Neonatal morbidity and mortality in birth centers in the United States 2018-2021: An observational study of low-risk birthing individuals.

BACKGROUND: Many studies reporting neonatal outcomes in birth centers include births with risk factors not acceptable for birth center care using the evidence-based CABC criteria. Accurate comparisons of outcomes by birth setting for low-risk patients are needed. METHODS: Data from the public Natality Detailed File from 2018 to 2021 were used. Logistic regression, including adjusted and unadjusted odds ratios, compared neonatal outcomes (chorioamnionitis, Apgar scores, resuscitation, intensive care, seizures, and death) between centers and hospitals. Covariates included maternal diabetes, body mass index, age, parity, and demographic characteristics. RESULTS: The sample included 8,738,711 births (8,698,432 (99.53%) in hospitals and 40,279 (0.46%) in birth centers). There were no significant differences in neonatal deaths (aOR 1.037; 95% CI [0.515, 2.088]; p-value 0.918) or seizures (aOR 0.666; 95% CI [0.315, 1.411]; p-value 0.289). Measures of morbidity either not significantly different or less likely to occur in birth centers compared to hospitals included chorioamnionitis (aOR 0.032; 95% CI [0.020, 0.052]; p-value < 0.001), Apgar score < 4 (aOR 0.814, 95% CI [0.638, 1.039], p-value 0.099), Apgar score < 7 (aOR 1.075, 95% CI [0.979, 1.180], p-value 0.130), ventilation >6 h (aOR 0.349; [0.281,0.433], p-value < 0.001), and intensive care admission (aOR 0.356; 95% CI [0.328, 0.386], p-value < 0.001). Birth centers had higher odds of assisted neonatal ventilation for <6 h as compared to hospitals (aOR 1.373; 95% CI [1.293, 1.457], p-value < 0.001). CONCLUSION: Neonatal deaths and seizures were not significantly different between freestanding birth centers and hospitals. Chorioamnionitis, Apgar scores < 4, and intensive care admission were less likely to occur in birth centers.

Maternal and neonatal outcomes associated with breech presentation in planned community (home and birth center) births in the United States: A prospective observational cohort study.

OBJECTIVE: Investigate maternal and neonatal outcomes associated with breech presentation in planned community births in the United States, including outcomes associated with types of breech presentation (i.e., frank, complete, footling/kneeling). DESIGN: Secondary analysis of prospective cohort data from a national perinatal data registry (MANA Stats). SETTING: Planned community birth (homes and birth centers), United States. SAMPLE: Individuals with a term, singleton gestation (N = 71,943) planning community birth at labor onset. METHODS: Descriptive statistics to calculate associations between types of breech presentation and maternal and neonatal outcomes. MAIN OUTCOME MEASURES: Maternal: intrapartum/postpartum transfer, hospitalization, cesarean, hemorrhage, severe perineal laceration, duration of labor stages and membrane rupture Neonatal: transfer, hospitalization, NICU admission, congenital anomalies, umbilical cord prolapse, birth injury, intrapartum/neonatal death. RESULTS: One percent (n = 695) of individuals experienced breech birth (n = 401, 57.6% vaginally). Most fetuses presented frank breech (57%), with 19% complete, 18% footling/kneeling, and 5% unknown type of breech presentation. Among all breech labors, there were high rates of intrapartum transfer and cesarean birth compared to cephalic presentation (OR 9.0, 95% CI 7.7-10.4 and OR 18.6, 95% CI 15.9-21.7, respectively), with no substantive difference based on parity, planned site of birth, or level of care integration into the health system. For all types of breech presentations, there was increased risk for nearly all assessed neonatal outcomes including hospital transfer, NICU admission, birth injury, and umbilical cord prolapse. Breech presentation was also associated with increased risk of intrapartum/neonatal death (OR 8.5, 95% CI 4.4-16.3), even after congenital anomalies were excluded. CONCLUSIONS: All types of breech presentations in community birth settings are associated with increased risk of adverse neonatal outcomes. These research findings contribute to informed decision-making and reinforce the need for breech training and research and an increase in accessible, high-quality care for planned vaginal breech birth in US hospitals.

Weight Bias Among Certified Nurse-Midwives and Certified Midwives: Findings From a National Sample.

INTRODUCTION: Weight bias toward individuals with higher body weights permeates health care settings in the United States and has been associated with poor weight-related communication and quality of care as well as adverse health outcomes. However, there has been limited quantitative investigation into weight bias among perinatal care providers. Certified nurse-midwives (CNMs)/certified midwives (CMs) attend approximately 11% of all births in the United States. The aims of this study were to measure the direction and extent of weight bias among CNMs/CMs and compare their levels of weight bias to the US public and other health professionals. METHODS: Through direct postcard distribution, social media accounts, professional networks, and email listservs, American Midwifery Certification Board (AMCB)-certified midwives were solicited to complete an online survey of their implicit weight bias using the Implicit Association Test and their explicit weight bias using the Antifat Attitudes Questionnaire, Fat Phobia Scale, and Preference for Thin People measure. RESULTS: A total of 2257 midwives participated in the survey, yielding a completion rate of 17.7%. Participants were mostly White and female, with a median age of 46 years and 11 years since AMCB certification. More than 70% of midwives have some level of implicit weight bias, although to a lesser extent compared with previously published findings among the US public (P < .01) and other health professionals (P < .01). In a subsample comparison of female midwives to female physicians, implicit weight bias levels were similar (P > .05). Midwives also express explicit weight bias, but at lower levels than the US public and other health professionals (P < .05). DISCUSSION: This study provides the first quantitative research documenting weight bias among a national US sample of perinatal care providers. Findings can inform educational efforts to mitigate weight bias in the perinatal care setting and decrease harm.

Implicit and Explicit Weight Bias among Midwives: Variations Across Demographic Characteristics.

INTRODUCTION: Weight bias toward individuals with higher body weights is present in health care settings. However, there has been limited quantitative exploration into weight bias among perinatal care providers and its potential variations based on demographic characteristics. The aim of this study was to examine if the direction and extent of weight bias among midwives certified by the American Midwifery Certification Board (AMCB) varied across age, years since certification, body mass index (BMI), race, ethnicity, and US geographic region. METHODS: Through direct email listservs, postcard distribution, social media accounts, and professional networks, midwives were invited to complete an online survey of their implicit weight bias (using the Implicit Association Test) and their explicit weight bias using the Anti-Fat Attitudes Questionnaire (AFA), Fat Phobia Scale (FPS), and Preference for Thin People (PTP) measure. RESULTS: A total of 2106 midwives who identified as Black or White and resided in one of 4 US geographic regions participated in the survey. Midwives with a lower BMI expressed higher levels of implicit (P <.01) and explicit (P ≤.01) weight bias across all 4 measures except for the AFA Fear of Fat Subscale. Implicit weight bias levels also varied by age (P <.001) and years since certification (P <.001), with lower levels among younger midwives (vs older) and those with fewer years (vs more) since certification. Only age and BMI remained significant (P <.001) after adjusting for other demographic characteristics. Lower explicit weight bias levels were found among midwives who identified as Black (vs White) on 2 measures (FPS: adjusted ß = -0.07, P = .004; PTP: P = .01). DISCUSSION: This was the first quantitative study of how weight bias varies across demographic characteristics among a national sample of midwives. Further exploration is needed in more diverse samples. In addition, research to determine whether weight bias influences clinical decision-making and quality of care is warranted.

Performance of Phenotype Algorithms for the Identification of Opioid-Exposed Infants.

OBJECTIVE: Observational studies examining outcomes among opioid-exposed infants are limited by phenotype algorithms that may under identify opioid-exposed infants without neonatal opioid withdrawal syndrome (NOWS). We developed and validated the performance of different phenotype algorithms to identify opioid-exposed infants using electronic health record data. METHODS: We developed phenotype algorithms for the identification of opioid-exposed infants among a population of birthing person-infant dyads from an academic health care system (2010-2022). We derived phenotype algorithms from combinations of 6 unique indicators of in utero opioid exposure, including those from the infant record (NOWS or opioid-exposure diagnosis, positive toxicology) and birthing person record (opioid use disorder diagnosis, opioid drug exposure record, opioid listed on medication reconciliation, positive toxicology). We determined the positive predictive value (PPV) and 95% confidence interval for each phenotype algorithm using medical record review as the gold standard. RESULTS: Among 41 047 dyads meeting exclusion criteria, we identified 1558 infants (3.80%) with evidence of at least 1 indicator for opioid exposure and 32 (0.08%) meeting all 6 indicators of the phenotype algorithm. Among the sample of dyads randomly selected for review (n = 600), the PPV for the phenotype requiring only a single indicator was 95.4% (confidence interval: 93.3-96.8) with varying PPVs for the other phenotype algorithms derived from a combination of infant and birthing person indicators (PPV range: 95.4-100.0). CONCLUSIONS: Opioid-exposed infants can be accurately identified using electronic health record data. Our publicly available phenotype algorithms can be used to conduct research examining outcomes among opioid-exposed infants with and without NOWS.