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We sought to assess the quality of race and ethnicity information in observational health databases, including electronic health records (EHRs), and to propose patient self-recording as an improvement strategy.

The study sought to explore online health communities (OHCs) for sexual minority women (SMW) with cancer by conducting computational text analysis on posts.

We aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or without structured race/ethnicity data.

Geriatric syndromes such as functional disability and lack of social support are often not encoded in electronic health records (EHRs), thus obscuring the identification of vulnerable older adults in need of additional medical and social services. In this study, we automatically identify vulnerable older adult patients with geriatric syndrome based on clinical notes extracted from an EHR system, and demonstrate how contextual information can improve the process.

Researchers conduct studies with selection biases, which may limit generalizability and outcomes of intervention research. In this methodological reflection, we examined demographic and health characteristics of implantable cardioverter defibrillator patients who were excluded from an informatics intervention due to lack of access to a computer and/or the internet.

The study sought to implement and assess the CommunityRx e-prescribing system to recruit research participants from a predominantly non-Hispanic Black community on Chicago's South Side.

Transgender people face substantial mental health disparities, and this population's emotional well-being can be particularly volatile during gender transition. Understanding gender transition sentiment patterns can positively impact transgender people by enabling them to anticipate, and put support in place for, particularly difficult time periods. Yet, tracking sentiment over time throughout gender transition is challenging using traditional research methods. This study's objective was to use social media data to understand average [...]

Determine whether women and men differ in volunteering to join a Research Recruitment Registry when invited to participate via an electronic patient portal without human bias.

Community health systems operating in remote areas require accurate information about where people live to efficiently provide services across large regions. We sought to determine whether a machine learning analyses of satellite imagery can be used to map remote communities to facilitate service delivery and planning.

To investigate the impact of health information technology (IT) systems on clinicians' work practices and patient engagement in the management and follow-up of test results.