FW-HTF-P: Understanding the Social and Ethical Implications of Algorithmic Decision Making by Nurses Using the Rothman Index in a Large-Scale Hospital Setting

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With a shift towards value-based care, healthcare organizations are seeking innovative ways to improve the quality of care while reducing costs. The next several decades will see a rise in algorithm-driven patient care and the widespread use of data-driven warning systems such as the Rothman Index. The Rothman Index is an algorithmic system that uses patient information, lab results, and other health-related data to predict health deterioration. Algorithmic systems such as the Rothman will undoubtedly change what it means to daily work in the field of healthcare, demanding new kinds of expertise and communication from an already over-extended workforce. While such systems may reduce staffing needs, they do not eliminate the need for human oversight and intervention. Understanding how traditionally trained healthcare practitioners interact with such systems is, therefore, vital for the successful implementation of algorithmic patient care. To accomplish this goal, this project seeks to expand our understanding of how nurses in the Virtual Intensive Care Unit (VICU) make algorithmically informed workplace decisions using the Rothman Index. More broadly, the project examines how healthcare workers mediate between algorithms and patient interaction. Consequently, it informs future training protocols, system redesign and revision, and overall optimization of similar futuristic algorithmic tools. This project will employ a participatory and worker-centered design process for implementing algorithmic patient care through close collaborations with healthcare workers to advance the technical design of the Rothman Index. It will focus on the experiences of the virtual nurses, the providers who currently mediate between the Rothman Index alerts and health practitioners on the floor, in making actual algorithmic decisions. The project’s foundation is relationship-building with relevant hospital stakeholders followed by collecting and analyzing preliminary data about experiences with the Rothman Index in the VICU work environment, including observations and interviews with virtual nursing staff and deidentified quantitative usage data extracted from the Rothman Index system. Drawing on preliminary findings, hospital stakeholders will be engaged in participatory design to improve workplace protocols and practices around algorithmic decision making. Subsequently, this project will inform three fundamental research challenges: (1) technical communication research on how cognition and memory facilitate workplace writing processes and the impacts of electronic systems on patient-provider and provider-provider communication; (2) organizational research on the synergistic mechanisms that successfully enable VICU; and (3) computer science research on the social and ethical implications of algorithmic interventions such as the Rothman Index. Furthermore, this research will open door to studying many related problems: (a) feasibility of algorithmic patient care for preventative population outreach programs; (b) predictions of job displacements caused by algorithmic patient care implementation and anticipatory workforce training; (c) future algorithmic design for healthcare workplaces.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.