalizations with a diagnosis of PDPH. An EBP was performed in 24,075 (48.8%; 95% confidence interval [CI], 47.8%–49.9%) of these hospitalizations. EBP was performed in 52.7% (95% CI, 51.3%–54.1%) of White non-Hispanic patients with PDPH. Compared to White non-Hispanic patients, Black non-Hispanic (adjusted odds ratio [aOR] = 0.69; 99% CI, 0.56–0.84), Hispanic (aOR = 0.80, 99% CI, 0.68–0.95), and Asian or Pacific Islander patients (aOR = 0.74, 99% CI, 0.58–0.96) were less likely to receive an EBP. The median (interquartile range [IQR]) time to perform an EBP was 2 (1–3) days after admission, with 90% of EBP procedures completed within 4 days of admission. There was no significant association between race and ethnicity and the timing of EBP placement. CONCLUSIONS: In this nationwide analysis of delivery hospitalizations from 2016 to 2020 in the United States with a diagnosis of PDPH, we identified racial and ethnic disparities in the utilization of EBP. Minoritized patients identified as Black non-Hispanic, Hispanic, or Asian or Pacific Islander were less likely to receive an EBP for the treatment of PDPH compared to White non-Hispanic patients. Suboptimal treatment of PDPH may be associated with adverse long-term outcomes such as postpartum depression, posttraumatic stress disorder, and chronic headaches. Racial and ethnic disparities in EBP utilization should be further investigated to ensure equitable health care delivery.

Digitalization and supply chain management: impact assessment of healthcare technology implementation on service delivery in public hospitals, Lagos, Nigeria

The study examined digitalization and supply chain management: assessing healthcare technology implementation for service delivery in Lagos General Hospital, Nigeria. It employed both qualitative and quantitative techniques. It analysed 293 questionnaires using multiple-regression, and Pearson. It used thematic to analyse data from interview and focused group discussion. The results showed a value of 3.28, with a standard deviation of 1.46, indicating the effectiveness of healthcare technology in general hospital. The H2 (R2 =.078, R = 278, F (2,290) = 12.19; p&lt;.001) revealed digitalization-supply chain management have effect on Service-Delivery. The H3 (t = 3.71; B =.234; p&lt;.001) revealed SCM can have an effect on achieving Sustainable-Development-Goal3. H4 (r =.070; p &gt;.05) Revealed E-Medical Record does not have an effect on death rate in Lagos State, Nigeria. The study recommended, among other things, that all government and private healthcare facilities should harmonise EMR through SCM.

Clinical characteristics associated with peripartum maternal bloodstream infection.

Bloodstream infection (BSI) during the peripartum period is a major cause of maternal morbidity and mortality. However, data on maternal BSI during hospitalization for delivery are limited. This study aimed to investigate the incidence, clinical characteristics, risk factors, microbiological features, and antibiotic resistance patterns of maternal peripartum BSI, with a focus on understanding the role of premature rupture of membranes (PROM), fever, and other risk factors in its development. We investigated the clinical characteristics associated with maternal BSI during the peripartum period. This study included febrile women with blood cultures obtained during hospitalization for delivery. We analyzed the clinical characteristics, pathogenic microorganisms, antibiotic resistance, and maternal and neonatal outcomes of these patients. Participants were divided into BSI (n = 85) and non-BSI (n = 361) groups. Spontaneous rupture of membranes, PROM, PROM >24 h before labor, vaginal examinations >5 times, and cesarean sections during labor were more common in the BSI group. Escherichia coli (51.8%; 44/85) was the predominant causative pathogen, followed by Enterococcus faecalis (7.1%, 6/85). Approximately 31.2% of E. coli were resistant to levofloxacin, and 38.6% were extended-spectrum β-lactamase-producing bacteria. The BSI group had higher rates of maternal sepsis and Apgar scores ≤ 7 at 1 min than the non-BSI group. Furthermore, PROM, fever ≥38.9°C (102°F), and fever within 24 h after delivery were risk factors for postpartum BSI in the adjusted analysis. Maternal BSI is a potentially life-threatening disease associated with PROM and the timing and severity of fever. Early identification and surveillance of pathogen composition and antimicrobial resistance can help prevent adverse outcomes.

Birth outcomes of individuals who have experienced incarceration during pregnancy.

Describe the prevalence, health, and birth outcomes of incarcerated pregnant individuals in California between 2011 and 2015. A population-based cohort study was performed using linked birth certificate and hospital discharge data. Associations between incarceration and birth outcomes were examined, including multivariable logistic regression to estimate odds ratios and 95% confidence intervals. Amongst 1401 incarcerated and 551,029 nonincarcerated pregnant people across 112 delivery hospitals, 33% of incarcerated individuals had late initiation of prenatal care; 2.4% experienced severe maternal morbidity, compared to 18.9% and 1.6% of controls, respectively (p < 0.05). Births to incarcerated individuals had higher adjusted likelihoods of prematurity (OR 1.42, 95% CI 1.21, 1.67), small for gestational age (OR 1.31, 95% CI 1.11, 1.56), and NICU admission (OR 1.64, 95% CI, 1.40, 1.93) relative to controls. Incarcerated individuals have greater likelihood of negative birth outcomes. Identification of approaches to reduce these harms is warranted.

Interprofessional collaboration between hospital-based palliative care teams and general healthcare workers: A realist review protocol.

Palliative care, vital for patients with advanced, life-limiting or life-threatening illnesses, faces an increasing global demand due to aging populations and rising non-communicable diseases. Specialized palliative care teams (PCTs) within hospitals significantly impact patient outcomes, which requires effective interprofessional collaboration with general healthcare workers. Therefore, We will conduct a realist review to explore the contextual factors, mechanisms and outcomes related to the interprofessional collaboration between PCTs and general healthcare workers. Grounded in the third generation Cultural-Historical Activity Theory, this review will follow 5-step iterative process. First, a preliminary literature search will define the review scope. Second, based on the preliminary searches an initial program theory will be developed. Third, systematic searches across PubMed, Embase, CINHAL, Web of Science, and Scopus will be caried out. Fourth, data extraction of included studies will be conducted. Simultaneously, relevance and rigour of individual studies will be evaluated. Lastly, data analysis and synthesis will be conducted in which identified individual Context-Mechanism-Outcome (CMO) configurations will be combined in chains of inference through which hypotheses can be formulated. In summary, this realist review will refine an initially developed program theory, producing a framework elucidating how interprofessional collaboration works between PCTs and general healthcare workers. This review aims to provide crucial insights into interprofessional collaboration between PCTs and general healthcare workers, informing optimized palliative care delivery in acute care hospitals for diverse stakeholders.

Delivery-Related Maternal Morbidity and Mortality Among Patients With Cardiac Disease.

To assess the risk of severe maternal morbidity (SMM) and mortality among pregnant patients with cardiovascular disease (CVD). This was a retrospective cohort study of U.S. delivery hospitalizations from 2010 to 2020 using weighted population estimates from the National Inpatient Sample database. The primary objective was to evaluate the risk of SMM and maternal mortality among patients with CVD at delivery hospitalization. International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification codes were used to identify delivery hospitalizations, CVD, and SMM events. Multivariable logistic regression analyses were performed to compare SMM and mortality risk among patients with CVD and those without CVD. Given the substantial racial and ethnic disparities in SMM, mortality, and CVD burden, secondary objectives included evaluating SMM and mortality across racial and ethnic groups and assessing the population attributable fraction within each group. Lastly, subgroup analyses of SMM by underlying CVD diagnoses (eg, congenital heart disease, chronic heart failure) were performed. Variables used in the regression models included socioeconomic and demographic maternal characteristics, maternal comorbidities, and pregnancy-specific complications. Among 38,374,326 individuals with delivery hospitalizations, 203,448 (0.5%) had CVD. Patients with CVD had an increased risk of SMM (11.6 vs 0.7%, adjusted odds ratio [aOR] 12.5, 95% CI, 12.0-13.1) and maternal death (538 vs 5 per 100,000 delivery hospitalizations, aOR 44.1, 95% CI, 35.4-55.0) compared with those without CVD. Patients with chronic heart failure had the highest SMM risk (aOR 354.4, 95% CI, 301.0-417.3) among CVD categories. Black patients with CVD had a higher risk of SMM (aOR 15.9, 95% CI, 14.7-17.1) than those without CVD with an adjusted population attributable fraction of 10.5% (95% CI, 10.0-11.0%). CVD in pregnancy is associated with increased risk of SMM and mortality, with the highest risk of SMM among patients with chronic heart failure. Although CVD affects less than 1% of the pregnant population, it contributes to nearly 1 in 10 SMM events in the United States.

Regional Disparities, Economic Development, and Neonatal Mortality and Hospital Delivery in China

A negative association between neonatal mortality and hospital delivery has been found in some low- and lower-middle-income countries but not in rural settings characterized by poor quality of maternal and child health care. To examine the association between neonatal mortality and hospital delivery in China across urban and rural regions, regional disparities, and varying levels of economic development. This retrospective cohort study used county-level data from 2008 to 2020 from the National Maternal & Child Health Statistics across mainland China. Statistical analysis was conducted from March to December 2023. Since 2008, China has strategically leveraged hospital deliveries with national subsidies to diminish neonatal mortality, particularly in rural areas. Neonatal mortality and hospital delivery rates were calculated, and their association was estimated using multivariable fixed-effects linear models of county-level cohort data to adjust for time-invariant differences across counties and controls for gross domestic product (GDP) per capita, women's years of education, hospital beds, and health workers. The analysis included data from 2930 counties, with 198.7 million live births across 36 255 county-year records between 2008 and 2020. The mean (SD) neonatal mortality rate per 1000 live births decreased in rural areas from 12.3 (7.5) in 2008 to 3.9 (2.7) in 2020 and decreased in urban areas from 5.0 (3.1) in 2008 to 2.0 (1.3) in 2020. Hospital delivery rates increased in rural areas from a mean (SD) of 93.4% (11.8%) in 2008 to 99.9% (0.6%) in 2020 and increased in urban areas from 97.7% (6.1%) in 2008 to 100.0% (0.1%) in 2020. In rural areas, an increase of 10 percentage points in hospital deliveries was associated with a neonatal mortality rate of -1.4 (95% CI, -1.9 to -1.0; P < .001) per 1000 live births, whereas this negative association was not observed in urban areas. When the analysis was stratified by regions and incomes, the negative association became considerably stronger in the western and central regions of China, as well as in counties with lower GDP per capita. This cohort study of more than 2900 counties in China suggests that an increase in hospital deliveries was associated with reduced neonatal mortality in rural and economically underdeveloped areas in China. To further reduce neonatal mortality and improve newborn health, it is imperative to increase the accessibility of hospital delivery services.

Development and Validation of a Predictive Model for Maternal Cardiovascular Morbidity Events in Patients With Hypertensive Disorders of Pregnancy.

Hypertensive disorders of pregnancy (HDP) are a major contributor to maternal morbidity, mortality, and accelerated cardiovascular (CV) disease. Comorbid conditions are likely important predictors of CV risk in pregnant people. Currently, there is no way to predict which people with HDP are at risk of acute CV complications. We developed and validated a predictive model for all CV events and for heart failure, renal failure, and cerebrovascular events specifically after HDP. Models were created using the Premier Healthcare Database. The inclusion criteria for the model dataset were delivery with an HDP with discharge from October 1, 2015 to December 31, 2020. Machine learning methods were used to derive predictive models of CV events occurring during delivery hospitalization (Index Model) or during readmission (Readmission Model) using a training set (60%) to estimate model parameters, a validation set (20%) to tune model hyperparameters and select a final model, and a test set (20%) to evaluate final model performance. The total model cohort consisted of 553,658 deliveries with an HDP. A CV event occurred in 6501 (1.2%) of the delivery hospitalizations. Multilabel neural networks were selected for the Index Model and Readmission Model due to favorable performance compared to alternatives. This approach is designed for prediction of multiple events that share risk factors and may cooccur. The Index Model predicted all CV events with area under the receiver operating curve (AUROC) 0.878 and average precision (AP) 0.239 (cerebrovascular events: AUROC 0.941, heart failure: AUROC 0.898, and renal failure: AUROC 0.885). With a positivity threshold set to achieve ≥90% sensitivity, model specificity was 65.0%, 83.5%, 68.6%, and 65.6% for predicting all CV events, cerebrovascular events, heart failure, and renal failure, respectively. CV events within 1 year of delivery occurred in 3018 (0.6%) individuals. The Readmission Model predicted all CV events with AUROC 0.717 and AP 0.022 (renal failure: AUROC 0.748, heart failure: AUROC 0.734, and cerebrovascular events AUROC 0.698). Feature importance analysis indicated that the presence of chronic renal disease, cardiac disease, pulmonary hypertension, and preeclampsia with severe features had the greatest effect on the prediction of CV events. Among individuals with HDP, our multilabel neural network model predicted CV events at delivery admission with good classification and events within 1 year of delivery with fair classification.

Antenatal pyelonephritis hospitalisation trends, risk factors and associated adverse outcomes: A retrospective cohort study.

To analyse trends, risk factors and adverse outcomes associated with antenatal pyelonephritis hospitalisations. Retrospective cohort. A national sample of US delivery hospitalisations with associated antenatal hospitalisations. US delivery hospitalisations in the Nationwide Readmissions Database from 2010 to 2020. Antenatal hospitalisations with a pyelonephritis diagnosis within the 9 months before delivery hospitalisation were analysed. Clinical, demographic and hospital risk factors associated with antenatal pyelonephritis hospitalisations were analysed with unadjusted and adjusted logistic regression models with unadjusted and adjusted odds ratios as measures of effect. Temporal trends in antenatal pyelonephritis hospitalisations were analysed with Joinpoint regression to determine the relative measure of average annual percent change (AAPC). Risk for severe maternal morbidity and sepsis during antenatal pyelonephritis hospitalisations was similarly analysed with Joinpoint regression. Of an estimated 10.2 million delivery hospitalisations, 49 140 (0.48%) had an associated antenatal pyelonephritis hospitalisation. The proportion of deliveries with a preceding antenatal pyelonephritis hospitalisation decreased by 29% from 0.56% in 2010 to 0.40% in 2020 (AAPC -2.9%, 95% CI -4.0% to -1.9%). Antenatal pyelonephritis decreased, but risk for sepsis diagnoses increased during these hospitalisations from 3.7% in 2010 to 18.0% in 2020 (AAPC 17.2%, 95% CI 14.2%-21.1%). Similarly, risk for severe morbidity increased from 2.6% in 2010 to 4.4% in 2020 (AAPC 5.5%, 95% CI 0.8%-10.7%). Antenatal pyelonephritis admissions appear to be decreasing in the USA. However, these hospitalisations are associated with a rising risk for sepsis and severe maternal morbidity.

Modeling heterogeneity of Sudanese hospital stay in neonatal and maternal unit: non-parametric random effect models with Gamma distribution

ObjectiveStudies looking into patient and institutional variables linked to extended hospital stays have arisen as a result of the increased focus on severe maternal morbidity and mortality. Understanding the length of hospitalization of patients after delivery is important to gain insights into when hospitals will reach capacity and to predict corresponding staffing or equipment requirements. In Sudan, the distribution of the length of stay during delivery hospitalizations is heavily skewed, with the average length of stay of 2 to 3 days. This study aimed to investigate the use of non-parametric random effect model with Gamma distributed response for analyzing skewed hospital length of stay data in Sudan in neonatal and maternal unit.MethodsWe applied Gamma regression models with unknown random effects, estimated using the non-parametric maximum likelihood (NPML) technique [5]. The NPML reduces the heterogeneity in the distribution of the response and produce a robust estimation since it does not require any assumptions on the distribution. The same applies to the log–Gamma link that does not require any transformation for the data distribution and it can handle the outliers in the data points. In this study, the models are fitted with and without covariates and compared using AIC and BIC values.ResultsThe findings imply that in the context of health care database investigations, Gamma regression models with non–parametric random effect consistently reduce heterogeneity and improve model accuracy. The generalized linear model with covariates and random effect (k = 4) had the best fit, indicating that Sudanese hospital length of stay data could be classified into four groups with varying average stays influenced by maternal, neonatal, and obstetrics data.ConclusionIdentifying factors contributing to longer stays allows hospitals to implement strategies for improvement. Non-parametric random effect model with Gamma distributed response effectively accounts for unobserved heterogeneity and individual-level variability, leading to more accurate inferences and improved patient care. Including random effects can significantly affect variable significance in statistical models, emphasizing the need to consider unobserved heterogeneity when analyzing data containing potential individual-level variability. The findings emphasise the importance of making robust methodological choices in healthcare research in order to inform accurate policy decisions.

Development and Application of a Delivery Infrastructure Collapse Risk Assessment Tool: A Focus on Metropolitan Metropolitan Areas

Purpose: This study aims to develop a tool to systematically assess the risk of collapse in the delivery infrastructure and apply it to 42 districts in Gyeonggi Province. The ultimate goal is to provide data for preventive and improvement strategies tailored to regional needs.Methods: Hospitals performing over 50 deliveries annually were identified. Regions were categorized as 'none,' 'one,' or 'more than two' delivery hospitals, with further subdivision by annual delivery volume. Regions were then classified into 5 categories: 'relatively stable,' 'low-risk,' 'moderate-risk,' 'high-risk,' and 'collapsed.'Results: Of the 42 districts, 23 were classified as relatively stable, 3 as low-risk, 1 as moderate-risk, 4 as highrisk, and 11 as collapsed. Notably, areas where the delivery infrastructure has collapsed or is at high risk of collapse accounted for approximately 36% of the total.Conclusion: Tailored strategies and urgent policy support are required for high-risk regions. While perinatal regionalization may be a future direction, stable infrastructure must be maintained until the maternal care delivery system is established.

Evaluating perinatal health in Europe: a comparison of routine population birth data sources

Abstract Background International comparisons provide essential benchmarks for evaluating perinatal health policies, but these rely on the availability of routine national birth data. This study aimed to describe population birth data sources in Europe by their ability to provide core perinatal health indicators. Methods The Euro-Peristat Network collected routine national data on a recommended set of core indicators from 2015 to 2021 using a federated protocol based on a common data model with 17 data items. Data providers filled in an on-line questionnaire to describe the sources used in each country. We classified countries by the number of data items they provided (all 16, 15-14, &amp;lt;14). Results 28 out of the 31 countries that provided data responded to the survey. Routine data sources included birth certificates (14 countries), electronic medical records (EMR) from delivery hospitalizations (14 countries), direct entry by health providers (9 countries), EMR from other care providers (6 countries) and Hospital Discharge Summaries (7 countries). Completeness of population coverage was at least 98%, with 15 countries reporting 100%. These databases most often included mothers giving birth on the national territory, regardless of nationality or place of residence (19 countries). In 20 countries, routine sources were linked, including linkage between birth and death certificates (15 countries). Countries providing all 16 items (N = 8) were more likely to use EMRs from delivery hospitalizations, 88%, compared to 50% and 13% in countries with 15-14 items (N = 13) and &amp;lt;14 items (N = 8). Linkage was also more common in these countries, 100%, versus 75% and 50% respectively. Other data source characteristics did not differ by the ability to provide data for the common data model. Conclusions There is high diversity in the data sources used to construct perinatal health indicators in Europe. Countries using EMR with linkage to other sources had the best data availability. Key messages • There is high diversity in the data sources used to construct perinatal health indicators in Europe. • Countries using Electronic Medical Records with linkage to other sources had the best data availability.

Emergency Department Utilization for Postpartum Behavioral Health Problems and Assault Injury During the COVID-19 Pandemic.

Objective: Distinctive stressors facing pregnant and postpartum individuals during the COVID-19 pandemic may have affected their emergency department (ED) care-seeking for behavioral health concerns and violence victimization. We tested whether the incidence of postpartum behavioral health and assault injury ED visits differed for individuals according to their months of postpartum pandemic exposure. Methods: We used statewide, longitudinally linked hospital and ED administrative claims data from California to classify all individuals with hospital deliveries between January 1, 2016, and December 31, 2020, according to their months of postpartum pandemic exposure. Outcomes comprised 12-month incidence of any ED visit for a psychiatric disorder, drug use disorder/overdose, alcohol use disorder/intoxication, or assault injury, defined using International Classification of Diseases-Clinical Modification, version 10 codes. Risk ratios compared the incidence of each outcome among people with 1-12 months of postpartum pandemic exposure to those with 0 months of exposure. Results: Compared to people with 0 months of postpartum pandemic exposure (n = 1,163,215), delivering people with 1-12 month' exposure (range: n = 26,836 to n = 273,561) were approximately equally likely to have a postpartum ED visit for a psychiatric disorder, drug use disorder, or alcohol use disorder, after adjusting for demographic differences (most p > 0.10). The incidence of assault injury was significantly lower among delivering individuals with 11 or 12 months of pandemic exposure (RRadj = 0.70 and 0.91, respectively; both p < 0.01) compared to those with 0 months. Conclusions: Contrary to expectations, the pandemic did not appear to have affected ED utilization for most behavioral health conditions among postpartum individuals, but assault injury ED visits declined.

Maternal Risk Conditions and Outcomes by Levels of Maternal Care.

Objectives: To (1) determine associations between maternal risk conditions and severe adverse outcomes that may benefit from risk-appropriate care and (2) assess whether associations between risk conditions and outcomes vary by level of maternal care (LoMC). Methods: We used the 2017-2019 National Inpatient Sample (NIS) to calculate associations between maternal risk conditions and severe adverse outcomes. Risk conditions included severe preeclampsia, placenta accreta spectrum (PAS) conditions, and cardiac conditions. Outcomes included disseminated intravascular coagulation (DIC) with blood products transfusion or shock, pulmonary edema or acute respiratory distress syndrome (ARDS), stroke, acute renal failure, and a composite cardiac outcome. Then we used 2019 delivery hospitalization data from five states linked to hospital LoMC. We calculated associations between risk conditions and outcomes overall and stratified by LoMC and assessed for effect modification by LoMC. Results: We found positive measures of association between risk conditions and outcomes. Among patients with severe preeclampsia or PAS, the magnitudes of the associations with DIC with blood products transfusion or shock, pulmonary edema or ARDS, and acute renal failure were lower in Level III/IV compared with <Level III facilities. Among patients with cardiac conditions, the magnitudes of the associations with these outcomes, along with stroke, were also lower in Level III/IV compared with <Level III facilities. The proportion of patients with risk conditions that delivered in <Level III facilities was 19.8-46.8%. Conclusions: Odds of severe adverse outcomes among women with selected risk conditions were lower for births occurring at higher-level facilities, supporting the benefit of risk-appropriate care.

Lived experiences of women with uterine rupture who were managed at Nekemte specialized hospital: a qualitative study

BackgroundUterine rupture is a rare but severe obstetric complication that poses significant risks to maternal and fetal health. Understanding the lived experiences of individuals who have undergone uterine rupture is crucial for improving care and support for those affected by this condition. This qualitative phenomenological study aimed to explore the experiences of individuals who have experienced uterine rupture.MethodThe study employed a qualitative phenomenological approach, conducting 12 in-depth interviews and four key informant interviews with individuals who had experienced uterine rupture. Data analysis was conducted thematically using Atlas ti software to identify patterns and themes within the participants’ narratives.ResultsThe analysis of the interviews highlighted six key themes: experience during diagnosis and initial symptoms, perceived predisposing factors of uterine rupture, challenges faced by individuals with uterine rupture, impacts on their lives, and coping and resilience strategies. The findings revealed that women often failed to recognise the initial symptoms of uterine rupture due to a lack of preparation, a preference for home deliveries, husband refusal, and a general lack of awareness. This delay in seeking care resulted in severe consequences, including the loss of their babies, infertility, fistula, psychological trauma, and disruptions to daily life and relationships. To cope, many women resorted to accepting their situation, isolating themselves, and using traditional healing techniques.ConclusionsThis study’s findings provide valuable insights into the complex and multifaceted nature of uterine rupture, shedding light on the experiences of those affected by this condition. To address the challenges, it is essential to enhance awareness and education through community education programs and comprehensive antenatal classes. Additionally, improving access to healthcare by strengthening health infrastructure and deploying mobile health clinics can ensure better prenatal care. Furthermore, encouraging hospital deliveries through incentives and the support of community health workers can reduce risks. Providing psychological counselling and establishing support groups can help affected women cope with the consequences. Moreover, engaging men in maternal health through educational programs and involving them in antenatal care can foster better support. Finally, promoting safe traditional practices by integrating traditional healers and respecting cultural sensitivities can increase acceptance and adherence.