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

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.

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).

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.

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.

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