Nesbitt TS, Marcin JP, Daschbach MM, et al. Rayford et al., 2023 Published by Mary Ann Liebert, Inc. High risk obstetrics telehealth telemedicine. Further research in this field is needed to better understand the impact of implementing telehealth in high-risk obstetrics patients. There are benefits for patients with certain pregnancy complications to incorporate telehealth visits in addition to regularly scheduled in-person clinic visits and may be suitable in a post-pandemic setting as well. ![]() Patients with private insurance were more likely to have telehealth visits than patients with public insurance. Patients with certain pregnancy complications elected to have more telehealth visits. In multivariable analysis, patient conditions of anxiety ( p < 0.01), maternal obesity ( p < 0.01), and twin pregnancy ( p = 0.04) were associated with higher rates of telehealth visits. Those patients with telehealth visits did not have any statistical differences in mode of delivery ( p = 0.2) or pregnancy outcomes ( p = 0.12), including fetal demise, preterm delivery, or delivery at term as compared with patients with all in-office visits. In univariate logistic analyses, patients with diagnoses of anxiety ( p < 0.01), asthma ( p = 0.03), and depression ( p < 0.01), at the time care was established, were more likely to have telehealth visits. ![]() Patients with private insurance were more likely to have telehealth visits than patients with public insurance (79.9% vs. Care provided by telehealth visits was not found to be related to self-reported race ( p = 0.81), maternal body mass index ( p = 1.0), or maternal age ( p = 0.53). We aimed to analyze whether telehealth visits significantly impacted pregnancy outcomes.įour hundred nineteen high-risk patients visited the clinic via in-person and/or telehealth appointments during the study period: 320 patients without telehealth visits and 99 patients with telehealth visits. ![]() Variables found to meet the criterion of p < 0.2 in the univariate case were introduced into a multivariable logistic model with a backward elimination for determining variable retention. Variables of interest were then tested for their univariate association with telehealth utilization using logistic regression. For the descriptive analysis, p-values were calculated using Wilcoxon rank sum for continuous variables and chi-square or Fisher exact (where cell n < 5) for categorical variables. To determine how telehealth has influenced outcomes in high-risk obstetrics patients during the Coronavirus disease 2019 (COVID-19) pandemic.Ī retrospective chart review was conducted to identify patterns in both telehealth and in-person clinic visits among patients of a Maternal Fetal Medicine (MFM) department from the onset of the COVID-19 pandemic from March 2020 until October 2021.
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