Neonatology Fellow, PGY-6 McGovern Medical School at the University of Texas Health Science Center at Houston Houston, Texas, United States
Background: Birth defects are the leading cause of infant death in the US, but survival has increased due to advancements in prenatal diagnosis and fetal intervention. Specialized Fetal Care Centers (FCC) manage these high-risk pregnancies and often track short-term pregnancy outcomes. Long-term follow-up data is lacking, partly due to the logistics and costs of in-person evaluations. An electronic system for remote collection of follow-up data is needed to better understand outcome predictors and compare data across centers. An automated system that allows for data collection via text message would be more accessible to patients and decrease the burden on patients and research staff. Objective: To assess the feasibility of using an automated database for collecting long-term outcome data at a large FCC in Houston, Texas. Design/Methods: This pilot study received IRB approval to enroll both retrospective and prospective cohorts. New or former FCC patients from 2011 onward are eligible, excluding women < 18 years old or non-English speakers. Patients are sent a link via text message to complete the consent and online questionnaires via REDCap®. Surveys will collect demographic and recent medical data and include validated tools such as The Ages & Stages Questionnaire®, Third Edition to screen for neurodevelopmental impairment, and the Pediatric Quality of Life Inventory® to assess the child’s health-related quality of life and family impact. Prospective patients will receive a survey link once their infant reaches 2 months of age, adjusted for prematurity. The specific surveys sent to retrospective patients will be based on the child’s current age at enrollment. This study utilizes a novel mechanism for survey scheduling which is completely automated and programmed into REDCap® using Boolean logic and R script. The recruitment goal is 40 per cohort, and feasibility will be established if the enrollment rate is ≥ 50% and survey completion rate is ≥ 70%, based on published thresholds in similar studies. Enrollment began October 2023 and completed datasets are expected by March 2024.
