The benefits of translational research (TR), which focuses on moving scientific discoveries from the laboratory settings to clinical applications for improved health outcomes, can be challenging to measure, as a TR enterprise intentionally spans across multiple domains. To address this and better communicate the positive effects and impacts of TR, various models and frameworks have been proposed. One frequently used model is the Translational Science Benefits Model (TSBM) (1, 2), which was developed to provide an organizing framework for conceptualizing and communicating the impact of TR.¹ The TSBM, in its origin, focuses on 30 measurable benefits across four domains that span the following content areas: clinical benefits, community benefits, economic benefits, and policy benefits. Clinical benefits include factors such as biomedical technology and diagnostic procedures. Community benefits encompass improvements in healthcare delivery quality. Economic benefits include patents and licenses, as well as cost savings. Policy benefits include legislative or standards changes and the provision of expert testimony.

The TSBM has been a core impact framework used to address the outcomes of TR. Clinical and Translational Science Award (CTSA) Hubs, which are supported by the National Institute for Health’s (NIH) National Center for Advancing Translational Sciences (NCATS), are designed to support and advance translational research. They have used the TSBM as a central mechanism for conceptualizing, assessing, and communicating the impact of their work; it has served as a basis for research impact assessment and has provided a framing for public communication of impact across numerous Hubs (3–5). Beyond the CTSA utilization, TSBM utility has informed similar efforts in multiple other research entities and studies; for instance, the Centers for Diabetes Translation Research (CDTR) adapted the TSBM to develop its Research Impact Framework, and the QUARTET USA trial, a randomized study on hypertension treatment, utilized the TSBM to assess its impact across clinical and community domains (6, 7). The original TSBM publication by Luke et al. (1), has shown a clear scholarly impact with an upward trajectory in its citations over time. Citations more than doubled in recent years—from 15 in 2018–2019 and rising sharply to 36 in 2024–early 2025—indicating growing recognition and increasing integration of the TSBM framework into the broader TR or translational science (TS) discourse.

The originally-published TSBM set the expectation that future use could employ it as an assessment framework, but it was not designed as a specific data collection process or organizational operational structure. However, over time, TSBM has been increasingly used to more directly assess impact. It has supported evaluation of training programs, helping junior investigators articulate broader benefits of their work, and been used to map implementation project outcomes to specific TSBM domains (8, 9). In addition, many institutions have created TSBM-based case studies (5, 10), often as ad hoc efforts focused on select projects, but newer guidance and tools for developing impact profiles more efficiently could support broader organizational adoption (11). The embedding of the TSBM into research training and institutional evaluation systems demonstrates its practical utility, beyond theoretical application, as a base for advancing and measuring the impact of TR.

The transition from a conceptual framework to an operationalized system that is concretely used across programmatic activities introduces new questions and considerations about the model. In this article, we identify three active processes within the Duke Clinical and Translational Science Institute (CTSI), which has advanced translational research and translational science via NCATS CTSA support and other funding sources, that employ the TSBM as a mechanism for collecting and organizing data on benefits. We then outline key considerations emerging from these cases that are relevant to using the TSBM as a structure for data collection on outcomes, and which provide opportunities to consider modifications or enhancements to the model itself. We focus on four considerations: who is collecting data, how potential outcomes are conceptualized and applied in measurement, potential limitations of TSBM use for programs (as compared to research projects), and potential limitations of TSBM use for examining TS (as compared to TR) impact. This publication offers key insights for using the TSBM as a data collection tool and highlights opportunities to expand its utility to understand, demonstrate, and augment the impact of TR and TS.

Below, briefly in text and with additional information in Figure 1, we identify and describe three distinct opportunities to utilize the TSBM including in concrete operational efforts (hereafter described as “use cases”). These use cases were selected because they represent primary mechanisms the Duke CTSI has integrated TSBM into organizational processes; because they each differ in their purpose and the ways the TSBM was operationalized, thereby representing variation in forms of TSBM application; and because each use case raised specific considerations and questions regarding TSBM operationalization, providing a diverse basis for subsequent (Section 3) discussion of these points. These represent application at the level of cases (projects, specific initiatives), program, and an institutional enterprise.

The application of the TSBM across these specific use cases described above—TSBM case studies focused on individual projects, the pilot grants program, and the enterprise-level TRACER program to assess knowledge translation impact in the hub—helped to reveal key critical considerations across these operationalizations. Below, we highlight four considerations with implications for integrating the TSBM into program processes; these address questions about “who” (who determines benefits), “how” (how one determines potential benefits), and “when/how” (when and how the TSBM works to different applications).

This work provides evidence for methods to integrate the TSBM into operational processes within entities supporting TR. The TSBM can be applied in commonly used case studies, but it can also be used in other ways. For instance, it can be used in funding award processes to preemptively consider potential outcomes, to utilize the TSBM as a basis for regular reporting during the grant period, and to continue ongoing toward longer-term tracking of research outcomes. This provides a way to integrate the TSBM across all stages of a funded project and across a research portfolio. Additionally, it can serve as a part of organizational and program-level tracking in an entity that seeks to advance TR, helping to systematically evaluate impact across an organization and inform strategic decision-making. While the TSBM is valuable as a conceptual framework, its utility is further enhanced when applied in concrete, operational contexts.

The operational use of the TSBM, while valuable, also highlights certain challenges or considerations for the use of the TSBM. Although these may be viewed as limitations, they also present opportunities for refinement and further development of the framework. In our experience, key challenges include definitional inconsistencies and lack of specificity (e.g., as relevant to the “who” and “how” considerations), which can lead to measurement difficulties; this speaks to potential issues in data quality and validity and to the importance of data standards and operational guidelines to aid in transforming TSBM from theory to practice. With this basis, our applications of the TSBM highlight the need for clearer definitions, such as specifying what constitutes a potential benefit, and suggest the addition of new indicators within the framework, such as incorporating economic benefits related to workforce development programs. Additionally, the TSBM may not be fully suited for certain areas of the TR enterprise, such as training and workforce development programs, nor for assessing more direct TS outcomes. This limitation is especially relevant to TS/TR entities that are placing greater emphasis on advancing TS, as is the case for CTSAs based on emphasis in the most recent CTSA Funding Opportunity Announcement (22); while the TSBM remains relevant to ongoing TR efforts and even some TS components, it does not necessarily capture the full range of TS impacts. These limitations suggest the need for additional or complementary frameworks to more fully assess TS impact. For example, the NCATS TS principles (23) or the Translational Science Promotion and Research Capacity (T-SPARC) framework (24), which includes proximal and distal indicators of TS impact in a logic model format, can provide useful foundations for refining and expanding future TS impact frameworks. Figure 2 utilizes the four considerations to provide lessons in the application of the TSBM in operational use.

Such advancements of a framework or model based on application across new contexts is consistent with framework and model development more broadly; in other fields, applying conceptual models and frameworks in applied uses has been essential for refining their applicability and enhancing their impact in healthcare and medical research. For instance, within implementation science, the RE-AIM framework has developed and refined over time based on its use across public health, clinical, and community-based settings (25). Similarly, the Consolidated Framework for Implementation Research use identified the need for more explicit considerations of sustainability within the framework (26, 27). These adaptations have improved the framework’s ability to guide the design and evaluation of implementation strategies in various healthcare contexts. Similarly, very recently, the TSBM has begun to be adjusted or augmented. For instance, recent work expands the TSBM to formally include additional indicators, and additional research offers modifications for an implementation science application (9, 28, 29). Additional work has developed the model by integrating key tenets from engagement science (30), demonstrating processes for adapting the TSBM by directly linking it to other aligned conceptual work. Shifts to the TSBM, informed by our work, can guide additional future enhancements and modification opportunities.

Beyond development of the model itself, the work presented in this paper builds upon other emerging developments informing operational use of the TSBM. For example, recent efforts to develop and provide initial validation of an instrument assessing TSBM benefits have introduced greater specificity and clarity to key indicators, which could enhance consistency in implementation across different systems (31). This, combined with added specificity in defining what comprises a potential impact, could help to create greater validity and reliability to TSBM measurement and enhance potential for system-wide applications. Additional work on the TSBM, including studies featured in this special issue, represents important steps toward refining its applications, identifying limitations, and expanding its scope and utility. We recommend future work that continues to apply the TSBM in practical and operational contexts, both to maximize its impact in real-world settings and to identify ways in which the model can be continually improved and refined.