Context Matters Blog Implications and Use Cases for HTA Decision Predictive Models

Predictive modeling can be a powerful tool for understanding how multiple factors contribute to an event. As outlined in previous posts, Context Matters created a model that used variables from oncology assessments by the Scottish Medicines Consortium (SMC) to identify the most influential variables for a positive reimbursement decision by that agency and used the model to demonstrate the impact that economics (i.e., patient access schemes and ICERs) have in predicting positive SMC decisions for oncology drugs. However, as discussed in our previous post, Understanding Predictive Modeling, not all models are created equal. One measure of a predictive model's quality is its ability to deliver actionable results and insights. If a model is not able to inform the initial hypothesis and provide a path forward, it is just an academic exercise. But what does it mean for a predictive model to be "useful" and to deliver "actionable results"? What are some of the implications and use cases for predictive models of Health Technology Assessment (HTA) agency decisions?