PRUDENT: Representing Evidence-Based Clinical Decision Making

Offline reinforcement learning for clinical treatment recommendation typically combines observed practice, clinical knowledge, and outcome-based objectives into a single optimisation problem, with the resulting policy determining the recommended action. While this formulation provides a natural way to optimise treatment, it obscures distinctions that evidence-based medicine requires at the point of care, including where evidence comes from, how strong it is, where it applies, and when it is silent. We instead take the clinical decision, rather than the optimised policy, as the object of study. We introduce PRUDENT, an evidence-based decision framework in which routine clinical practice anchors the decision while guidelines and learned policies remain explicit evidence sources, each retaining its strength, coverage, and ability to remain silent. PRUDENT characterises the decision context along two continuous dimensions, measuring how atypical the current state is relative to routine precedent and how strongly the evidence sources that speak disagree. Together, these dimensions form a decision plane that distinguishes routine decisions, known controversy, consensus extrapolation, and the true edge. PRUDENT represents each evidence source as a transport route from routine practice toward the action it supports, using conditional flow matching to learn these routes. The decision context governs how far departure from routine is warranted, while evidence strength limits how far each source may be followed. The resulting candidates are arbitrated separately for each action dimension using only the sources that speak, and the final action is projected onto the clinically feasible set. On MIMIC-IV, the decision plane identifies a consensus extrapolation region comprising 22% of decisions in which patients have lower SOFA and lactate and higher mean arterial pressure, receive substantially less fluid and vasopressor treatment, yet experience 1.76× the mortality of patients in the routine region. These findings are observational and require no counterfactual estimate. In controlled simulation with known optimal control, PRUDENT adapts its departure from routine across five regimes, moving away when routine practice becomes unreliable while remaining close when it remains appropriate. Together, these results show how evidence-based clinical decision making can be represented without collapsing heterogeneous evidence into a single optimised policy.