COVID-19 in pregnancy: Creating an outpatient surveillance model in a public hospital system

Abstract

We describe a standardized, scalable outpatient surveillance model for pregnant women with COVID-19 with several objectives: (1) to identify and track known, presumed, and suspected COVID-positive pregnant patients both during their acute illness and after recovery, (2) to regularly assess patient symptoms and escalate care for those with worsening disease while reducing unnecessary hospital exposure for others, (3) to educate affected patients on warning symptoms, hygiene, and quarantine recommendations, and (4) to cohort patient care, isolating stable infected patients at home and later within the same physical clinic area upon their return to prenatal care. Pregnant women in an urban public hospital system with presumed or confirmed COVID-19 were added to a list in our electronic medical record as they came to the attention of providers. They received a series of phone calls based on their illness severity and were periodically assessed until deemed stable. A total of 83 patients were followed between March 19 and May 31, 2020. Seven (8%) were asymptomatic, 62 (75%) had mild disease, 11 (13%) had severe disease, and three (4%) had critical illness. We encourage others to develop and utilize outpatient surveillance systems to facilitate appropriate care and to optimize maternal and fetal well-being.