Table 4 Results from inductive analysis for themes related to spread/scale

Aligning affordability and scalability:

Intervention studies are typically resource-intensive and high cost, which can be barriers to scaling-up

Although the added costs of such resource-intensive support [intensive training, site-visits etc.] can be maintained during research evaluations, it is challenging to incorporate these costs into a business model that enables sustainable, scalable provision of the service. [47]

Routinely collected, accumulating data in administrative data sets offers a cost-effective opportunity to implement and evaluate antimicrobial stewardship interventions at scale across large populations. [60]

A key advantage of automated feedback interventions is that the cost of scaling delivery across entire health systems is much less than for more intensive interventions. [54]

Balancing fidelity and scalability:

Maintaining fidelity to the initial study is not always feasible at scale, particularly for complex interventions

There are questions about whether more complex interventions can be scaled successfully and feasibly, since they are often resource intensive. [61]

Our intervention, … shows that the favourable results of earlier work could not be replicated. It appeared that large-scale uptake of evidence-based but complex implementation strategies with a minimum of influence of external researchers, but with the stakeholders in healthcare themselves being responsible for the work that comes with integrating this intervention into their own groups, was not feasible. [44]

Balancing effect size and scalability:

Scalable interventions may not lead to the same beneficial outcomes as the original trial; however, when delivering interventions at scale, a small effect can still have a large impact

Improving health system performance by even a small margin has the potential to make a major effect on disease burden if improvements can be delivered at scale. [25]

These findings suggest that low-intensity, wide-reach CME [Continuing Medical Education] programs may be more effective at improving processes but not outcomes of care. [48]

Although a change of one pill per prescription may be perceived as a modest effect clinically, it reflects a 7 percent decrease (data not shown) during a period of heightened awareness about opioid risks, implementation of multiple other concurrent interventions (for example, the State of California’s opioid prescription drug monitoring program), and a resulting trend toward less prescribing. [62]