Digital health outreach to promote postpartum screening after gestational diabetes: A randomized factorial pilot study.

Objective: We examined the acceptability and feasibility of a multi-component digital health outreach intervention to promote uptake of guideline-recommended postpartum screening for type 2 diabetes among patients with gestational diabetes (GDM). Methods: We conducted a 24 randomized factorial experiment as part of the Multiphase Optimization Strategy (MOST) preparation phase for developing behavioral interventions. Participants with current or recent GDM in an integrated healthcare system were randomized to receive an outreach message with up to four intervention components, designed to be self-administered in about 10 min and efficiently delivered online via REDCap: a streamlined values affirmation, personalized information on diabetes risk, an interactive motivational interviewing-based component, and an interactive action planning component. Patient-reported acceptability and feasibility outcomes were assessed via survey. Results: Among 162 participants, 72% self-identified with a racial/ethnic minority group. Across components, acceptability scores averaged 3.9/5; ≥91% of participants read most or all of the outreach message; ≥89% perceived the amount of information as "about right"; and ≥ 87% completed ≥1 interactive prompt. Conclusion: Each intervention component was acceptable to diverse patients and feasible to deliver in a brief, self-directed, online format. Innovation: These novel components target unaddressed barriers to patient engagement in guideline-recommended postpartum diabetes screening and adapt theory-based behavior change techniques for large-scale use.

Prenatal Health Care Outcomes Before and During the COVID-19 Pandemic Among Pregnant Individuals and Their Newborns in an Integrated US Health System.

Importance: The COVID-19 pandemic accelerated the use of telemedicine. However, data on the integration of telemedicine in prenatal health care and health outcomes are sparse. Objective: To evaluate a multimodal model of in-office and telemedicine prenatal health care implemented during the COVID-19 pandemic and its association with maternal and newborn health outcomes. Design, Setting, and Participants: This cohort study of pregnant individuals using longitudinal electronic health record data was conducted at Kaiser Permanente Northern California, an integrated health care system serving a population of 4.5 million people. Individuals who delivered a live birth or stillbirth between July 1, 2018, and October 21, 2021, were included in the study. Data were analyzed from January 2022 to May 2023. Exposure: Exposure levels to the multimodal prenatal health care model were separated into 3 intervals: unexposed (T1, birth delivery between July 1, 2018, and February 29, 2020), partially exposed (T2, birth delivery between March 1, 2020, and December 5, 2020), and fully exposed (T3, birth delivery between December 6, 2020, and October 31, 2021). Main Outcomes and Measures: Primary outcomes included rates of preeclampsia and eclampsia, severe maternal morbidity, cesarean delivery, preterm birth, and neonatal intensive care unit (NICU) admission. The distributions of demographic and clinical characteristics, care processes, and health outcomes for birth deliveries within each of the 3 intervals of interest were assessed with standardized mean differences calculated for between-interval contrasts. Interrupted time series analyses were used to examine changes in rates of perinatal outcomes and its association with the multimodal prenatal health care model. Secondary outcomes included gestational hypertension, gestational diabetes, depression, venous thromboembolism, newborn Apgar score, transient tachypnea, and birth weight. Results: The cohort included 151 464 individuals (mean [SD] age, 31.3 [5.3] years) who delivered a live birth or stillbirth. The mean (SD) number of total prenatal visits was similar in T1 (9.41 [4.75] visits), T2 (9.17 [4.50] visits), and T3 (9.15 [4.66] visits), whereas the proportion of telemedicine visits increased from 11.1% (79 214 visits) in T1 to 20.9% (66 726 visits) in T2 and 21.3% (79 518 visits) in T3. NICU admission rates were 9.2% (7014 admissions) in T1, 8.3% (2905 admissions) in T2, and 8.6% (3615 admissions) in T3. Interrupted time series analysis showed no change in NICU admission risk during T1 (change per 4-week interval, -0.22%; 95% CI, -0.53% to 0.09%), a decrease in risk during T2 (change per 4-week interval, -0.91%; 95% CI, -1.77% to -0.03%), and an increase in risk during T3 (change per 4-week interval, 1.75%; 95% CI, 0.49% to 3.02%). There were no clinically relevant changes between T1, T2, and T3 in the rates of risk of preeclampsia and eclampsia (change per 4-week interval, 0.76% [95% CI, 0.39% to 1.14%] for T1; -0.19% [95% CI, -1.19% to 0.81%] for T2; and -0.80% [95% CI, -2.13% to 0.55%] for T3), severe maternal morbidity (change per 4-week interval , 0.12% [95% CI, 0.40% to 0.63%] for T1; -0.39% [95% CI, -1.00% to 1.80%] for T2; and 0.99% [95% CI, -0.88% to 2.90%] for T3), cesarean delivery (change per 4-week interval, 0.06% [95% CI, -0.11% to 0.23%] for T1; -0.03% [95% CI, -0.49% to 0.44%] for T2; and -0.05% [95% CI, -0.68% to 0.59%] for T3), preterm birth (change per 4-week interval, 0.23% [95% CI, -0.11% to 0.57%] for T1; -0.37% [95% CI, -1.29% to 0.55%] for T2; and -0.15% [95% CI, -1.41% to 1.13%] for T3), or secondary outcomes. Conclusions and Relevance: These findings suggest that a multimodal prenatal health care model combining in-office and telemedicine visits performed adequately compared with in-office only prenatal health care, supporting its continued use after the pandemic.

Perinatal Outcomes After Bariatric Surgery Compared With a Matched Control Group.

OBJECTIVE: To evaluate perinatal outcomes associated with pregnancy after bariatric surgery within a large integrated health care system using propensity score matching. METHODS: We conducted a retrospective cohort study that evaluated perinatal outcomes in pregnant patients after bariatric surgery from January 2012 through December 2018. History of bariatric surgery was identified by using International Classification of Diseases codes and a clinical database. Primary outcomes were preterm birth (PTB), gestational hypertension, preeclampsia, impaired glucose tolerance or gestational diabetes, a large-for-gestational-age (LGA) or small-for-gestational-age (SGA) neonates, and cesarean birth. Propensity scores were estimated by using logistic regression that accounted for age at delivery, prepregnancy body mass index, year of delivery, parity, neighborhood deprivation index, race and ethnicity, insurance status, initiation of prenatal visit in the first trimester, smoking during pregnancy, chronic hypertension, and preexisting diabetes. Five patients in the control group were matched to each patient in the case group on linear propensity score, and modified Poisson regression was used to adjust for covariates. Sensitivity analyses by timing and type of surgery were performed. RESULTS: We identified a case cohort of 1,591 pregnancies in patients after bariatric surgery and a matched cohort of 7,955 pregnancies in patients who had not undergone bariatric surgery. Demographic characteristics were similar in both groups. In multivariate models, pregnancy after bariatric surgery was associated with a decreased risk of preeclampsia (7.5% vs 10.2%, adjusted relative risk [aRR] 0.72, 95% CI 0.60-0.86), gestational diabetes or impaired fasting glucose (23.5% vs 35.0%, aRR 0.73, 95% CI 0.66-0.80), and LGA (10.6% vs 19.9%, aRR 0.56, 95% CI 0.48-0.65) and an increased risk of SGA (10.9% vs 6.6%, aRR 1.51, 95% CI 1.28-1.78). No significant differences were observed in PTB, gestational hypertension and cesarean delivery. CONCLUSION: Pregnancy after bariatric surgery in a racially and ethnically diverse cohort of patients is associated with decreased risk of preeclampsia, gestational diabetes or impaired fasting glucose, and LGA neonates; it is also associated with an increased risk of SGA neonates compared with pregnant patients in a matched control group.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Testing and Detection During Peripartum Hospitalizations Among a Multicenter Cohort of Pregnant Persons: March 2020-February 2021.

BACKGROUND: Identifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections during peripartum hospitalizations is important to guide care, implement prevention measures, and understand infection burden. METHODS: This cross-sectional analysis used electronic health record data from hospitalizations during which pregnancies ended (peripartum hospitalizations) among a cohort of pregnant persons at 3 US integrated healthcare networks (sites 1-3). Maternal demographic, medical encounter, SARS-CoV-2 testing, and pregnancy and neonatal outcome information was extracted for persons with estimated delivery and pregnancy end dates during March 2020-February 2021 and ≥1 antenatal care record. Site-stratified multivariable logistic regression was used to identify factors associated with testing and compare pregnancy and neonatal outcomes among persons tested. RESULTS: Among 17 858 pregnant persons, 10 863 (60.8%) had peripartum SARS-CoV-2 testing; 222/10 683 (2.0%) had positive results. Testing prevalence varied by site and was lower during March-May 2020. Factors associated with higher peripartum SARS-CoV-2 testing odds were Asian race (adjusted odds ratio [aOR]: 1.36; 95% confidence interval [CI]: 1.03-1.79; referent: White) (site 1), Hispanic or Latino ethnicity (aOR: 1.33; 95% CI: 1.08-1.64) (site 2), peripartum Medicaid coverage (aOR: 1.33; 95% CI: 1.06-1.66) (site 1), and preterm hospitalization (aOR: 1.69; 95% CI: 1.19-2.39 [site 1]; aOR: 1.39; 95% CI: 1.03-1.88 [site 2]). CONCLUSIONS: Findings highlight potential disparities in SARS-CoV-2 peripartum testing by demographic and pregnancy characteristics. Testing practice variations should be considered when interpreting studies relying on convenience samples of pregnant persons testing positive for SARS-CoV-2. Efforts to address testing differences between groups could improve equitable testing practices and care for pregnant persons with SARS-CoV-2 infections.

Development and Validation of an Obstetric Comorbidity Risk Score for Clinical Use.

Background: A comorbidity summary score may support early and systematic identification of women at high risk for adverse obstetric outcomes. The objective of this study was to conduct the initial development and validation of an obstetrics comorbidity risk score for automated implementation in the electronic health record (EHR) for clinical use. Methods: The score was developed and validated using EHR data for a retrospective cohort of pregnancies with delivery between 2010 and 2018 at Kaiser Permanente Northern California, an integrated health care system. The outcome used for model development consisted of adverse obstetric events from delivery hospitalization (e.g., eclampsia, hemorrhage, death). Candidate predictors included maternal age, parity, multiple gestation, and any maternal diagnoses assigned in health care encounters in the 12 months before admission for delivery. We used penalized regression for variable selection, logistic regression to fit the model, and internal validation for model evaluation. We also evaluated prenatal model performance at 18 weeks of pregnancy. Results: The development cohort (n = 227,405 pregnancies) had an outcome rate of 3.8% and the validation cohort (n = 41,683) had an outcome rate of 2.9%. Of 276 candidate predictors, 37 were included in the final model. The final model had a validation c-statistic of 0.72 (95% confidence interval [CI] 0.70-0.73). When evaluated at 18 weeks of pregnancy, discrimination was modestly diminished (c-statistic 0.68 [95% CI 0.67-0.70]). Conclusions: The obstetric comorbidity score demonstrated good discrimination for adverse obstetric outcomes. After additional appropriate validation, the score can be automated in the EHR to support early identification of high-risk women and assist efforts to ensure risk-appropriate maternal care.

Outcomes of Admissions for Preterm Labor.

Objective This study aims to quantitate the incidence of preterm labor (PTL) admissions and determine the frequency and predictors of preterm delivery (PTD) during these admissions. Study Design Retrospective cohort of singleton pregnancies within Kaiser Permanente Northern California, 2001 to 2011. PTL admissions were defined as inpatient encounters > 24 hours with an International Classification of Diseases, 9th Revision code for PTL. Results Total study population was 365,897 with PTL admission rate 11%. PTD occurred in 85% of pregnancies with PTL admission. Delivery occurred within 48 hours of admission in 96% ≥34 weeks, 67% 31 to 33 weeks, and 51.9% <31 weeks. Predictors of delivery during PTL admission included gestational age 34 to 36 weeks (adjusted odds ratio [aOR], 6.90), chorioamnionitis (aOR, 105.58), and preterm rupture of membranes (aOR 19.29). Conclusion We demonstrate a high rate of PTD per PTL admission in a highly integrated health care system. More work is needed to determine optimal practices for hospitalization and treatment of women diagnosed with PTL.