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Healthcare providers’ implicit bias, based on patients’ physical characteristics and perceived identities, negatively impacts healthcare access, care quality, and outcomes. Feedback tools are needed to help providers identify and learn from their biases. To incorporate providers’ perspectives on the most effective ways to present such feedback, we conducted semi-structured design critique sessions with 24 primary care providers. We found that providers seek feedback designed with transparent metrics indicating the quality of their communication with a patient and trends in communication patterns across visits. Based on these metrics and trends, providers want this feedback presented in a dashboard paired with actionable, personalized tips about how to improve their communication behaviors. Our study provides new insights for interactive systems to help mitigate the impact of implicit biases in patient-provider communication. New systems that build upon these insights could support providers in making healthcare more equitable, particularly for patients from marginalized communities.
Affective computing improves rapidly, allowing systems to process human emotions. This enables systems such as conversational agents or social robots to show empathy toward users. While there are various established methods to measure the empathy of humans, there is no reliable and validated instrument to quantify the perceived empathy of interactive systems. Thus, we developed the Perceived Empathy of Technology Scale (PETS) to assess and compare how empathic users perceive technology. We followed a standardized multi-phase process of developing and validating scales. In total, we invited 30 experts for item generation, 324 participants for item selection, and 396 additional participants for scale validation. We developed our scale using 22 scenarios with opposing empathy levels, ensuring the scale is universally applicable. This resulted in the PETS, a 10-item, 2-factor scale. The PETS allows designers and researchers to evaluate and compare the perceived empathy of interactive systems rapidly.
In serious illness contexts, caregivers are often tasked to make values-based decisions for patients without decision-making capacity. However, most existing values elicitation tools are designed for patient use, which might not address caregivers’ unique needs. In this study, we developed five low-fidelity prototypes as probes to explore the design requirements for caregiver-facing values elicitation tools with 12 caregivers. Our findings indicate that caregivers need more support in reconciling various conceptions of patient values and their own values. Caregivers wanted to use the tools to build consensus among family members, but may prefer to use the online tool on their own rather than share the interface with other caregivers. Lastly, there is a prevalent lack of understanding of the importance of values in decision-making. From these insights, we draw some implications for the design of online tools for caregiver-facing values elicitation.
Smart hospital patient rooms integrate smart devices for digital control of both entertainment (e.g., television and sound system) and the environment (e.g., lights, blinds, and temperature). While primarily designed to enhance the patient experience, this technology also impacts the hospital employees who work in these patient rooms. This study explores hospital employee experiences with smart patient rooms. We conducted 23 interviews with rehabilitation healthcare professionals, including nurses, doctors, psychologists, and occupational, physical, and speech therapists, to understand their perspectives on working in smart patient rooms. Drawn from thematic analysis of the interviews, our findings offer insights into employees' current use of the technology, the benefits and drawbacks they encounter, and their suggestions for improving the technology. These findings shed light on the complex problem of building smart patient rooms that simultaneously support the needs of multiple stakeholders, including patients and employees; they also point to important considerations for future designs.
Clinical practice guidelines, care pathways, and protocols are designed to support evidence-based practices for clinicians; however, their adoption remains a challenge. We set out to investigate why clinicians deviate from the "Wake Up and Breathe" protocol, an evidence-based guideline for liberating patients from mechanical ventilation in the intensive care unit (ICU). We conducted over 40 hours of direct observations of live clinical workflows, 17 interviews with frontline care providers, and 4 co-design workshops at three different medical intensive care units. Our findings indicate that unlike prior literature suggests, disagreement with the protocol is not a substantial barrier to adoption. Instead, the uncertainty surrounding the application of the protocol for individual patients leads clinicians to deprioritize adoption in favor of tasks where they have high certainty. Reflecting on these insights, we identify opportunities for technical systems to help clinicians in effectively executing the protocol and discuss future directions for HCI research to support the integration of protocols into clinical practice in complex, team-based healthcare settings.