COVID-19期间高危妊娠的远程医疗利用

Margie A Rayford, Joshua M Morris, Ramona Phinehas, Elizabeth Schneider, Amanda Lund, Sarah Baxley, Jim Y Wan, Patricia J Goedecke, Roberto Levi-D'Ancona
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摘要

目的:了解2019冠状病毒病(COVID-19)大流行期间远程医疗对产科高危患者预后的影响。方法:通过回顾性图表分析,确定2020年3月至2021年10月COVID-19大流行发病期间母婴医学(MFM)科患者的远程医疗和现场就诊模式。对于描述性分析,使用连续变量的Wilcoxon秩和和卡方或Fisher精确值(其中细胞n p)计算p值。结果:在研究期间,419名高风险患者通过亲自和/或远程医疗预约就诊:320名患者没有远程医疗就诊,99名患者有远程医疗就诊。远程医疗访问提供的护理与自我报告的种族(p = 0.81)、母亲体重指数(p = 1.0)或母亲年龄(p = 0.53)无关。私人保险患者比公共保险患者更有可能进行远程医疗访问(79.9% vs. 65.5%, p p p = 0.03),抑郁症(p p = 0.2)或妊娠结局(p = 0.12),包括死胎、早产或足月分娩,与所有在办公室就诊的患者相比。在多变量分析中,患者的焦虑状况(p p p = 0.04)与更高的远程医疗访问率相关。结论:有一定妊娠并发症的患者选择远程就诊较多。拥有私人保险的患者比拥有公共保险的患者更有可能进行远程医疗访问。对于患有某些妊娠并发症的患者来说,除了定期安排的亲自诊所就诊外,还包括远程保健就诊是有益的,并且可能也适用于大流行后的环境。需要在这一领域进行进一步研究,以更好地了解在产科高危患者中实施远程医疗的影响。
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Telehealth Utilization in High-Risk Pregnancies During COVID-19.
Purpose: To determine how telehealth has influenced outcomes in high-risk obstetrics patients during the Coronavirus disease 2019 (COVID-19) pandemic. Methods: A 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. 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. Variables of interest were then tested for their univariate association with telehealth utilization using logistic regression. 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. We aimed to analyze whether telehealth visits significantly impacted pregnancy outcomes. Results: Four 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. 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). Patients with private insurance were more likely to have telehealth visits than patients with public insurance (79.9% vs. 65.5%, p < 0.01). 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. 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 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. Conclusion: Patients with certain pregnancy complications elected to have more telehealth visits. Patients with private insurance were more likely to have telehealth visits than patients with public insurance. 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. Further research in this field is needed to better understand the impact of implementing telehealth in high-risk obstetrics patients.
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Correction to : “A Prioritized Patient-Centered Research Agenda to Reduce Disparities in Telehealth Uptake:Results from a National Consensus Conference” by Kristin L. Rising et al. Telemed Report 2023;4(1): 387–395; doi: 10.1089/tmr.2023.0051 The Impact of Waiting Times on Behavioral Outcomes for Children with Otitis Media: Results from an Urban Ear, Nose, and Throat Telehealth Service Factors Associated with the Digital Patient Experience of Virtual Care Across Specialties. Telemedicine in Brazil: Teleconsultations at the Largest University Hospital in the Country. Achieving Digital Health Equity by Personalizing the Patient Experience.
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