Q: What was your first introduction to ProviderTrust?
I had met Chris Redhage who was one of the co-founders, I had met Michael Rosen, his other co-founder, and I’d met several of the employees. And especially in contrast to the company I was working for, it was like, “I think there’s something different about this company and these people. I want to work with them.”
Q: What in particular made you want to work with them?
ProviderTrust treated me the same way they treated everyone else. That stood out. That was one of the many things that attracted me to the culture. That has stayed true throughout my whole tenure at ProviderTrust. It is truly a special place where I know that I am valued more than a bottom line or more than a fiduciary stakeholder. I know that they hold my relationship—our relationship—up as something that’s important to them. That goes a long way.
Q: What problem in the healthcare industry is ProviderTrust solving?
ProviderTrust exists to help healthcare companies stay in compliance and optimize patient outcomes. But the reality is there are a lot of bad actors that are in the healthcare industry today. The Medicare and Medicaid agencies have said, “Listen, we don’t want any of these people that we’ve identified as fraudulent or abusive working for any company that is receiving taxpayer dollars.” So they’ve built a list—they call it the exclusion list-—and they have required anyone in the healthcare industry that’s benefiting from the Medicare or Medicaid funding to check this list to make sure that none of those players are in the network. They’re not employees, they’re not referring providers, they’re not vendors, et cetera.
The problem with that is that this list is now 300,000 rows long. If you’re just Control+F-ing through an Excel file it’s pretty unwieldy pretty quickly, and the requirements are pretty stringent. You have to check this list every single month against your existing employees and any new employees that you’ve hired. For any medium-to-large size organization, that quickly becomes a pretty impossible task unless you literally create an entire team and sometimes an entire department that is just focused on this.
The other problem with this is the fact that there is no real standardization across these exclusion lists. So it’s one thing if all 300,000 of those excluded records show up in one file, but they’re spread out over 42 different files, and those 42 different files are in 42 different formats, and they have a data model that’s completely separate and inconsistent. So you begin to get a sense of the state of this data. We take it upon ourselves to thoroughly cleanse that data, to standardize it, to consolidate it into one of those big files that we can take on that work.
Q: When it comes to the names on the exclusion lists, what information do you have to work with?
What we’re given is primarily transient data—things like name and address. If you’ve ever looked at personal data for any length of time, both of those things can be really unreliable. You can get married. Your name can change. Same thing with address, people just move. We use our compliance intelligence to enrich this type of data and combine it with our own internal real human verifiers to make sure we’re getting the full picture of the people and entities we monitor.
Q: How do you eliminate room for error?
Our real human verifiers. We put our data enrichment research through a series of reviews to ensure multiple sources are achieving the same results. If, and only if, all of those things come out as a pass, then we’ll load that into our system and persist it and make decisions based on that data and report back to our clients.
And so it’s building a process that ensures accuracy from the very beginning. Knowing that the outcome of our decisions based on this data is really critical to get right. The outcomes and the impacts are really important, ultimately affecting patients and the care that they’re receiving from their health plan network or the hospital that they’re choosing to go to. We take great care on the frontend to make sure that all those little decisions and places where it could go wrong are hemmed in.
Q: How much of this process is algorithm vs. hands-on?
We are fans of automation and things like machine learning. We love being able to take advantage of cutting-edge technology. However, we are not comfortable entrusting all of the decision-making power to an algorithm or a pattern. We’re very careful in the ways that we wield machine learning, automation, that sort of thing. If we get too fancy with technology, there’s a chance that we would allow a machine or a piece of code to make a decision that really a human should have made. And so we’re very careful about architecting and engineering solutions that never engineer the person out of the formula. And I say that with two meanings: one is the patient on the other end who’s ultimately going to benefit or not benefit from our decision, and then the [other] person who’s playing gatekeeper— that would be the person that’s working for ProviderTrust.
Q: What’s some of the best leadership advice you’ve ever received?
I think of two things. One is more philosophical. You have to be able to lead yourself before you can lead others. But really what that translates into for me is that if I wanna see an outcome in the folks that I’m leading and the teams that I’m leading, I need to figure out how to achieve it for myself first. If I want to see balance on my teams — a sustainable, balanced, working rhythm — I have to first find that for myself.
The second one is that as an executive, one of the primary ways that you serve your team is by wrangling budget. For one, it forces you to really think through, “What am I convicted about? What do I really need and what does my team really need?” And then two, turn that into a plan that has dates and dollars, and map that. Map that on a calendar; put that in an org chart. Doing the work first provides me with an enormous amount of clarity and conviction about where we’re going and what we need.