PROJECT SUMMARY Millions of Americans living with serious illness experience burdensome symptoms and receive aggressive care that is not aligned with their goals and preferences. Palliative care, which entails a supportive approach to care focused on maximizing quality of life, improves patient-centered, clinical, and economic outcomes for patients living with serious illness. For this reason, national guidelines recommend that palliative care is provided as part of standard serious illness care, and most hospitals in the U.S. have invested in specialist palliative care programs. Yet, it has become clear that relying on clinicians to consistently recognize unmet palliative care needs across different types of patients is impractical, and an important source of current inefficiencies and inequities in hospital palliative care delivery, and systematic changes are needed. For this reason, some hospitals have implemented screening criteria, or “triggers” in the electronic health record (EHR) to facilitate more reliable and equitable patient identification; however, current diagnostic- and prognostic- based criteria are nonspecific for unmet palliative care needs and exclude many patients with similar or greater needs. Automating palliative care needs-based triggers surmounts these limitations, but evidence of their real- world effectiveness to improve patient outcomes is needed. Further, it is not clear that a palliative care needs trigger alone – which merely provides clinicians information – will be sufficient to meaningfully change clinician behavior with regard to palliative care delivery. Thus, we hypothesize that a palliative care needs trigger in the EHR will improve both patient-centered outcomes and the equity of palliative care delivery compared with usual care, and that combining this trigger with an effective behavioral intervention (a default palliative care consult order) will improve these outcomes further compared with the trigger alone. We will conduct a hybrid type 1 pragmatic, cluster-randomized trial among more than 64,000 patients across 9 diverse hospitals to study the effectiveness of these interventions on hospital-free days and numerous other patient-centered and clinical outcomes, and the equity of palliative care consultation among different patient subgroups. During the trial, we will conduct an embedded mixed-methods study to quantitively assess each intervention's reach, adoption, implementation, and maintenance, and to qualitatively identify contextual factors and barriers to enhance the interpretation of the trial findings and translation to other hospital settings. Our trial design has several methodologic innovations, including a design that supports two randomized questions, a pre-planned Bayesian interpretation, and newer effect modification methods. By providing high-quality, comparative evidence of the real-world effectiveness, equity, and implementation of two scalable approaches to improve hospital palliative care delivery and patient-centered outcomes, this study will have a significant impact on palliative care research and practice, and will inform the optimal approach for other health systems to promote desired clinician behavior change to improve serious illness care.

PROJECT NARRATIVE Many Americans living with serious illness and unmet palliative care needs who could benefit from palliative care never receive it. This pragmatic trial will test the effectiveness of using an automated trigger in the electronic health record to identify hospitalized patients with unmet palliative care needs with and without an additional gentle nudge for clinicians to consider consulting palliative care. This study will also examine how these approaches impact the equity of palliative care consultation, and key implementation barriers and other contextual factors that may influence their effectiveness and translation to other health systems.