Traditional approaches for evaluating the impact of scientific research – mainly scholarship (i.e., publications, presentations) and grant funding – fail to capture the full extent of contributions that come from larger scientific initiatives. The Translational Science Benefits Model (TSBM) was developed to support more comprehensive evaluations of scientific endeavors, especially research designed to translate scientific discoveries into innovations in clinical or public health practice and policy-level changes. Here, we present the domains of the TSBM, including how it was expanded by researchers within the Implementation Science Centers in Cancer Control (ISC3) program supported by the National Cancer Institute. Next, we describe five studies supported by the Penn ISC3, each focused on testing implementation strategies informed by behavioral economics to reduce key practice gaps in the context of cancer care and identify how each study yields broader impacts consistent with TSBM domains. These indicators include Capacity Building, Methods Development (within the Implementation Field) and Rapid Cycle Approaches, implementing Software Technologies, and improving Health Care Delivery and Health Care Accessibility. The examples highlighted here can help guide other similar scientific initiatives to conceive and measure broader scientific impact to fully articulate the translation and effects of their work at the population level.

Organizations supporting translational research and translational science, including Clinical and Translational Science Award (CTSA) hubs, provide a diverse and often changing array of resources, support, and services to a myriad of researchers and research efforts. While a wide-ranging scope of programs is essential to the advancement of translational research and science, it also complicates a systematic and unified process for tracking activities, studying research processes, and examining impact. To overcome these challenges, the Duke University School of Medicine’s CTSA hub created a data platform, Translational Research Accomplishment Cataloguer (TRACER), that provides capacity to enhance strategic decision-making, impact assessment, and equitable resource distribution. This article reviews TRACER development processes, provides an overview of the TRACER platform, addresses challenges in the development process, and describes avenues for addressing or overcoming these challenges. TRACER development allowed our hub to conceptually identify key processes and goals within programs and linkages between programs, and it sets the stage for advancing evidence-based improvement across our hub. This platform development provides key insight into facilitators that can inform other initiatives seeking to collect and align organizational data for strategic decision-making and impact assessment. TRACER or similar platforms are additionally well positioned to advance the study of translational science.