Every health system CEO should have clinical trials on their radar as a strategic approach to increasing revenue and improving patient outcomes. Artificial intelligence (AI) is a game-changer in enabling health systems to perform more clinical trials, boost revenues, attract and retain talent and provide patients with access to cutting-edge treatments.
We will illustrate return on investment (ROI) through case study examples from a major academic medical center in which researchers benchmarked advanced AI against conventional subject identification methods. Beyond patient matching, we will look at the entire trial design and recruitment cycle to find where AI can meaningfully support researchers, physicians, patients, sponsors and other stakeholders. We’ll demonstrate the impact of accelerated recruitment on a health system’s revenue stream, discuss how to create a business model to monetize existing patient data using AI, and identify relevant success metrics.
Recognize how various stakeholders (hospitals, researchers, physicians, patients, sponsors) can benefit from applying AI to existing workflows
Identify and benchmark operational success metrics related to clinical trials
Quantify time and cost savings associated with using AI versus conventional methods
Calculate revenue potential from identified opportunities
Develop corresponding business model and define success metrics and measurement criteria