CRII: CHS: Novel Approaches for Real-Time Data Capture in Fast-Paced Medical Work

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Significant effort has been made to digitize medical documentation in order to provide a more accurate account of treatments and changes in patient status. Unlike clinicians providing ongoing care in hospital wards, emergency care providers engage in complex tasks that are unpredictable, time-critical, and cognitively consuming. More importantly, most of these tasks require their eyes and hands on the patient, rather than on a medical record. Emergency care work is inherently important to society as it involves life-threatening injuries and situations that affect people from all backgrounds. Improving the work efficiency of emergency care will lead to decreased medical errors and better patient outcomes. To this end, this research will develop novel tools and interaction techniques for real-time and hands-free data capture in fast-paced medical work. This project uses Emergency Medical Services (EMS) as an example domain to derive design requirements by determining how context-specific information should be captured and integrated in real time, to support the work of emergency medical teams while also accounting for their limited capacity to interact with handheld computing devices. The specific research contributions of this project will include: 1) a conceptual and empirical understanding of the information behaviors and temporal rhythms of emergency care providers collecting data during fast-paced medical work; 2) approaches for supporting real-time data capture and integration; 3) novel interaction techniques to reduce the physical and cognitive demands of using data capture tools; and 4) recommendations based on the development and evaluation of hands-free data capture prototypes in both simulated and real-world settings.This research has two main aims. The first aim is to gain a deeper understanding of the work practices, issues, and the technological needs around real-time data capture during fast-paced medical events. Understanding what, when, and how contextual information is currently being documented will inform the design of innovative approaches toward seamless and unobtrusive data capture. The researchers will pursue this objective by conducting fieldwork and video analyses. Building upon the findings, the second aim focuses on iteratively designing technological solutions to support rapid, hands-free data capture. The researchers will take a multi-phased, user-centered approach involving participatory design, rapid prototyping, and formative evaluation methods. Findings and design recommendations will be generalizable to multiple domains including information behaviors in time-critical work, human-computer interaction in environments where direct interaction with devices is limited, and designing for wearable technologies to support rapid data capture and integration from multiple sources. The conceptual insights and design recommendations derived through this project can potentially be applied in other settings facing similar challenges with real-time data capture and integration such as disaster response. This research will also establish an interdisciplinary education and outreach program by involving a diverse group of high school, undergraduate, and graduate students, most of whom are underrepresented minorities and first-generation immigrants.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.