Patient Characteristics Associated With Optimal Telemedicine Experience in Maternal–Fetal Medicine (MFM) [ID: 1368093]

Abstract

INTRODUCTION: Data regarding patient satisfaction with telemedicine use in obstetrics are limited. Our objective was to identify demographics and their effect on patient satisfaction with telemedicine in maternal–fetal medicine (MFM) to better identify patients who may prefer this modality. METHODS: An IRB-approved prospective survey was offered to patients in MFM from March 2022 to May 2022. Telemedicine experience was not required. Demographics and responses to statements comparing telemedicine versus in-person appointments were collected via a 5-point Likert scale. Telemedicine was defined as an appointment where provider–patient interaction occurred via telecommunications technology. The primary outcome was patient characteristics associated with telemedicine satisfaction. Exploratory factor analysis was performed to identify components affecting patient satisfaction. RESULTS: Surveys were completed by 327 patients. Factor analysis yielded two components from eight statements: “attentiveness” from the provider and “technology” comfort. Telemedicine was viewed neutrally for attentiveness-related questions and favorably for technology-related questions. While both factors were significantly associated with desire for future telemedicine option, the effect of attentiveness was twice as strong as that of technology in multiple regression. Higher education level and being married were significantly associated with lower levels of perceived attentiveness. Employment and telemedicine experience were significantly associated with increased technology comfort. Those with telemedicine experience and higher technology comfort experienced statistically fewer connection problems. CONCLUSION: Telemedicine was viewed neutrally or favorably for the factors studied. Perceived provider attentiveness and technology comfort affected patient satisfaction with telemedicine; each is associated with certain patient demographics. Once validated, this scale can be used to identify patients who may prefer telemedicine appointments.