Tony Wen

BACKGROUND Digital health programs involve substantial implementation costs that are often not fully captured in economic evaluations. For managed care organizations considering coverage of these programs, understanding both implementation costs and cost-effectiveness is essential for informed decision-making. OBJECTIVE To evaluate the cost-benefit of Electronic Health Record (EHR)-integrated MOMitor™ postpartum monitoring smartphone application versus usual care by comparing 1-year postpartum acute care costs (hospitalizations and emergency department [ED] visits for common postpartum complications) and implementation costs (software, hardware, and labor). METHODS We conducted a retrospective cohort study using EHR data from a large quaternary care health system in the southeastern United States. English-speaking women aged ≥18 years, smartphone owners, with ≥1 prenatal visit within 8 weeks pre-delivery, who enrolled in MOMitor™ during delivery hospitalization were included as users. Non-users received usual care. Index date was defined as the day after discharge. Covariates were balanced using inverse probability of treatment weighting (IPTW), with absolute standardized mean differences (ASMDs) <0.1 indicating good balance. One-year postpartum acute care costs were estimated using a two-part model with a gamma distribution and log link. Models were adjusted for baseline acute care costs (8-week pre-delivery) and delivery hospitalization costs. Costs and benefits were monetized to estimate per-patient per-year (PPPY) costs from a healthcare system perspective, adjusted to 2023 USD with 3% annual inflation rate. RESULTS This analysis included 1,679 patients (mean [SD] age 27.0 [5.6] years; 27% Black), with 486 MOMitor™ users and 1,193 non-users. IPTW achieved good covariate balance (ASMDs <0.1) for all covariates. PPPY MOMitor™ implementation costs were $63 for MOMitor™ users only. IPTW-adjusted PPPY postpartum acute care costs were higher among MOMitor™ users ($2,003 vs. $1,151; p=0.61, yielding an incremental acute-care cost of $852 PPPY and a net program cost of $915 PPPY. CONCLUSIONS MOMitor™ was not cost-saving during the first postpartum year. Higher acute care costs may partly reflect timely care escalation prompted by app-identified symptoms. Future studies incorporating outpatient costs, maternal morbidity, and quality-adjusted life years are needed. Evaluating MOMitor™ over a longer time horizon would help determine whether its upfront implementation costs are offset by downstream reductions in maternal morbidity and acute-care spending.

Background: Postpartum hypertension defined as elevated blood pressure after childbirth, affects approximately 20% of women after delivery. Digital health interventions that include remote monitoring therefore, present an important opportunity to facilitate regular blood pressure assessment in this high-risk population. Objective: The primary objective is to assess within- and between-person changes in hypertension status over the first 6 weeks postpartum using a smartphone-based ecological momentary assessment protocol. The secondary objective is to characterize the trajectory of hypertension indicators across the 6-week period and to compare hypertension screening results from week one and week six within participants. Methods: This study uses a time-series design using data from prospectively enrolled patients within a large health system. Patients eligible for recruitment were women aged 18 years or older who spoke English, owned a smartphone, had a liveborn neonate, and were willing to download an app and respond to survey questions within the app. Throughout the study period, all participants received hypertension screening items that asked whether their blood pressure was greater than 140/90 mm Hg and whether they felt dizzy or lightheaded, short of breath, or had a severe headache. A subset of participants were additionally asked to report their blood pressure readings. We estimate within- and between-participant effects using a generalized linear mixed model for a positive hypertension screen during weeks one through six. The model includes both fixed and random effects, controlling for age, race, marital status, education, insurance status, mode of delivery, total number of pregnancies, and history of diabetes mellitus. Results: The study was funded July 2021 and data collection was initiated in November 2021. Data collection for this study, per protocol, was completed in June 2025, though other participants continue to be enrolled in the ongoing parent study. Data analysis is expected to be completed by Spring 2026 with publication planned for Summer 2026. Conclusions: The study findings will provide insight into trajectories of hypertension outcomes in postpartum women and the utility for smartphone app-based remote blood pressure monitoring among postpartum women whose blood pressure was regularly tracked. Findings will provide evidence to support whether widespread implementation of this digital health surveillance approach to improve outcomes in maternal health, especially in the postpartum period, is clinically warranted.

Objective: Glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) are prescribed to women of reproductive age for obesity, type 2 diabetes, obstructive sleep apnea, and more. Data on pregnancy outcomes following prepregnancy exposure remain limited. We evaluated associations between prepregnancy GLP‐1RA exposure and maternal and neonatal outcomes among women with preexisting obesity and diabetes. Methods: We conducted a retrospective cohort study using electronic health records data. Prepregnancy GLP‐1RA exposure was defined by prescription orders within 12 and 24 months prior to delivery. Propensity score matching was performed using maternal age, race and ethnicity, prepregnancy obesity status, diabetes type, chronic hypertension, insurance type, and rurality. Primary outcomes included preeclampsia (PE). Secondary outcomes included cesarean delivery, infant growth, gestational age at delivery, and neonatal intensive care unit length of stay. Results: Among 31 exposed pregnancies, 29 were matched to unexposed controls. GLP‐1RA exposure was associated with higher prevalence of PE (12 months: p = 0.023; 24 months: p = 0.018). Cesarean delivery occurred more frequently among exposed pregnancies ( p < 0.05). No differences were observed in neonatal outcomes after matching. Conclusions: Prepregnancy GLP‐1RA exposure was associated with higher prevalence of PE and cesarean delivery in this cohort. Larger studies are needed to confirm these findings and clarify underlying mechanisms.

Background: Hypertension among persons with childbearing potential is on the rise. Maintaining proper blood pressure during pregnancy is vital to prevent maternal and neonatal complications. Yet, limited evidence on the risk-benefit of various antihypertensives presents challenges for informed decision-making during this critical period. This study aimed to examine the utilization patterns of different classes of antihypertensives among persons with pre-existing hypertension before, during, and after pregnancy. Methods: We used MarketScan® Commercial Database 2011−2020 to analyze antihypertensive utilization among pregnant persons aged 12 to 55 identified via a validated algorithm. Pre-existing hypertension was defined as ≥1 inpatient or ≥2 outpatient encounters for hypertension within the 180 days preceding the LMP. Antihypertensive utilization was described during target periods: 0–3 months (0-3M) before pregnancy, 1st/2nd/3rd trimester (T1/2/3), 0-3M, and 4-6M after pregnancy. Results: We identified 1,950,292 pregnancies, of which 20,576 (12,978 live and 7,598 non-live) had pre-existing hypertension. Both groups had similar antihypertensive use (80.1% and 81.0%, respectively) during the 6 months before pregnancy (baseline). For live-birth pregnancies, 13.9% of baseline users discontinued treatment during pregnancy, while 28.9% of non-users initiated antihypertensives during pregnancy, and 17.2% started postpartum. Before pregnancy, the predominant antihypertensives included thiazide diuretics (21.9%), combined α- and β-blockers (18.4%), and dihydropyridines (16.2%). During pregnancy, thiazide diuretics, cardioselective β-blockers, and ACE inhibitors declined (T3: 3.0%, 4.2%, and 0.8%). Dihydropyridine use was steady during pregnancy, but preference shifted from amlodipine to nifedipine in T3 (2.2.% vs.10.8%). Central α2‐agonists increased during pregnancy (up to 15.2% in T3) compared to both pre- (9.8%) and post-pregnancy (5.7%). ARBs mirrored ACE inhibitors, with less than 1% utilization in later trimesters. Combination agents dropped from 10.8% pre-pregnancy to 0.8% in T3, then rebounded to 7.3% post-pregnancy. Conclusion: Research is warranted to evaluate the choice of antihypertensives and optimal timing to switch to safer alternatives, considering maternal and fetal outcomes.

Background: The rates of hepatitis C virus (HCV) infection have increased in the pregnant population. We aim to describe the age-stratified clinical outcomes and trends for inpatient pregnant women with HCV in the U.S. Methods: We utilized hospitalization data from the 2010–2020 National Inpatient Sample. Pregnancy and HCV were identified according to their ICD-9/ICD-10 codes. Demographic and clinical data including cirrhosis, mortality, preterm birth, and stillbirth were extracted. The age groups were defined as ≤18, 19–25, 26–34, and ≥35 years. Results: We identified 195,852 inpatient pregnant women with HCV, among whom 0.7% were ≤18, 26.7% were 19–25, 57.9% were 26–34, and 14.8% were ≥35 years of age. The hospitalization rates of pregnant women with HCV increased overall between 2010 and 2020, with the highest velocity in the 26–34 age group. The 26–34 age group had the highest HCV burden, with an age-standardized hospitalization rate of 660 per 100,000 in 2020. The rates of mortality and cirrhosis were significantly higher in the HCV cohort and increased further with age (p < 0.05). Among the HCV pregnant cohort, 151,017 (77.1%) delivered during hospitalization. Preterm births and stillbirths were significantly higher in the HCV pregnant cohort compared to the controls across multiple age groups (p < 0.05). Minority race/ethnicity was associated with increased mortality, cirrhosis, preterm birth, and stillbirth (p < 0.001). HIV co-infection, hepatitis B co-infection, and diabetes increased the odds of cirrhosis (p < 0.001). Conclusions: Hospitalizations of pregnant women with HCV are escalating, and these women are at increased risk of mortality, cirrhosis, preterm birth, and stillbirth with modifying factors, exacerbating risks further.

Background: Prevention of the vertical transmission of the hepatitis C virus (HCV) presents an obstetric challenge. There are no approved antiviral medications for the treatment or prevention of HCV for pregnant patients. Objective: We aimed to create a composite score to accurately identify a population of pregnant patients with HCV who have high potential for vertical transmission. Study Design: In a retrospective, multicenter cohort study, we identified pregnant patients with hepatitis C with linked data to their infants who have had HCV RNA or HCV antibody testing. Demographic data, including age and race/ethnicity, as well as clinical and laboratory data, including tobacco/alcohol use, infections, liver function tests, the HCV RNA titer, HCV antibody, HCV genotype, absolute lymphocyte count, and platelet count, were collected. Data were analyzed using logistic regression and receiver operating characteristics (ROCs) and internally validated using the forward selection bootstrap method. Results: We identified 157 pregnant patients and 163 corresponding infants. The median maternal delivery age was 29 (IQR: 25–33) years, and the majority (141, or 89.8%) were White. A high HCV RNA titer, high absolute lymphocyte count, and high platelet count were associated with vertical transmission. A high HCV RNA titer had an AUROC of 0.815 with sensitivity, specificity, a positive predictive value, and a negative predictive value of 100.0%, 59.1%, 17.6%, and 100.0%, respectively. A composite score combining the three risk factors had an AUROC of 0.902 (95% CI = 0.840–0.964) but with a risk of overfitting. Conclusions: An HCV RNA titer alone or a composite score combining the risk factors for HCV vertical transmission can potentially identify a population of pregnant patients where the rate of vertical transmission is high, allowing for potential interventions during antepartum care.

Background: Up to 15% of pregnant and postpartum women commonly experience undiagnosed and untreated mental health conditions, such as depression and anxiety, which may result in serious health complications. Mobile health (mHealth) apps related to mental health have been previously used for early diagnosis and intervention but not among pregnant and postpartum women. Objective: This study aims to assess the acceptability of using mHealth to monitor and assess perinatal and postpartum depression and anxiety. Methods: Focus group discussions with pregnant and postpartum women (n=20) and individual interviews with health care providers (n=8) were conducted to inform the acceptability of mHealth and determine its utility for assessing perinatal and postpartum mood symptoms. Participants were recruited via purposive sampling from obstetric clinics and the surrounding community. A semistructured interview guide was developed by an epidemiologist with qualitative research training in consultation with an obstetrician. The first author conducted all focus group discussions and provider interviews either in person or via Zoom (Zoom Video Communications, Inc) depending on the COVID-19 protocol that was in place during the study period. All interviews were audio recorded with consent; transcribed; and uploaded for coding to ATLAS.ti 8 (ATLAS.ti Scientific Software Development Gmb H), a qualitative data analysis and retrieval software. Data were analyzed using the deductive content analysis method using a set of a priori codes developed based on the interview guide. Methodological rigor and quality were ensured by adopting a systematic approach during the implementation, data collection, data analysis, and reporting of the data. Results: Almost all women and providers had downloaded and used at least 1 health app. The respondents suggested offering short questions in layperson language that could be understood by women of all educational levels and offering no more than 2 to 3 assessments per day at preferred timings decided by the women themselves. They also suggested that the women themselves receive the alerts first, with other options being family members, spouses, or friends if the women themselves did not respond within 24 to 72 hours. Customization and snooze features were strongly endorsed by women and providers to improve acceptability and utility. Women mentioned competing demands on their time during the postpartum period, fatigue, privacy, and the security of mental health data as concerns. Health care professionals highlighted the long-term sustainability of app-based mood assessment and monitoring as an important challenge. Conclusions: The findings from this study show that mHealth would be acceptable to pregnant and postpartum women for monitoring mood symptoms. This could inform the development of clinically meaningful and inexpensive tools for facilitating the continuous monitoring of, the early diagnosis of, and an early intervention for mood disorders in this vulnerable population.

BACKGROUND Up to 15% of pregnant and postpartum women commonly experience undiagnosed and untreated mental health conditions, such as depression and anxiety, which may result in serious health complications. Mobile health (mHealth) apps related to mental health have been previously used for early diagnosis and intervention but not among pregnant and postpartum women. OBJECTIVE This study aims to assess the acceptability of using mHealth to monitor and assess perinatal and postpartum depression and anxiety. METHODS Focus group discussions with pregnant and postpartum women (n=20) and individual interviews with health care providers (n=8) were conducted to inform the acceptability of mHealth and determine its utility for assessing perinatal and postpartum mood symptoms. Participants were recruited via purposive sampling from obstetric clinics and the surrounding community. A semistructured interview guide was developed by an epidemiologist with qualitative research training in consultation with an obstetrician. The first author conducted all focus group discussions and provider interviews either in person or via Zoom (Zoom Video Communications, Inc) depending on the COVID-19 protocol that was in place during the study period. All interviews were audio recorded with consent; transcribed; and uploaded for coding to ATLAS.ti 8 (ATLAS.ti Scientific Software Development Gmb H), a qualitative data analysis and retrieval software. Data were analyzed using the deductive content analysis method using a set of a priori codes developed based on the interview guide. Methodological rigor and quality were ensured by adopting a systematic approach during the implementation, data collection, data analysis, and reporting of the data. RESULTS Almost all women and providers had downloaded and used at least 1 health app. The respondents suggested offering short questions in layperson language that could be understood by women of all educational levels and offering no more than 2 to 3 assessments per day at preferred timings decided by the women themselves. They also suggested that the women themselves receive the alerts first, with other options being family members, spouses, or friends if the women themselves did not respond within 24 to 72 hours. Customization and snooze features were strongly endorsed by women and providers to improve acceptability and utility. Women mentioned competing demands on their time during the postpartum period, fatigue, privacy, and the security of mental health data as concerns. Health care professionals highlighted the long-term sustainability of app-based mood assessment and monitoring as an important challenge. CONCLUSIONS The findings from this study show that mHealth would be acceptable to pregnant and postpartum women for monitoring mood symptoms. This could inform the development of clinically meaningful and inexpensive tools for facilitating the continuous monitoring of, the early diagnosis of, and an early intervention for mood disorders in this vulnerable population.