AMIA 2023
Implicit biases in healthcare harm communication, decision-making, and care quality for marginalized patients. Through co-design workshops with 32 BIPOC, LGBTQ+, and QTBIPOC individuals, we identified four patient-centered solutions: accountability measures, real-time correction, enablement tools, and provider resources. These insights advance patient-focused approaches to addressing bias in care.
ASSETS 2022 To explore the potential opportunities for visualizing time-series based EMA data on standalone IVAs, we designed a prototype system, where older adults are able to query and examine the time–series EMA data on Amazon Echo Show — a widely used commercially available standalone screen–based IVA
EICS 2022 We present an exploratory study that uses iterative design to understand needs and opportunities to bring contour delineation into an immersive 3D space, such as the one enabled by today’s head-mounted VR displays
ASTRO 2022 Daily re-evaluation of contours associated with adaptive planning is time-intensive and difficult to access. This project evaluated the efficacy of everyday touch devices for contouring using a novel cross-platform interface.
CHI 2022 To understand the perspectives of clinicians on the design of effective educational strategies and for tools to help identify implicit bias, we conducted 21 semi-structured interviews with primary care clinicians about their perspectives and design recommendations for tools to improve patient-centered communication and to help mitigate implicit bias.
CHI 2022 - QT-BIPOC PD Workshop We present wireframes displaying communication metrics that negatively impact patient-centered care divided into the following categories: digital nudge, dashboard, and guided reflection. Our wireframes provide quantitative, real-time, and conversational feedback promoting provider reflection on their interactions with patients.