Patient Preferences for Receiving Test Results at San Francisco Bay Area Free Clinics: A Multi-Site Evaluation - Gururangan, Kapil; Shin, Jane Hae Soo; Shi, Yangyang; Ye, Patrick Peiyong; Vaca, Silvia Daniella; Gopisetty, Divya; Leon, Daniel Sotelo; Leyden, Jacinta; Lin, Steven (Journal of Student-Run Clinics, 2019)
Background: Laboratory follow-up is a critical aspect of patient care, and clinicians and patients communicate via both in-person and remote channels. Patient preferences for different modalities and the impact of experiencing in-person versus phone follow-up on future preferences are not well understood, especially in safety net settings. Methods: We conducted a survey of 235 patients at two San Francisco Bay Area student-run free clinics to ascertain patient preferences for in-person and phone follow-up. We determined the clinical complexity of laboratory follow-up and overall patient care by conducting a chart review of 113 surveyed patients who received lab results and all 579 patients who received care at either clinic. Results: Patients naÃ¯ve to laboratory follow-up reported similar preferences for in-person (32%) and phone (36%) follow-up (p=0.58). Patients who received results in-person subsequently reported a greater preference for future in-person follow-up (65%, p=0.003), whereas preference for phone follow-up (43%, p=0.69) did not shift after experiencing this modality. Patients with more complex follow-up (e.g., altering medications or ordering additional diagnostic studies, versus routine health counseling) reported a greater preference for receiving results in-person (p=0.013) and a lower preference for receiving results by phone (p=0.036). Conclusions: Patientsâ€™ preferences for receiving test results shift significantly after experiencing certain modalities (i.e., in-person) but not others (i.e., phone), and these shifts may be associated with the clinical complexity of laboratory follow-up. Future research should explore the utility of these findings in personalizing laboratory follow-up to optimize care delivery and quality in safety net settings.