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Background. Multiple studies have shown that digitally mediated decision aids help prepare patients for medical decision making with their providers. However, few studies have investigated whether decision-support preferences differ between non-English-speaking and English-speaking Latino men with limited literacy. Objective. To identify and compare health information seeking patterns, preferences for information presentation, and interest in digital decision aids in a sample of Southern Californian underserved Latino men with newly diagnosed prostate cancer at a county hospital. Methods. We conducted semistructured, in-depth telephone interviews with 12 Spanish-speaking and 8 English-speaking Latino men using a purposive sampling technique. Following transcription of taped interviews, Spanish interviews were translated. Using a coding protocol developed by the team, two bilingual members jointly analyzed the transcripts for emerging themes. Coder agreement exceeded 80%. Differences were resolved through discussion. Results. Thematic differences between groups with different preferred languages emerged. Most respondents engaged in online health information seeking using cellphones, perceived a paternalistic patient-provider relationship, and expressed willingness to use hypothetical digital decision aids if recommended by their provider. English speakers reported higher digital technology proficiency for health-related searches. They also more frequently indicated family involvement in digital search related to their condition and preferred self-guided, web-based decision aids. In comparison, Spanish speakers reported lower digital technology proficiency and preferred family-involved, coach-guided, paper and visual decision aids. English speakers reported substantially higher levels of formal education. Conclusion. Preferences regarding the use of digital technology to inform prostate cancer treatment decision making among underserved Latino men varied depending on preferred primary language. Effective preparation of underserved Latino men for shared decision making requires consideration of alternative approaches depending on level of education attainment and preferred primary language.

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Background: Referring patients to specialty care providers is an important function of a student-run free clinic. Selecting the appropriate referral site is a complex problem, as the criteria for eligibility are often very specific and frequently change. Mobile Clinic Project, a free clinic at University of California, Los Angeles, previously managed referral decisions by training a “referrals committee.” This committee maintained paper documentation on 140+ referral sites that was used to make on-site referral decisions. This approach was time consuming and subject to error. Our team aimed to build a web app to streamline the process of searching for the optimal referral site. Methods: A web app was created, and pilot testing was conducted to determine its efficacy in the hands of referrals committee members versus untrained clinic volunteers. After pilot testing, the app was released for use in the clinic, and a Likert survey was done at three months to assess its utility and usability. Results: The app, iRefer, allows users to electronically search information about referral sites and provides recommendations for the most appropriate sites based on patient information. Patient feedback about their visits to off-site providers can be incorporated into iRefer so that well-reviewed sites will be more highly recommended in future patient encounters. Additional features include the ability to print directions to the site directly from a volunteer’s phone and to track the number of times a particular referral site is recommended. Pilot testing of the app demonstrated that it allows users to make appropriate referral decisions with little training time required. Users viewed iRefer as an effective tool to improve the quality and efficiency of referrals at Mobile Clinic. Conclusions: A web app may be a technology-enabled tool for facilitating referrals at a student-run free clinic.