Publications

OBJECTIVE: To measure the association between restricted abortion access and maternal and infant health by maternal nativity (whether they were born in the US).

DESIGN: Observational population-based retrospective cohort study.

SETTING: United States.

POPULATION: All births (N = 33 663 837) in the United States from 2011 to 2019.

METHODS: We use Centers for Disease Control and Prevention (CDC) Period Linked Birth/Infant Deaths datafiles, with a dataset of state-level abortion restrictions (Targeted Restrictions on Abortion Providers (TRAP) laws) to estimate the association between restricted abortion access and maternal and infant health by maternal nativity. We examine restricted abortion access and maternal nativity in a triple-differences framework.

MAIN OUTCOMES MEASURES: The primary outcome we examine is maternal morbidity (defined by the CDC as any delivery involving third- or fourth- degree perineal laceration, ruptured uterus, unplanned hysterectomy, or maternal admission to intensive care). We also explore several secondary factors associated with maternal and infant health (birth interval, birth weight, receiving care in the first trimester, and gestational age at birth).

RESULTS: While we find no impact of TRAP laws on non-immigrants, foreign-born individuals in states with TRAP laws have 15% higher odds of maternal morbidity (aOR = 1.15; CI = 1.00-1.31) compared to US-born individuals in states without TRAP laws.

CONCLUSIONS: Anti-abortion legislation can worsen existing inequalities in maternal and infant health. These findings underscore the urgent need for policies that ensure equitable access to reproductive healthcare for immigrant populations.

IMPORTANCE: The US has the highest rate of preganncy-related death among high-income countries, and disparities continue to widen despite many of these deaths being largely preventable.

OBJECTIVE: To examine the age-standardized national rates of pregnancy-related death from 2018 to 2022 in the US, stratified by cause, and to compare the rates across state and race and ethnicity.

DESIGN, SETTING, AND PARTICIPANTS: This serial cross-sectional study used nationwide data on births and pregnancy-related deaths from the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research. All pregnancy-related deaths among women aged 15 to 54 years from 2018 to 2022 were included.

EXPOSURE: State, race and ethnicity, and age.

MAIN OUTCOMES AND MEASURES: The primary outcomes were all-cause and cause-specific maternal death and late maternal death (ie, deaths occurring >42 days and up to 1 year after pregnancy). The age-standardized annual and aggregated rate of pregnancy-related mortality (ASR) was estimated by age group and race and ethnicity, and state-specific crude pregnancy-related mortality rates per 100 000 live births and 95% CIs were calculated.

RESULTS: During 2018 to 2022, there were 6283 pregnancy-related deaths, including 1891 late maternal deaths. The ASR increased by 27.7% from 25.3 deaths per 100 000 live births (95% CI, 23.7-26.9) in 2018 to 32.6 deaths per 100 000 live births (95% CI, 31.2-34.8) in 2022. The increase was observed across age group and was disproportionately driven by deaths that occurred among women aged 25 to 39 years (by 36.8%, 2018 vs 2022). There was a considerable variation in rates by state, ranging from 18.5 to 59.7 deaths per 100 000 live births. If the national rate was reduced to the lowest state rate, 2679 pregnancy-related deaths could have been prevented in 2018 to 2022. American Indian and Alaska Native women had the highest ASR (106.3 deaths per 100 000 live births), followed by non-Hispanic Black women (76.9 deaths per 100 000 live births). Although cardiovascular disease was the leading cause of the overall pregnancy-related deaths, cancer, mental and behavior disorders, and drug-induced and alcohol-induced death were important contributing causes of late maternal death.

CONCLUSIONS AND RELEVANCE: In this cross-sectional analysis of pregnancy-related deaths in the US, rates increased during 2018 to 2022, with large variations by state and race and ethnicity. The concerning rates in the US should be an urgent public health priority.

BACKGROUND: Disparities in obstetric care have been well documented, but disparities in the within-hospital population have not been as extensively explored. The objective is to assess cesarean delivery rate disparities at the hospital level in a nationally recognized low risk of cesarean delivery group.

METHODS: An observational study using a national population-based database, Nationwide Inpatient Sample, from 2008 to 2011 was conducted. All patients with nulliparous, term, singleton, vertex pregnancies from Black and White patients were included. The primary outcome was delivery mode (cesarean vs vaginal). The primary independent variable was race (Black vs White).

RESULTS: A total of 1,064,351 patients were included and the overall nulliparous, term, singleton, and vertex pregnancies cesarean delivery rate was 14.1%. The within-hospital disparities of cesarean delivery rates were lower in minority-serving hospitals (OR: 1.20 95% CI: 1.12-1.28), rural hospitals (OR 1.11 95% CI: 1.02-1.20), and the South (OR 1.24 95% CI 1.19-1.30) compared to their respective counterparts. Non-minority serving hospitals (OR: 1.20 95% CI 0.12-1.25), and urban hospitals (OR1.32 95% CI 1.28-1.37), the Northeast (OR 1.41 95% CI 1.30-1.53) or West (OR 1.52 95% CI 1.38-1.67), had higher within-hospital racial disparities of cesarean delivery rates. The odds ratios reported are comparing within-hospital cesarean delivery rates in Black and White patients.

DISCUSSION: Significant within-hospital disparities of cesarean delivery rates across hospitals highlight the importance of facility-level factors. Policies aimed at advancing health equity must address hospital-level drivers of disparities in addition to structural racism.

Community-based organizations are uniquely positioned to address critical gaps in social support that contribute to inequities in maternal health. Using a human-centered design process, we held 3 design workshops with members of 15 organizations in Greater Boston, including community-based organizations, allied hospital systems, and public health departments, to assess proposed solutions for gaps in social support services during pregnancy and the first year after childbirth. The workshops focused on solutions to problems that emerged from a mixed-methods research study with community-based organizations that provide social support services; workshop attendees explored facilitators and barriers to implementing solutions. Key considerations included colocation of solutions, shared ownership of program and client data, decision making about triage and referrals, and strengthening coordination of existing programs. Collaborative design workshops surfaced potential solutions to improve coordination of services, which require addressing structural and interpersonal racism in Greater Boston.

IMPORTANCE: Crisis standards of care (CSOC) scores designed to allocate scarce resources during the COVID-19 pandemic could exacerbate racial disparities in health care.

OBJECTIVE: To analyze the association of a CSOC scoring system with resource prioritization and estimated excess mortality by race, ethnicity, and residence in a socially vulnerable area.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort analysis included adult patients in the intensive care unit during a regional COVID-19 surge from April 13 to May 22, 2020, at 6 hospitals in a health care network in greater Boston, Massachusetts. Participants were scored by acute severity of illness using the Sequential Organ Failure Assessment score and chronic severity of illness using comorbidity and life expectancy scores, and only participants with complete scores were included. The score was ordinal, with cutoff points suggested by the Massachusetts guidelines.

EXPOSURES: Race, ethnicity, Social Vulnerability Index.

MAIN OUTCOMES AND MEASURES: The primary outcome was proportion of patients in the lowest priority score category stratified by self-reported race. Secondary outcomes were discrimination and calibration of the score overall and by race, ethnicity, and neighborhood Social Vulnerability Index. Projected excess deaths were modeled by race, using the priority scoring system and a random lottery.

RESULTS: Of 608 patients in the intensive care unit during the study period, 498 had complete data and were included in the analysis; this population had a median (IQR) age of 67 (56-75) years, 191 (38.4%) female participants, 79 (15.9%) Black participants, and 225 patients (45.7%) with COVID-19. The area under the receiver operating characteristic curve for the priority score was 0.79 and was similar across racial groups. Black patients were more likely than others to be in the lowest priority group (12 [15.2%] vs 34 [8.1%]; P = .046). In an exploratory simulation model using the score for ventilator allocation, with only those in the highest priority group receiving ventilators, there were 43.9% excess deaths among Black patients (18 of 41 patients) and 28.6% (58 of 203 patients among all others (P = .05); when the highest and intermediate priority groups received ventilators, there were 4.9% (2 of 41 patients) excess deaths among Black patients and 3.0% (6 of 203) among all others (P = .53). A random lottery resulted in more excess deaths than the score.

CONCLUSIONS AND RELEVANCE: In this study, a CSOC priority score resulted in lower prioritization of Black patients to receive scarce resources. A model using a random lottery resulted in more estimated excess deaths overall without improving equity by race. CSOC policies must be evaluated for their potential association with racial disparities in health care.

INTRODUCTION: In the US, there are striking inequities in maternal health outcomes between racial and ethnic groups. Community-based organizations (CBOs) provide social support services that are critical in addressing the needs of clients of color during and after pregnancy.

METHODS: We conducted a descriptive, cross-sectional mixed methods study of CBOs in Greater Boston that provide social support services to pregnant and postpartum clients. In May-August 2020, we administered an online survey about organizational characteristics, client population, and services offered. In July-August 2020, we conducted semi-structured interviews focused on services provided, gaps in services, and the impact of structural racism on clients. We used descriptive statistics to characterize CBOs and services and used thematic analysis to extract themes from the qualitative data.

RESULTS: A total of 21 unique CBOs participated with 17 CBOs completing the survey and 14 participating in interviews. CBOs served between 10 and 35,000 pregnant and postpartum clients per year (median = 200), and about half (n = 8) focused their programming on pregnant and postpartum clients. The most significant gaps in social support services were housing and childcare. Respondents identified racism and lack of coordination among organizations as the two primary barriers to accessing social support.

DISCUSSION: CBOs face multiple challenges to providing social support to pregnant and postpartum clients of color, and significant gaps exist in the types of services currently provided. Improved coordination among CBOs and advocacy efforts to develop community-informed solutions are needed to reduce barriers to social support.

IMPORTANCE: Little is known about changes in obstetric outcomes during the COVID-19 pandemic.

OBJECTIVE: To assess whether obstetric outcomes and pregnancy-related complications changed during the COVID-19 pandemic.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included pregnant patients receiving care at 463 US hospitals whose information appeared in the PINC AI Healthcare Database. The relative differences in birth outcomes, pregnancy-related complications, and length of stay (LOS) during the pandemic period (March 1, 2020, to April 31, 2021) were compared with the prepandemic period (January 1, 2019, to February 28, 2020) using logistic and Poisson models, adjusting for patients' characteristics, and comorbidities and with month and hospital fixed effects.

EXPOSURES: COVID-19 pandemic period.

MAIN OUTCOMES AND MEASURES: The 3 primary outcomes were the relative change in preterm vs term births, mortality outcomes, and mode of delivery. Secondary outcomes included the relative change in pregnancy-related complications and LOS.

RESULTS: There were 849 544 and 805 324 pregnant patients in the prepandemic and COVID-19 pandemic periods, respectively, and there were no significant differences in patient characteristics between periods, including age (≥35 years: 153 606 [18.1%] vs 148 274 [18.4%]), race and ethnicity (eg, Hispanic patients: 145 475 [47.1%] vs 143 905 [17.9%]; White patients: 456 014 [53.7%] vs 433 668 [53.9%]), insurance type (Medicaid: 366 233 [43.1%] vs 346 331 [43.0%]), and comorbidities (all standardized mean differences <0.10). There was a 5.2% decrease in live births during the pandemic. Maternal death during delivery hospitalization increased from 5.17 to 8.69 deaths per 100 000 pregnant patients (odds ratio [OR], 1.75; 95% CI, 1.19-2.58). There were minimal changes in mode of delivery (vaginal: OR, 1.01; 95% CI, 0.996-1.02; primary cesarean: OR, 1.02; 95% CI, 1.01-1.04; vaginal birth after cesarean: OR, 0.98; 95% CI, 0.95-1.00; repeated cesarean: OR, 0.96; 95% CI, 0.95-0.97). LOS during delivery hospitalization decreased by 7% (rate ratio, 0.931; 95% CI, 0.928-0.933). Lastly, the adjusted odds of gestational hypertension (OR, 1.08; 95% CI, 1.06-1.11), obstetric hemorrhage (OR, 1.07; 95% CI, 1.04-1.10), preeclampsia (OR, 1.04; 95% CI, 1.02-1.06), and preexisting chronic hypertension (OR, 1.06; 95% CI, 1.03-1.09) increased. No significant changes in preexisting racial and ethnic disparities were observed.

CONCLUSIONS AND RELEVANCE: During the COVID-19 pandemic, there were increased odds of maternal death during delivery hospitalization, cardiovascular disorders, and obstetric hemorrhage. Further efforts are needed to ensure risks potentially associated with the COVID-19 pandemic do not persist beyond the current state of the pandemic.

BACKGROUND: Despite extensive efforts to develop and refine intervention packages, complex interventions often fail to produce the desired health impacts in full-scale evaluations. A recent example of this phenomenon is BetterBirth, a complex intervention designed to implement the World Health Organization's Safe Childbirth Checklist and improve maternal and neonatal health. Using data from the BetterBirth Program and its associated trial as a case study, we identified lessons to assist in the development and evaluation of future complex interventions.

METHODS: BetterBirth was refined across three sequential development phases prior to being tested in a matched-pair, cluster randomized trial in Uttar Pradesh, India. We reviewed published and internal materials from all three development phases to identify barriers hindering the identification of an optimal intervention package and identified corresponding lessons learned. For each lesson, we describe its importance and provide an example motivated by the BetterBirth Program's development to illustrate how it could be applied to future studies.

RESULTS: We identified three lessons: (1) develop a robust theory of change (TOC); (2) define optimization outcomes, which are used to assess the effectiveness of the intervention across development phases, and corresponding criteria for success, which determine whether the intervention has been sufficiently optimized to warrant full-scale evaluation; and (3) create and capture variation in the implementation intensity of components. When applying these lessons to the BetterBirth intervention, we demonstrate how a TOC could have promoted more complete data collection. We propose an optimization outcome and related criteria for success and illustrate how they could have resulted in additional development phases prior to the full-scale trial. Finally, we show how variation in components' implementation intensities could have been used to identify effective intervention components.

CONCLUSION: These lessons learned can be applied during both early and advanced stages of complex intervention development and evaluation. By using examples from a real-world study to demonstrate the relevance of these lessons and illustrating how they can be applied in practice, we hope to encourage future researchers to collect and analyze data in a way that promotes more effective complex intervention development and evaluation.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT02148952; registered on May 29, 2014.