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The stats on patient payments aren't good: • Almost 70% of patients' hospital bills don't get paid in full • Over 40% of U.S. adults have medical or dental debt • Nearly 20% of U.S. adults have medical bills that are in collections With the rise of high deductible health plans putting increasing financial responsibility on patients, hospitals can't afford 𝘯𝘰𝘵 to make their payment processes as simple and seamless as possible. We recently dug into the patient payments space, with a particular focus on how AI is being applied to this problem. THE CURRENT PATIENT PAYMENTS MARKET In the legacy fee-for-service patient payment model, the hospital revenue department (or an outsourced firm) sends out bills, tries to take payment, and, after 60-120 days, sells them to collections. In the last five years, tech entrants in this space have focused on one of the hardest parts of this problem: engaging with the patient throughout the journey so that when the bill is due, the patient understands it and sees a clear path to payment. Despite improvements, however, we're still seeing underpayment across the majority of patient bills. AI FOR PATIENT PAYMENTS AI is rapidly being applied to the patient payment process in a number of ways: 📄 AI-generated patient bills or explanations, minimizing errors and helping patients better understand their bills. 🤖 Billing inquiry chatbots that help patients handle routine billing questions and workflows 📅 Optimized payment schedules that help determine the optimal times and channels for reminders, messaging, etc. 💸 Integration of relevant data and prediction of ability to pay in order to provide discounts, payment schedules, and other financial support for patients. In the new AI-enabled model, there are essentially two main market segments that echo their legacy counterparts:  patient financial engagement solutions & companies that model and take on financial risk. PATIENT FINANCIAL ENGAGEMENT Like their predecessors, these digital front-door technologies focus on creating easy consumer payment experiences. They differentiate from prior solutions by using machine learning to optimize messaging, delivery time, and message channels. They also often include billing inquiry chatbots and AI-generated explanations for bills. Examples include: • Cedar • Decoda Health • Flywire • Raxia • VantageHealth.ai PATIENT FINANCIAL RISK These tools leverage AI to predict whether patients will pay and how much they can pay over time, creating payment plans to help them pay off bills. In some cases, vendors also automatically pay health systems and take on financial risk to collect from patients. Flywire PayZen Sift Healthcare Our team is betting the future for patient payments will be hospital systems getting paid immediately, and AI-enabled patient payment platforms taking on the responsibility for collecting payment. Where do you see the patient payments category going?