Search

Objective  This study aimed to analyze whether hospital safety-net burden status is associated with increased risk for severe maternal morbidity (SMM) and postpartum readmissions. Study Design  The 2010 to 2014 Nationwide Readmissions Database was utilized for this retrospective cohort study. Hospitals were categorized as high-burden hospitals (25% of hospitals with the highest safety-net burden), medium-burden hospitals (50% of hospitals with intermediate safety-net burden), and low-burden hospitals (25% of hospitals with the lowest safety-net burden) based on the proportions of Medicaid or uninsured patients. Risk for (1) SMM, (2) 60-day postpartum readmissions, and (3) SMM during postpartum readmissions was analyzed. Unadjusted and adjusted log-linear regression models were performed, respectively, for these outcomes with unadjusted risk ratio (RR) and adjusted RR (aRR) as measures of effect. Adjusted models included demographic, hospital, and clinical factors. Results  High-burden safety-net status was associated with increased risk for SMM compared with low-burden safety-net status in both unadjusted (RR: 1.51, 95% confidence interval [CI]: 1.50–1.53) and adjusted analyses (aRR: 1.27, 95% CI: 1.25–1.30). High-burden status was also associated with increased risk for readmissions in unadjusted analyses (RR: 1.42, 95% CI: 1.40–1.44), although this risk was attenuated in adjusted analyses (aRR: 1.07, 95% CI: 1.06–1.08). High-burden status was associated with significantly increased risk for readmission for uterine infections, hypertensive diseases of pregnancy, and psychiatric diagnoses. High-burden status was not associated with severe morbidity during readmissions in adjusted or unadjusted analyses (RR: 1.02, 95% CI: 0.98–1.05; aRR: 0.95, 95% CI: 0.92–0.99). Conclusion  This study found that high safety-net burden hospitals may be a higher risk setting for obstetric care. Improvement of outcomes in high-burden settings may be important in overall efforts to reduce maternal risk. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate risk for postpartum readmissions and associated severe morbidity by maternal age.Materials and Methods: This retrospective cohort study used the Nationwide Readmissions Database to analyze 60-day all-cause postpartum readmission risk from 2010 to 2014. Risk for severe maternal morbidity (SMM) during readmission was ascertained using criteria from the Centers for Disease Control and Prevention. The primary exposure of interest was maternal age. Outcomes included time to readmission, risk of readmission, and risk for SMM during readmission. Multivariable log linear analyses adjusting for patient, obstetric, and hospital factors were conducted to assess readmission and SMM risk with adjusted risk ratios (aRRs) with 95% confidence intervals (CIs) as measures of effect.Results: Between 2010 and 2014, we identified 15.7 million deliveries, 15% of which were to women aged 35 or older. The 60-day all-cause readmission rate was 1.7%. Of these, 13% were complicated by SMM. Age-stratification revealed that women 35 and older were at increased risk for readmission and increased risk for SMM. The majority of readmissions occurred within the first 20 days regardless of age; although, women 35 and older were more likely to be admitted within the first 10 days of discharge. Patients ages 35-39, 40-44, and >44 years had 9% (95% CI 7-10%), 37% (95% CI 34-39%), and 66% (95% CI 55-79%) significantly higher rates of postpartum readmission when compared to women age 25-29. Women 35-39, 40-44, and >44 years of age had a 15% (95% CI 10-21%), 26% (95% CI 18-34%), and 56% (95% CI 25-94%) higher risk of a readmission with SMM than women 25-29.Conclusions: AMA women are at higher risk for both postpartum readmission and severe morbidity during readmission. Women older than 35 years represent the group most likely to experience complications requiring readmission, with the highest risk age 40 and older. [ABSTRACT FROM AUTHOR]

Objective  To review obstetric personnel absences at a hospital during the initial peak of coronavirus disease 2019 (COVID-19) infection risk in New York City from March 25 to April 21, 2020. Study Design  This retrospective study evaluated absences at Morgan Stanley Children's Hospital. Clinical absences for (1) Columbia University ultrasonographers, (2) inpatient nurses, (3) labor and delivery operating room (OR) technicians, (4) inpatient obstetric nurse assistants, and (5) attending physicians providing inpatient obstetric services were analyzed. Causes of absences were analyzed and classified as illness, vacation and holidays, leave, and other causes. Categorical variables were compared with the chi-square test or Fisher's exact test. Results  For nurses, absences accounted for 1,052 nursing workdays in 2020 (17.2% of all workdays) compared with 670 (11.1%) workdays in 2019 (p  < 0.01). Significant differentials in days absent in 2020 compared with 2019 were present for (1) postpartum nurses (21.9% compared with 12.9%, p  < 0.01), (2) labor and delivery nurses (14.8% compared with 10.6%, p  < 0.01), and (3) antepartum nurses (10.2% compared with 7.4%, p  = 0.03). Evaluating nursing assistants, 24.3% of workdays were missed in 2020 compared with 17.4% in 2019 (p  < 0.01). For ultrasonographers, there were 146 absences (25.2% of workdays) in 2020 compared with 96 absences (16.0% of workdays) in 2019 (p  < 0.01). The proportion of workdays missed by OR technicians was 22.6% in 2020 and 18.3% in 2019 (p  = 0.25). Evaluating attending physician absences, a total of 78 workdays were missed due to documented COVID-19 infection. Evaluating the causes of absences, illness increased significantly between 2019 and 2020 for nursing assistants (42.6 vs. 57.4%, p  = 0.02), OR technicians (17.1 vs. 55.9%, p  < 0.01), and nurses (15.5 vs. 33.7%, p  < 0.01). Conclusion  COVID-19 outbreak surge planning represents a major operational issue for medical specialties such as critical care due to increased clinical volume. Findings from this analysis suggest it is prudent to devise backup staffing plans. Key Points 1) COVID-19 outbreak surge planning represents a major operational issue for obstetrics. 2) Inpatient obstetric volume cannot be reduced. 3) Staffing contingencies plans for nurses, sonographers, and physicians may be required. [ABSTRACT FROM AUTHOR]

Objective  To characterize risk and temporal trends for preeclampsia and related outcomes by maternal age. Study Design  Deliveries to women aged 15 to 54 years in the 1998 to 2014 National Inpatient Sample who had a diagnosis of preeclampsia, eclampsia, or both were included in the analysis. Age was categorized as 15 to 17, 18 to 24, 25 to 29, 30 to 34, 35 to 39, 40 to 44, and 45 to 54 years. The primary outcome was temporal trends in preeclampsia based on maternal age. Secondary outcomes analyzed included risk for severe maternal morbidity. Results  The proportion of women with preeclampsia aged 15 to 24 years decreased from 42.3% in 1998 to 30.1% in 2014, while preeclampsia among those 30 to 54 years increased from 32.9 to 43.7%. Preeclampsia risk increased for all groups over the study period. Risk for severe morbidity by age group with and without transfusion was "U-shaped," with risk highest for women 18 to 24 and 40 to 54 years. The risk for abruption, acute renal failure, acute heart failure or pulmonary edema, and stroke was lowest for women aged 15 to 24 years and increased in a "dose-dependent" manner with increasing maternal age. In contrast, eclampsia risk was highest for women aged 15 to 17 years. Conclusion  With a changing demographic profile of preeclampsia, older women accounted for an increasing proportion of preeclampsia and related adverse outcomes. [ABSTRACT FROM AUTHOR]

Postpartum hemorrhage (PPH) remains a leading cause of maternal morbidity. Pregnancy-associated acquired hemophilia A (AHA) caused by autoantibodies against factor VIII can present with recurrent episodes of postpartum bleeding. Case 1  A 50-year-old G2P0112 presented with vaginal bleeding 22 days postcaesarean. She underwent dilation and curettage, hysterectomy, and interventional radiology (IR) embolization before AHA diagnosis. She was hospitalized for 32 days and received 23 units of blood product. She remains without relapse of AHA after 5 years. Case 2  A 48-year-old G3P1021 presented with vaginal bleeding 8 days postcaesarean. She underwent three surgeries and IR embolization before AHA diagnosis. She was hospitalized for 18 days and received 39 units of blood product. Prednisone and cyclophosphamide were continued after discharge. AHA is a rare cause of PPH. An isolated prolonged activated partial thromboplastin time (aPTT) should prompt further workup in postpartum patients with refractory bleeding. Rapid recognition of AHA can prevent significant morbidity related to hemorrhage, massive transfusion, and multiple surgeries., Competing Interests: Conflict of Interest Dr. D'Alton has a leadership role in ACOG II's Safe Motherhood Initiative, which received unrestricted funding from Merck for Mothers. The other authors do not report any potential conflicts of interest., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Maternal morbidity and mortality have gained major attention recently, spurred on by rising domestic rates even as maternal mortality decreases in Europe. A major driver of morbidity and mortality among delivering women is postpartum hemorrhage (PPH). PPH is currently phenotyped using the subjective measure of 'Estimated blood loss' (EBL), which has been shown to be unreliable for tracking quality. Here we present a framework for phenotyping PPH into multiple severity levels, using a combination of data-driven techniques and expert-derived clinical indicators. We validate the framework by predicting large drops in hematocrit and quantitative blood loss, finding that the framework performs better in predicting coded PPH than a hematocrit-based predictor or predictors based on other metrics such as blood transfusions, and does better in predicting quantitative blood loss, a gold standard metric for blood loss that we have for a subset of patients, than any predictor we could build using hematocrit drops alone. In all, we present a principled framework that can be used to phenotype PPH in hospitals using readily available EHR data, and that will perform with more granularity and accuracy than existing methods., (©2019 AMIA - All rights reserved.)