Automatic Enrollment in Patient Portal Systems Mitigates the Digital Divide in Healthcare: An Interrupted Time Series Analysis of an Autoenrollment Workflow Intervention.

Autor: Milanfar L; School of Medicine, University of California, San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, United States of America. leila.milanfar@ucsf.edu., Soulsby WD; Department of Pediatrics, Division of Pediatric Rheumatology, University of California, San Francisco, San Francisco, CA, United States of America., Ling N; Department of Pediatrics, Division of Pediatric Rheumatology, University of California, San Francisco, San Francisco, CA, United States of America., O'Brien JS; Department of Pediatrics, Division of General Pediatrics, University of California, San Francisco, San Francisco, CA, United States of America., Oates A; Department of Pediatrics, Division of Pediatric Nephrology, University of California, San Francisco, San Francisco, CA, United States of America., McCulloch CE; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States of America.
Jazyk: angličtina
Zdroj: Journal of medical systems [J Med Syst] 2024 Oct 08; Vol. 48 (1), pp. 94. Date of Electronic Publication: 2024 Oct 08.
DOI: 10.1007/s10916-024-02114-7
Abstrakt: Purpose: 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.
Materials and Methods: 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.
Results: 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.
Conclusion: 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.
(© 2024. The Author(s).)
Databáze: MEDLINE
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