Parth Mehrotra
Analyst · Nephron Research.
Thanks, Josh. So sequentially, if you look at, Medicaid lives grew about 15,000, round numbers, from 100,000 to 115,000. That was mainly driven by organic growth across all of our markets, but then also notably, as we entered Arizona. And again, in the Medicaid book, as you rightly noted, we don't take any downside risk. We are trying to contract with payers where if we can add value to these practices and manage these lives and have some upside shared savings, we get a piece of it with no downside for all the reasons you know about that program. Very volatile, very hard to deliver a lot of value without getting paid for it. And so, that's been our position in Medicaid. But I think our platform allows our physicians to handhold these lives in a much better way than just plain fee-for-service Medicaid. And so, we think it's a great program to be in. We get paid a little bit for the value we add, and we're happy not to take any downside risk, given all the structural issues with that program and what the payers are seeing, as you well know. And then, to your second question, look, we've been using machine learning, AI bots for many years across our entire workflow. So our teams, our technology team and operations team look at the entire fee-for-service workflow and then the value-based care workflows. And revenue cycle was an area where a lot of the innovation happened over the past few years, whether it's getting paid faster, whether it's reducing administrative burden, so on and so forth. But I think some of the new investments we've made, worked with companies like Navina, are all on the clinical side that drive application of AI into the clinical workflow for value-based care arrangements, where we have identified suspect medical conditions where, at the point of care, physicians are getting prompted to make sure if a patient shows up over a certain age with certain comorbidities, taking certain medications, to check for other conditions that might be persistent based on data sets that are expanding over time, our data set, data from the payers. Ultimately, hopefully, there'll be a national data set that we could rely on to. So those are the areas in the clinical workflow. A lot of innovation happening in the scribing world. We've tried different scribe solutions over the years. But with AI-driven scribing solutions, I think that's another area where documentation is getting better, getting faster. And it all leads to reducing the burden for the doctors ultimately and better clinical outcomes, better coding for the patients in a very compliant manner. So those are the areas we're focused on and partnering with many companies in that space as they innovate.