CHI 2024
Analyzing patient-provider communication through social signals like dominance, interactivity, engagement, and warmth can help improve care by identifying opportunities for better interactions. We introduce a machine-learning pipeline embedded in ConverSense, a web application that visualizes communication patterns across visits. A user study with clinicians and patients highlights its potential to provide actionable, context-specific feedback for enhancing communication quality and patient outcomes.
CHI 2024
Implicit bias among healthcare providers can negatively impact care quality and patient outcomes, necessitating tools to identify and address these biases. Through design sessions with 24 primary care providers, we found they prefer feedback with transparent metrics, trends across visits, and actionable tips presented in a dashboard. These insights can guide the development of interactive systems to support equitable healthcare, especially for marginalized communities.
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.
CHI 2021In this paper, we describe ARTEMIS' design process with a summary of specific user goals ARTEMIS addresses. We also describe the system implementation and show an early validation of how the system addresses user goals.
CHI 2021 This paper presents a 2x2 mixed factorial experiment that explores the effects of providing spatial information and system-generated guidance to task objects. It also investigates the effects of such guidance on the remote collaborators need for spatial information.
CHI 2021 Co-location matters, especially when running collaborative design thinking workshops. What if participation cannot occur in person? How can we conduct these workshops remotely?