School of Medicine, University of California, San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, United States of America.
Department of Pediatrics, Division of Pediatric Rheumatology, University of California, San Francisco, San Francisco, CA, United States of America.
J Med Syst. 2024 Oct 8;48(1):94. doi: 10.1007/s10916-024-02114-7.
Racial and ethnic healthcare disparities require innovative solutions. Patient portals enable online access to health records and clinician communication and are associated with improved health outcomes. Nevertheless, a digital divide in access to such portals persist, especially among people of minoritized race and non-English-speakers. This study assesses the impact of automatic enrollment (autoenrollment) on patient portal activation rates among adult patients at the University of California, San Francisco (UCSF), with a focus on disparities by race, ethnicity, and primary language.
Starting March 2020, autoenrollment offers for patient portals were sent to UCSF adult patients aged 18 or older via text message. Analysis considered patient portal activation before and after the intervention, examining variations by race, ethnicity, and primary language. Descriptive statistics and an interrupted time series analysis were used to assess the intervention's impact.
Autoenrollment increased patient portal activation rates among all adult patients and patients of minoritized races saw greater increases in activation rates than White patients. While initially not statistically significant, by the end of the surveillance period, we observed statistically significant increases in activation rates in Latinx (3.5-fold, p = < 0.001), Black (3.2-fold, p = 0.003), and Asian (3.1-fold, p = 0.002) patient populations when compared with White patients. Increased activation rates over time in patients with a preferred language other than English (13-fold) were also statistically significant (p = < 0.001) when compared with the increase in English preferred language patients.
An organization-based workflow intervention that provided autoenrollment in patient portals via text message was associated with statistically significant mitigation of racial, ethnic, and language-based disparities in patient portal activation rates. Although promising, the autoenrollment intervention did not eliminate disparities in portal enrollment. More work must be done to close the digital divide in access to healthcare technology.
种族和民族医疗保健差异需要创新的解决方案。患者门户允许在线访问健康记录和临床医生的沟通,并且与改善健康结果相关。然而,在获得此类门户方面仍然存在数字鸿沟,特别是在少数族裔和非英语使用者中。本研究评估了自动注册(自动注册)对加利福尼亚大学旧金山分校(UCSF)成年患者患者门户激活率的影响,重点关注种族、族裔和主要语言的差异。
从 2020 年 3 月开始,通过短信向 UCSF 18 岁或以上的成年患者发送患者门户的自动注册优惠。分析考虑了干预前后患者门户的激活情况,检查了种族、族裔和主要语言的变化。使用描述性统计和中断时间序列分析来评估干预的影响。
自动注册增加了所有成年患者的患者门户激活率,少数族裔患者的激活率增加幅度大于白人患者。虽然最初没有统计学意义,但在监测期结束时,我们观察到拉丁裔(3.5 倍,p<0.001)、黑人(3.2 倍,p=0.003)和亚洲(3.1 倍,p=0.002)患者群体的激活率有统计学意义的增加与白人患者相比。与英语首选语言患者的增长相比,首选语言不是英语的患者的激活率随着时间的推移也呈统计学显著增加(13 倍,p<0.001)。
通过短信提供患者门户自动注册的基于组织的工作流程干预与患者门户激活率方面的种族、族裔和语言差异的统计学显著缓解相关。虽然有希望,但自动注册干预并没有消除门户注册方面的差异。必须做更多的工作来缩小获得医疗保健技术的数字鸿沟。