Modeling financial outcomes and quantifying risk in episode-based payment models.

Objectives: Health systems and provider groups currently lack a systematic mechanism to evaluate the financial implications of value-based alternative payments. We sought to develop a method to prospectively quantify the financial implications, including risk and uncertainty of (1) transitioning from a fee-for-service to an episode-based payment model and (2) modifying episode-specific clinical cost drivers. Finally, we highlight practical applications for the model to help facilitate stakeholder engagement in the transition to value-based payment models.

Study Design: We created a financial simulation from empirical data to demonstrate the feasibility and potential use cases within the context of a hypothetical episode-based payment model for prostate cancer surgery (prostatectomy).

Methods: We used Monte Carlo simulation methods to predict financial outcomes under various clinical and payment model scenarios for our pilot prostatectomy episode use case. We input patient-level empirical cost, reimbursement, and clinical data for a cohort of 157 patients at our institution into our model to quantify expected financial outcomes (payments, financial margins) and financial risk for stakeholders (payer, hospital, providers) under an episode-based payment model.

Results: Compared with the status quo, there is a range of expected financial outcomes for various stakeholders depending on the financial parameters (episode price, shared savings, downside risk, stop-loss) in an episode-based payment model. Modifying clinical cost drivers has a profound impact on these outcomes. Uncertainty is high due to the small number of episodes.

Conclusions: The simulation demonstrates that both financial parameters and clinical cost drivers significantly affect the expected financial outcomes for stakeholders in value-based payment models.