ArtsRx as an arts prescribing model: leveraging CRM data to understand participation and engagement

Introduction Arts prescribing programs, through which health and social care providers refer patients to arts-based activities to support health and wellbeing, are emerging in the United States but remain heterogeneous in design and implementation. Moreover, many community-based models lack consistent, technology-enabled engagement tracking systems for tracking attendance, engagement, and longitudinal participation, limiting evaluation and quality improvement. To address this gap, ArtsRx, a program developed and managed by an anchor cultural institution in New Jersey, leverages a customer relationship management (CRM) platform to capture real-time registration, attendance, and engagement data. This study presents a 2-year analysis of ArtsRx participation patterns and modifiers of engagement. Methods This retrospective observational study was done via quantitative analysis of de-identified records for 498 individuals referred to ArtsRx between 2023 and 2025. Data extracted from the program's CRM were used to categorize engagement (no, low, medium, high). Descriptive statistics were calculated for engagement rates and examined by demographic characteristics (age, race/ethnicity, gender) and referral source. Results Among 498 participants, 21.9% completed the program, 45.7% withdrew, 19.3% remained enrolled, and 13.1% submitted an intake form without fully enrolling. Engagement analyses focused on 336 participants who completed or withdrew. Completers attended a mean of 78.2% of scheduled activities, compared with 8.7% among withdrawn participants. Engagement level was associated with program year and referral source but not with race/ethnicity or gender; referral patterns varied by program year and participant demographics. Conclusions This analysis demonstrates the feasibility of a CRM-based platform for monitoring engagement in U.S. arts prescribing programs. Participation patterns indicate consistent engagement across demographic groups, with variations linked to referral pathways and program year. These findings support the use of technology-enabled infrastructure for strengthening and scaling arts prescribing models within health and community care systems.