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使用多语言人工智能护理代理来减少结直肠癌筛查中的差异,以提高西班牙语患者对粪便免疫化学检测的接受度:回顾性分析。

Using a Multilingual AI Care Agent to Reduce Disparities in Colorectal Cancer Screening for Higher Fecal Immunochemical Test Adoption Among Spanish-Speaking Patients: Retrospective Analysis.

作者信息

Bhimani Meenesh, Baker R Hal, Ausin Markel Sanz, Meixiong Gerald, Lasko Rae, Raglow-Defranco Mariska, Miller Alex, Mukherjee Subhabrata, Godil Saad, Cook Anderson, Agnew Jonathan D, Atreja Ashish

机构信息

Hippocratic AI, Palo Alto, CA, United States.

WellSpan Health, York, PA, United States.

出版信息

J Med Internet Res. 2025 Jun 25;27:e71211. doi: 10.2196/71211.

Abstract

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

摘要

背景

与非西班牙裔白人相比,西班牙裔和拉丁裔人群的结直肠癌(CRC)筛查率仍然低得不成比例。虽然人工智能(AI)在医疗服务中显示出前景,但人们担心基于AI的干预措施可能因开发和部署中的偏差而对非英语人群不利。

目的

本研究旨在评估多语言AI护理代理与说英语的患者相比,在促使说西班牙语的患者进行CRC筛查方面的有效性。

方法

这项回顾性分析考察了2024年9月在宾夕法尼亚州和马里兰州的韦尔斯潘健康中心开展的一项由AI驱动的外展倡议。该研究纳入了1878名有资格进行CRC筛查但缺乏活跃的基于网络的健康档案的患者(517名说西班牙语的患者,1361名说英语的患者)。一个多语言AI对话代理以患者偏好的语言进行个性化电话呼叫,以提供有关CRC筛查的教育,并协助请求粪便免疫化学检测(FIT)试剂盒。主要结局是FIT检测选择加入率,次要结局包括接通率和通话时长。统计分析包括描述性统计、双变量比较和多变量逻辑回归分析

结果

在FIT检测选择加入率(18.2%对7.1%,P<0.001)、接通率(69.6%对53.0%,P<0.001)和通话时长(6.05对4.03分钟,P<0.001)方面,说西班牙语的患者在所有指标上的参与度均显著高于说英语的患者。在人口统计学上,说西班牙语的患者更年轻(平均年龄57岁对61岁,P<0.001),且更可能为女性(49.1%对38.4%,P<0.001).在多变量分析中,在控制了人口统计学因素和通话时长后,西班牙语偏好仍然是FIT检测选择加入的独立预测因素(调整后的优势比为2.012,95%置信区间为1.340 - 3.019;P<0.001)。

结论

由AI驱动的外展活动在说西班牙语的患者中实现了显著更高的参与度,这挑战了技术干预措施必然对非英语人群不利的假设。说西班牙语患者的FIT检测选择加入率高出2.6倍,这与医疗保健差距中的历史模式明显不同。这些发现表明语言一致型AI交互可能有助于解决预防性医疗服务获取方面长期存在的差距。研究局限性包括其单一的医疗系统环境、短持续时间以及缺乏关于完成筛查的后续数据。未来的研究应评估长期依从性以及更高的参与度是否转化为改善的临床结局。

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