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1.
BMC Pregnancy Childbirth ; 22(1): 759, 2022 Oct 10.
Article in English | MEDLINE | ID: mdl-36217115

ABSTRACT

BACKGROUND: Reducing cesarean rates is a public health priority. To help pregnant people select hospitals with lower cesarean rates, numerous organizations publish publically hospital cesarean rate data. Few pregnant people use these data when deciding where to deliver. We sought to determine whether making cesarean rate data more accessible and understandable increases the likelihood of pregnant people selecting low-cesarean rate hospitals. METHODS: We conducted a 1:1 randomized controlled trial in 2019-2021 among users of a fertility and pregnancy mobile application. Eligible participants were trying to conceive for fewer than five months or were 28-104 days into their pregnancies. Of 189,456 participants approached and enrolled, 120,621 participants met entry criteria and were included in analyses. The intervention group was offered an educational program explaining the importance of hospital cesarean rates and an interactive tool presenting hospital cesarean rates as 1-to-5-star ratings. Control group users were offered an educational program about hospital choice and a hospital choice tool without cesarean rate data. The primary outcome was the star rating of the hospital selected by each patient during pregnancy. Secondary outcomes were the importance of cesarean rates in choosing a hospital and delivery method (post-hoc secondary outcome). RESULTS: Of 120,621 participants (mean [SD] age, 27.8 [7.9]), 12,284 (10.2%) reported their choice of hospital during pregnancy, with similar reporting rates in the intervention and control groups. Intervention group participants selected hospitals with higher star ratings (2.52 vs 2.16; difference, 0.37 [95% CI, 0.32 to 0.43] p < 0.001) and were more likely to believe that the hospitals they chose would impact their chances of having cesarean deliveries (38.5% vs 33.1%, p < 0.001) but did not assign higher priority to cesarean delivery rates when choosing their hospitals (76.2% vs 74.3%, p = 0.05). There was no difference in self-reported cesarean rates between the intervention and control groups (31.4% vs 31.4%, p = 0.98). CONCLUSION: People offered an educational program and interactive tool to compare hospital cesarean rates were more likely to use cesarean data in selecting a hospital and selected hospitals with lower cesarean rates but were not less likely to have a cesarean. CLINICAL TRIAL REGISTRATION: Registered December 9, 2016 at clinicaltrials.gov, First enrollment November 2019. ID NCT02987803, https://clinicaltrials.gov/ct2/show/NCT02987803.


Subject(s)
Cesarean Section , Hospitals, Maternity , Adult , Female , Humans , Pregnancy , Research Design
2.
JMIR Pediatr Parent ; 4(4): e27769, 2021 Oct 04.
Article in English | MEDLINE | ID: mdl-34509975

ABSTRACT

BACKGROUND: The COVID-19 pandemic has presented obstacles for providers and patients in the maternal health care setting, causing changes to many pregnant women's birth plans, as well as abrupt changes in hospital labor and delivery policies and procedures. Few data exist on the effects of the COVID-19 pandemic on the maternal health care landscape at the national level in the United States. OBJECTIVE: The aim of this study is to assess the incidence of key obstetrics outcomes (preterm delivery, Cesarean sections, and home births) and length of hospital stay during the COVID-19 pandemic as compared to the 6 months prior. METHODS: We conducted a retrospective cohort study of women aged 18-44 years in the United States who delivered between October 1, 2019, and September 30, 2020, had singleton deliveries, and completed a birth report in the Ovia Pregnancy mobile app. Women were assigned to the prepandemic cohort if they delivered between October 2019 and March 2020, and the pandemic cohort if they delivered between April and September 2020. Gestational age at delivery, delivery method, delivery facility type, and length of hospital stay were compared. RESULTS: A total of 304,023 birth reports were collected, with 152,832 (50.26%) in the prepandemic cohort and 151,191 (49.73%) in the pandemic cohort. Compared to the prepandemic cohort, principal findings indicate a 5.67% decrease in preterm delivery rates in the pandemic cohort (P<.001; odds ratio [OR] 0.94, 95% CI 0.91-0.96), a 30.0% increase in home birth rates (P<.001; OR 1.3, 95% CI 1.23-1.4), and a 7.81% decrease in the average hospital length of stay postdelivery (mean 2.48 days, SD 1.35). There were no overall changes in Cesarean section rates between cohorts, but differences were observed between age, race, and ethnicity subgroups. CONCLUSIONS: Results suggest a need for continuous monitoring of maternal health trends as the COVID-19 pandemic progresses and underline the important role of digital data collection, particularly during the pandemic.

3.
Fertil Steril ; 112(3): 450-457.e3, 2019 09.
Article in English | MEDLINE | ID: mdl-31272722

ABSTRACT

OBJECTIVE: To investigate the validity of self-reported fertility data generated by a mobile application-based cohort in comparison with data collected by traditional clinical methodologies. DESIGN: Data were collected from July 2013 to July 2018 through a mobile application designed to track fertility. Bayesian hierarchical models were used to assess day-specific pregnancy probabilities. Descriptive statistics were used to estimate differences in day of ovulation and lengths of menstrual phases and to assess changes in the cervix and ovulation-related symptoms drawing closer to the day of ovulation. SETTING: Not applicable. PATIENT(S): Data consisted of 225,596 menstrual cycles from 98,903 women. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Day-specific probabilities of pregnancy, variability in lengths of the follicular and luteal phases, trends in prevalence of symptoms and cervix changes across the fertile window. RESULT(S): Analyses were consistent with established clinical knowledge. Probability of conception was highest during the 5 days before and day of ovulation, with the highest probability occurring the day before ovulation. The average cycle length was 29.6 days, and average lengths of the follicular and luteal phases were 15.8 and 13.7 days, respectively. Closer to day of ovulation, women were more likely to report changes in the cervix corresponding to fluid consistency, feel, position, and openness and symptoms associated with ovulation, including pelvic pain, tender breasts, increased sex drive, and cramps. CONCLUSION(S): Components of the menstrual cycle and fertile window, when re-evaluated with a mobile application-based cohort, were found to be consistent with established clinical knowledge, suggesting an agreement between traditional and modern data collection methodologies.


Subject(s)
Fertility/physiology , Fertilization/physiology , Menstrual Cycle/physiology , Mobile Applications/standards , Ovulation Detection/methods , Ovulation Detection/standards , Adolescent , Adult , Cohort Studies , Female , Follow-Up Studies , Humans , Pregnancy , Pregnancy Outcome/epidemiology , Self Report , Young Adult
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