Screening to understand pregnancy preferences and offer referrals and treatment (SUPPORT): Results of a pilot quality improvement initiative

Abstract

Objective To assess the feasibility of integrating a pregnancy intention assessment screening algorithm into the electronic medical record (EMR) at a multispecialty clinic focused on the health of women and people assigned female at birth (AFAB). Study design This pilot quality improvement project implemented a series of clinician reminders, new data fields in the patient record, and templated clinical notes to prompt care providers across specialties to ask AFAB reproductive age individuals about their desire for future pregnancies. Investigators created a novel screening question based on prior literature and expert input. Prospective observational study of one year of during-intervention EMR data on screening uptake and documentation, contraceptive use, and referrals to obstetrics and gynecology (OBGYN) for preconception care, contraceptive care, and related services. Results SUPPORT launched in February 2020 and was paused for 6 months due to the COVID-19 pandemic. During the intervention period through July 2021, 18% of patients for whom the automated screening reminder was activated had a documented pregnancy intention. Patients were screened in OBGYN, internal medicine, and eight subspecialty medical clinics. Among those screened, individuals who reported they did not desire pregnancy in the next year were more likely to use contraception (aOR 1.8, 95% CI 1.1, 3.1). Individuals that did desire pregnancy in the next year were more likely to be subsequently referred to OBGYN (aOR 2.7, 95% CI 1.2, 6.0). Conclusions Despite the competing demands of the COVID-19 pandemic, the SUPPORT intervention was utilized at higher rates than prior similar interventions and across multiple disease specialties. Implications Results from the SUPPORT pilot suggest that pregnancy intention screening of reproductive age AFAB individuals with an EMR-based screening prompt is feasible at scale.