Bringing D&I Science to Early Interventions in Pediatric Hospital Medicine

Dissemination and implementation (D&I) science supports the spread and adoption of interventions with a traditional focus on those backed by strong clinical evidence.1 Many definitions go further, positioning D&I science as a way to promote the use of evidence-based practices—typically those supported by rigorous clinical effectiveness trials—in routine care.2,3 But, in practice, urgency often outpaces the availability of high-quality evidence, a tension not unique to pediatric hospital medicine.4 We argue that D&I science can be applied earlier in the life cycle of interventions, not to replace clinical effectiveness research, but rather to support structured learning and real-time evaluation.In most settings, teams frequently move forward with interventions based on patient safety concerns, operational priorities, opinion-based guidelines, or external pressures complicated by the lack of clearly superior alternatives. When these efforts go unevaluated, we miss opportunities to improve design, measure impact, and contribute to the broader knowledge base. Early application of D&I science makes sense under these conditions, especially when the intervention has plausible value grounded in available evidence, real-world experience,1 and subject matter expertise. Although we absolutely need to continue expanding the clinical effectiveness research base in pediatric hospital medicine, we also need to apply discipline and rigor to the promising early interventions already happening around us. D&I science offers tools that help us do exactly that.Strict definitions of the term “evidence-based” only complicate this conversation. Evidence of what? Compared to what? If we limit the term to interventions backed by patient-centered outcomes from controlled, comparative trials, very few tools or programs in pediatric hospital medicine qualify.5,6 Exclude studies that use biomarkers, system outcomes, or quality-of-life measures, and the list gets even shorter. Exclude those without a comparison group or superiority design, and we’re left with only a small subset, often aligned with the priorities of well-funded research programs but not necessarily with the immediate needs of our patients or health systems. The idea that we can identify a clinical problem, start fresh, and work our way through the traditional research pipeline before acting does not reflect the reality of pediatric care.7,8 And if the average research-to-practice timeline is 15 to 17 years,9 many of the patients who could have benefited from an innovation will not be around to see it implemented in practice.This is where early use of D&I science can add value. The goal is not to shortcut evidence generation, but rather to support it. Tools like the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework help teams understand whether an intervention is working, how it’s working and under what conditions, and what that means for future efforts.10,11 Each RE-AIM dimension offers specific insights that are especially useful in the early stages of an intervention’s development. Reach focuses on whether the intervention is engaging the intended population. For early interventions, assessing reach can help ensure that the team is targeting the right groups before broader rollout. Effectiveness tracks the impact on outcomes that matter and allows teams to link those early clinical effectiveness signals to how the intervention was delivered. Adoption captures the willingness of key individuals, teams, or institutions to use the intervention, offering important context for potential spread. Implementation covers fidelity, adaptations made during delivery, and costs, providing practical insights for future optimization.12Maintenance looks at sustainability and long-term integration, key considerations when deciding whether to invest further. Used together, these dimensions offer a structure for learning that can inform both local improvement and broader evidence development.Consider a hospital confronting unacceptably high emergency transfer rates.13 After reviewing literature and learning from peers, the team identifies a Watcher Program as a promising option to enhance shared situation awareness and improve team-based care escalation. There is no randomized trial to support it, but experience from other sites and early data offer enough reason to act.14 With no other strong alternatives and real patient risk, the team implements the program as part of its safety strategy. The rollout is comprehensive—touching workflows, technology, and training across disciplines and settings. Some iteration is expected, but the goal is broad implementation from the start. Applying a D&I framework at this stage helps the team approach rollout deliberately, evaluate if it can be feasibly and sustainably implemented, monitor how the program functions in context, ensure it reaches key populations, and adapt it as needed. Just as importantly, it creates a foundation for future effectiveness work. Studying implementation does not get in the way of evaluating effectiveness—it strengthens it. In fact, RE-AIM has been productively used in early-stage intervention development and evaluation in other fields.15Several research strategies align with this approach, and we advocate for their wide-scale pursuit. Pragmatic trials evaluate interventions in real-world conditions.16 Hybrid trial designs explicitly combine effectiveness and implementation measures, with Types 1, 2, and 3 varying by emphasis.1,17 Learning health systems embed feedback loops into care delivery to facilitate continuous, data-driven improvement and innovation.18 Adaptive or active implementation strategies make space for course correction based on learnings about implementation barriers.19 Each of these approaches offer opportunities to apply D&I science earlier to promising interventions. Even quality improvement efforts—especially those tied to larger-scale interventions—increasingly benefit from applying D&I methods to support structured evaluation and increase the generalizability of findings.20That said, applying D&I science to early interventions requires judgment. High-cost, high-impact efforts demand greater D&I rigor. Lower-risk initiatives may warrant nimbler D&I evaluation aligned with small-scale testing and quality improvement principles. The key is matching evaluation intensity to the level of risk, scale, and anticipated impact. We are not arguing that D&I science universally accelerates the production of clinical effectiveness evidence but rather that it supports evidence generation in context, providing insight early, helping teams adjust, and setting the stage for larger trials when appropriate. We also do not advocate for the application of D&I science to justify low-value or poorly conceived practices. In fact, we believe D&I science helps teams bring discipline and structure to the interventions already moving forward due to necessity or urgency. Many of these efforts will proceed with or without formal study. D&I science gives us a way to learn from them, understand what works, and improve what does not.In pediatric hospital medicine, many interventions emerge out of necessity rather than certainty. Instead of waiting for the ideal evidence base to materialize, we need ways to bring discipline to what is already being implemented. Applied thoughtfully, D&I science supports structured learning, contextual understanding, and evidence generation in real time. By using D&I science earlier in the life of an intervention, we can better understand what is working, for whom, and under what conditions, narrowing the gap between action and understanding without compromising either.