According to Manns et al. (2025), Canada struggles to turn good ideas into routine care because functions for evidence, funding, procurement and delivery are fragmented. In the UK, these functions are, in part, connected within a tax-funded service free at the point of use. This commentary maps the architecture, linking research translation, independent assessment, regulation, procurement, adoption support and data and explains how evidence moves into practice through principles aligned with the nonadoption, abandonment, scale-up, spread and sustainability framework, which addresses nonadoption, abandonment, the challenges of scale-up, spread and sustainability. Two worked examples, placental growth factor testing and stroke imaging artificial intelligence, show that national assessment, adoption support and procurement enabled rapid adoption at a national scale. Practical implications for Canada include a single repeatable pathway from promising evidence to routine use, conditional adoption with evidence generation, national frameworks that reduce transaction costs, investment in implementation capability and secure data environments for real-world evaluation.
Whitty et al. (Mon,) studied this question.