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Using a Multilingual AI Care Agent to Reduce Disparities in Colorectal Cancer Screening: Higher FIT Test Adoption Among Spanish-Speaking Patients (Preprint)

预印本 考试(生物学) 结直肠癌 医学 老年学 家庭医学 癌症 万维网 心理学 计算机科学 内科学 古生物学 生物
作者
Meenesh Bhimani,Roger Baker,Markel Sanz Ausin,Gerald Meixiong,Rae Lasko,Mariska Raglow-Defranco,Alex Miller,Subhabrata Mukherjee,Saad Godil,A. I.M. Cook,Jonathan D. Agnew,Ashish Atreja
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
标识
DOI:10.2196/71211
摘要

Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations compared to non-Hispanic White populations. While artificial intelligence (AI) shows promise in health care delivery, concerns exist that AI-based interventions may disadvantage non-English-speaking populations due to biases in development and deployment. This study aimed to evaluate the effectiveness of a multilingual AI care agent in engaging Spanish-speaking patients for CRC screening compared to that with English-speaking patients. This retrospective analysis examined an AI-powered outreach initiative at WellSpan Health in Pennsylvania and Maryland during September 2024. The study included 1878 patients (517 Spanish-speaking, 1361 English-speaking) eligible for CRC screening who lacked active web-based health profiles. A multilingual AI conversational agent conducted personalized telephone calls in the patient's preferred language to provide education about CRC screening and facilitate fecal immunochemical test (FIT) kit requests. The primary outcome was the FIT test opt-in rate, with secondary outcomes including connect rates and call duration. Statistical analysis included descriptive statistics, bivariate comparisons, and multivariate logistic regression. Spanish-speaking patients demonstrated significantly higher engagement across all measures than English-speaking patients with respect to FIT test opt-in rates (18.2% vs 7.1%, P<.001), connect rates (69.6% vs 53.0%, P<.001), and call duration (6.05 vs 4.03 minutes, P<.001). Demographically, Spanish-speaking patients were younger (mean age 57 vs 61 years, P<.001) and more likely to be female (49.1% vs 38.4%, P<.001). In multivariate analysis, Spanish language preference remained an independent predictor of FIT test opt-in (adjusted odds ratio 2.012, 95% CI 1.340-3.019; P<.001) after controlling for demographic factors and call duration. AI-powered outreach achieved significantly higher engagement among Spanish-speaking patients, challenging the assumption that technological interventions inherently disadvantage non-English-speaking populations. The 2.6-fold higher FIT test opt-in rate among Spanish-speaking patients represents a notable departure from historical patterns of health care disparities. These findings suggest that language-concordant AI interactions may help address longstanding disparities in preventive care access. Study limitations include its single health care system setting, short duration, and lack of follow-up data on completed screenings. Future research should assess long-term adherence and whether higher engagement translates to improved clinical outcomes.
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