Implementation Strategies for Real-World Evidence (RWE) Based Post Reimbursement Management

Real-world evidence (RWE) refers to clinical evidence generated through the processing and analysis of real-world data (RWD), which are routinely collected from real-world clinical settings rather than from controlled experimental environments such as randomized clinical trials.The use of RWE in health technology assessment has substantially increased, particularly for therapies addressing unmet medical needs, severe disease burden, and rare diseases.To improve patient access while managing uncertainty and financial risk, the Korean government implemented a performance evaluation system based on the RWD linked to risk-sharing agreements for several ultra expensive therapies.Furthermore, the introduction of the new coverage with evidence development risk-sharing scheme in 2025 establishes a legal and procedural basis for post-reimbursement outcome evaluations.Nevertheless, significant gaps remain in the systematic structure of the evaluation framework, including criteria for drug selection, stakeholder roles and responsibilities, data collection standards, evaluation methodologies, and decision-making processes.Real world evidence can serve as an important postreimbursement management tool for addressing uncertainty in clinical evidence.However, decisions regarding the collection of new RWD should be based on a balanced assessment of both the expected value of reducing uncertainty and the financial and administrative burden associated with data collection.When RWE is intended to complement existing reimbursement decision-making frameworks, the need for additional data collection should be evaluated by considering the quality of existing evidence, the feasibility of resolving uncertainty through supplementary data generation, and the likelihood that new evidence will meaningfully inform policy decisions.A structured and pre-agreed framework is essential to ensure that appropriate RWD are identified and collected through scientifically robust methods.This framework should include clear agreements on outcome measures, data collection methodologies, evaluation criteria, and post-evidence decision-making actions.These are necessary to support the transparent and consistent application of RWE in reimbursement and post-market pharmaceutical evaluation systems.