Improving Equity in Access to Appointments: Impact of Spanish-Language Fast Pass Messaging in an Academic Health System

Objective: Patients with limited English proficiency often face barriers to accessing timely care. We evaluated whether Spanish-language Fast Pass messaging, combined with two-way Short Message Service (SMS) functionality, increased appointment acceptance rates among Spanish-preferring patients while maintaining equitable outcomes for English-preferring patients. Methods: A pre/post-quality improvement project was conducted at Mayo Clinic from November 2023 to June 2025. Epic’s Fast Pass, an automated appointment waitlist system, was enhanced with Spanish-language templates and bidirectional SMS in lieu of patient portal utilization. The primary outcome was the Fast Pass acceptance rate for Spanish-preferring patients. Balancing measures included acceptance among English-preferring patients. Secondary outcomes included scheduler efficiency and cost savings. Results: Prior to implementation, Spanish-preferring patients accepted 4.69% of Fast Pass offers compared with 7.57% for English-preferring patients. Post-implementation, acceptance rates for Spanish-preferring patients increased from 4.69% to 8.05%, a 71.6% improvement in the acceptance rate, exceeding the initial target of a 7.57% acceptance rate. Acceptance rates for English-preferring patients also improved, rising from 7.57% to 9.5%, or a 25.5% improvement in the acceptance rate. The intervention resulted in 344 additional Spanish-language accepted appointments and 29,883 additional English-language accepted appointments, both measured by unique patient appointments. The intervention also improved operational efficiency, saving more than 4,000 hours of scheduler time and reducing scheduling-related costs. Conclusions: Spanish-language concordant and SMS-enabled Fast Pass messages improved patient equity in appointment access while increasing scheduling efficiency and reducing operational costs. Health systems should adopt language-concordant digital communication strategies. Future research should expand to include additional languages and explore artifical intelligence–based scheduling support.