Purpose: Conduct an individual-level analysis of hospital utilization during the first year of life to test the hypothesis that community material deprivation increases healthcare utilization. Methods: We used a population-based perinatal data repository based on linkage of electronic health records (EHR) from regional delivery hospitals to subsequent hospital utilizations at the region's only dedicated children's hospital. Zero-inflated Poisson and Cox proportional hazards regression models were used to quantify the causal role of a census tract based deprivation index on the total number, length, and time until hospital utilizations during the first year of life. Results: After adjusting for any neonatal intensive care unit (NICU) admission, chronic complex conditions, race and ethnicity, insurance status, birth season, and very low birth weight we found that a 10% increase in the deprivation index caused a 1.032 fold increase (95% CI: [1.025, 1.040]) in post initial hospitalization length of stay, a 1.011 fold increase (95% CI: [1.002, 1.021]) in number of post initial hospital encounters, and 1.022 fold increase (95% CI: [1.009, 1.035]) in hazard for hospitalization utilization during the first year of life. Conclusions: Interventions designed to reduce material deprivation and income inequalities could significantly reduce infant hospital utilization.

OBJECTIVES: To compare pharmacologic treatment strategies for neonatal abstinence syndrome (NAS) with respect to total duration of opioid treatment and length of inpatient hospital stay. METHODS: We conducted a cohort analysis of late preterm and term neonates who received inpatient pharmacologic treatment of NAS at one of 20 hospitals throughout 6 Ohio regions from January 2012 through July 2013. Physicians managed NAS using 1 of 6 regionally based strategies. RESULTS: Among 547 pharmacologically treated infants, we documented 417 infants managed using an established NAS weaning protocol and 130 patients managed without protocol-driven weaning. Regardless of the treatment opioid chosen, when we accounted for hospital variation, infants receiving protocol-based weans experienced a significantly shorter duration of opioid treatment (17.7 vs 32.1 days, P < .0001) and shorter hospital stay (22.7 vs 32.1 days, P = .004). Among infants receiving protocol-based weaning, there was no difference in the duration of opioid treatment or length of stay when we compared those treated with morphine with those treated with methadone. Additionally, infants treated with phenobarbital were treated with the drug for a longer duration among those following a morphine-based compared with methadone-based weaning protocol. (P ≤ .002). CONCLUSIONS: Use of a stringent protocol to treat NAS, regardless of the initial opioid chosen, reduces the duration of opioid exposure and length of hospital stay. Because the major driver of cost is length of hospitalization, the implications for a reduction in cost of care for NAS management could be substantial.

ObjectiveTo test the hypothesis that exposure to fine particulate air pollution (PM2.5) is associated with stillbirth.Study DesignGeo-spatial population-based cohort study using Ohio birth records (2006-2010) and local measures of PM2.5, recorded by the EPA (2005-2010) via 57 monitoring stations across Ohio. Geographic coordinates of the mother’s residence for each birth were linked to the nearest PM2.5 monitoring station and monthly exposure averages calculated. The association between stillbirth and increased PM2.5 levels was estimated, with adjustment for maternal age, race, education level, quantity of prenatal care, smoking, and season of conception.ResultsThere were 349,188 live births and 1,848 stillbirths of non-anomalous singletons (20-42 weeks) with residence ≤10 km of a monitor station in Ohio during the study period. The mean PM2.5 level in Ohio was 13.3 μg/m3 [±1.8 SD, IQR(Q1: 12.1, Q3: 14.4, IQR: 2.3)], higher than the current EPA standard of 12 μg/m3. High average PM2.5 exposure through pregnancy was not associated with a significant increase in stillbirth risk, adjOR 1.21(95% CI 0.96,1.53), nor was it increased with high exposure in the 1st or 2nd trimester. However, exposure to high levels of PM2.5 in the third trimester of pregnancy was associated with 42% increased stillbirth risk, adjOR 1.42(1.06,1.91).ConclusionsExposure to high levels of fine particulate air pollution in the third trimester of pregnancy is associated with increased stillbirth risk. Although the risk increase associated with high PM2.5 levels is modest, the potential impact on overall stillbirth rates could be robust as all pregnant women are potentially at risk.

OBJECTIVE: To develop and validate a predictive risk calculator for cesarean delivery among women undergoing induction of labor. METHODS: We performed a population-based cohort study of all women who had singleton live births after undergoing induction of labor from 32 0/7 to 42 6/7 weeks of gestation in the United States from 2012 to 2016. The primary objective was to build a predictive model estimating the probability of cesarean delivery after induction of labor using antenatal factors obtained from de-identified U.S. live-birth records. Multivariable logistic regression estimated the association of these factors on risk of cesarean delivery. K-fold cross validation was performed for internal validation of the model, followed by external validation using a separate live-birth cohort from 2017. A publicly available online calculator was developed after validation and calibration were performed for individual risk assessment. The seven variables selected for inclusion in the model by magnitude of influence were prior vaginal delivery, maternal weight at delivery, maternal height, maternal age, prior cesarean delivery, gestational age at induction, and maternal race. RESULTS: From 2012 to 2016, there were 19,844,580 live births in the United States, of which 4,177,644 women with singleton gestations underwent induction of labor. Among these women, 800,423 (19.2%) delivered by cesarean. The receiver operating characteristic curve for the seven-variable model achieved an area under the curve (AUC) of 0.787 (95% CI 0.786–0.788). External validation demonstrated a consistent measure of discrimination with an AUC of 0.783 (95% CI 0.764–0.802). CONCLUSION: This validated predictive model uses seven variables that were obtainable from the patient's medical record and discriminates between women at increased or decreased risk of cesarean delivery after induction of labor. This risk calculator, found at https://ob.tools/iol-calc, can be used in addition to the Bishop score by health care providers in counseling women who are undergoing an induction of labor and allocating appropriate resources for women at high risk for cesarean delivery.