- Wells, Rachel D;
- Guastaferro, Kate;
- Azuero, Andres;
- Rini, Christine;
- Hendricks, Bailey A;
- Dosse, Chinara;
- Taylor, Richard;
- Williams, Grant R;
- Engler, Sally;
- Smith, Charis;
- Sudore, Rebecca;
- Rosenberg, Abby R;
- Bakitas, Marie A;
- Dionne-Odom, J Nicholas
Recent systematic reviews and meta-analyses have reported positive benefit of multicomponent "bundled" palliative care interventions for patients and family caregivers while highlighting limitations in determining key elements and mechanisms of improvement. Traditional research approaches, such as the randomized controlled trial (RCT), typically treat interventions as "bundled" treatment packages, making it difficult to assess definitively which aspects of an intervention can be reduced or replaced or whether there are synergistic or antagonistic interactions between intervention components. Progressing toward palliative care interventions that are effective, efficient, and scalable will require new strategies and novel approaches. One such approach is the Multiphase Optimization Strategy (MOST), a framework informed by engineering principles, that uses a systematic process to empirically identify an intervention comprised of components that positively contribute to desired outcomes under real-life constraints. This article provides a brief overview and application of MOST and factorial trial design in palliative care research, including our insights from conducting a pilot factorial trial of an early palliative care intervention to enhance the decision support skills of advanced cancer family caregivers (Project CASCADE).