Dear Editor, We read with great interest the study by Groenveld et al (2025) on the early health economic evaluation of virtual reality (VR) therapy for postoperative pain management1. The integration of digital therapeutics with economic modeling is both timely and innovative, highlighting the potential of VR to transform pain management while optimizing healthcare resource utilization. Notably, the authors’ use of external validation, a feature often omitted in similar early-stage economic studies, enhances the credibility of their findings and demonstrates a commitment to methodological rigor. The TITAN Guidelines 2025 (Transparent and Interpretable Reporting of Artificial Intelligence in Medicine) now offer a structured roadmap for developing, validating, and transparently reporting AI-based diagnostics, ensuring reproducibility and fostering trust in clinical practice2. The study offers an important first step. However, there are several considerations warrant further reflection. First, generalizability of evidence The economic model relies heavily on early-phase trials with relatively small sample sizes. While the preliminary results are promising, the variability in patient populations, surgical procedures, and pain management protocols may limit generalizability. Expanding future analyses to multicenter or international datasets would strengthen the applicability of these findings across diverse clinical contexts. Second, beyond direct costs The current evaluation focuses primarily on direct intervention costs and immediate postoperative outcomes. Indirect costs such as long-term healthcare utilization, rehabilitation requirements, and broader societal impacts like productivity loss remain underexplored3. Incorporating these factors in subsequent analyses could substantially alter the perceived cost-effectiveness and provide a more comprehensive understanding of VR therapy’s value. Third, model assumptions and uncertainty Key assumptions regarding the durability of VR-induced analgesic effects, patient adherence, and potential variability across patient subgroups introduce inherent uncertainty4. More extensive probabilistic sensitivity analyses, as well as scenario modeling to capture real-world variability, would enhance the robustness of the economic conclusions. Fourth, holistic patient-centered outcomes While pain reduction is an essential endpoint, VR interventions may confer additional benefits, including reduced anxiety, increased patient engagement, and improved overall quality of life5. Integrating these patient-centered outcomes into economic modeling would better reflect the comprehensive therapeutic and economic potential of VR therapy. Finally, implementation and scalability considerations Despite the clear promise of VR therapy, real-world adoption depends on addressing logistical, infrastructural, and training barriers6. These factors can substantially influence both the feasibility and cost-effectiveness of VR integration into routine clinical pathways. Systematic evaluation of these challenges will be critical for translating early economic insights into practical clinical application. Conclusion Groenveld et al provide a pioneering contribution to the evaluation of digital therapeutics in postoperative care. By addressing the considerations outlined above, future work can translate this early-stage promise into robust, scalable, and generalizable evidence, ultimately informing clinical and policy decision-making. This study not only underscores the potential of VR as a cost-effective, patient-centered intervention but also sets a high methodological standard for early-stage economic analyses in digital health.
Ali Pezeshkian (2026) studied this question.