OBJECTIVES: Electronic medical records (EMR) provide a rich source of routinely collected real-world data on health outcomes and resource use, which could be potentially used in economic models to adjust pharmaceutical pricing in real time to reflect the value a product delivers to the health care system. Our aim was to simulate how real time outcomes-based pricing could be operationalised using the example of visual acuity outcomes associated with treatment with ranibizumab for age-related macular degeneration (AMD) collected in a UK EMR database. METHODS:  A 5-year patient-level simulation model was developed to synthesise cost and outcomes of patients treated with ranibizumab for AMD recorded in EMR and patients’ natural history reported in the placebo arms of pivotal trials. The model was updated at daily intervals following the first treatment in 2008 until 2012 with the cumulative visual acuity outcomes recorded in EMR. The price of ranibizumab was adjusted each day to maintain a target incremental cost effectiveness ratio (ICER). RESULTS: The price of ranibizumab was reported at daily intervals over the course of the simulation. The first price of ranibizumab could be calculated after 3 months and reached GBP434.76 per vial at the end of the simulation when targeting an ICER of GBP30,000 per QALY. The simulation included data on 8,681 patients treated across 1,416 days. At the end of the simulation, the mean number of QALYs accumulated by patients was 3.05 in the treatment arm compared to 2.56 in the natural history arm over the five year time horizon. CONCLUSIONS:  Real world data may be used to monitor the cost-effectiveness of on-market drugs and to regularly refine their prices based on the value delivered in clinical practice. Performance-based pricing could be used to negotiate earlier market access for pharmaceuticals in advance of mature data on cost-effectiveness.