![]() It’s not like we’re on the R and D side of pharmaceuticals or something like that. And so what we’re doing, and I’m sure we’ll get in this into more detail in an environment where you often don’t have the luxury of doing a randomized control trial. We’re, we’re an analytics platform that really takes on the triple discipline of, you know, targeting measurement and optimization. Jason: Uh, NextHealth technologies is in the business of optimizing interventions in order to improve the affordability of healthcare. And so tell me about, um, somebody tell me about the company and what you guys do. That’s interesting.Ĭurtis: That’s quite the journey. So I think I can bring a bit of a empathy to our, to our company from that perspective. ![]() I would have been the guy across the table at Kaiser, you know, vetting whether or not next off technologies was a good fit for us. I in some sense would have been a potential client. And I’ve been in healthcare since after three years at state Medicaid, eight years, Kaiser Permanente Colorado where I ran their payer side analytics at the end of my tenure and then ended up at, uh, next health technologies, uh, where I’m the senior director of health care analytics and ultimately sort of responsible for listening to the market and listening to our clients and figuring out, you know, what is the future direction of, uh, our platform, our product that we bring to the healthcare analytics space. And so then I was applying those econometric principles directly to healthcare. ![]() And I landed at the Colorado Medicaid agency, uh, the department health care policy and financing in their budget office as an analyst. Even though, even though it was just a small company and it wasn’t even related to healthcare is actually in publishing, but then the economy turn 2007, not sure, paper publishing and small business was what I wanted to do given where the economy was going by policy degree, looked pretty good to government agencies. When when, uh, your personal ability to put bread on the table is reliant on the quality of your decisions. Spent a little bit of time running my own company and got a very well versed in the need for data driven based decisions. Really strategic level business process consulting. And so that sort of holistic approach to problem solving is what started me down this path for doing some consulting in the beltway. And then you’ve got to go figure out how to answer that question using data. Now we’re talking about values and what are your near civic disciplines and that kind of thing. What is success of a stand your ground law. And so now I’m kind of in that theory space. Do stand your ground laws work well, I don’t know what does work mean. I’d love to say it was intentional, but it wasn’t around sort of here’s what government I think is supposed to work like and that was theory and here’s how it actually works and here’s the practice.Īnd that got me into that sort of more scientific methodology of problem solving where you’re trying to piece together either experiments or creating synthetic experiments with data in order to figure out what, what exactly is working. I got excited about this sort of marriage that I had formed. So teaching statistics to graduate students and that sent me down the rabbit hole. And so I got into econometrics and econometric study of policy analysis and eventually was a graduate level teaching assistant. He was just a professor that we sort of latched onto each other, and he came out of the Princeton school of thought around econometric analysis. And just so happened that a professor took me under my wing. And then got a master’s degree in public management, so basically an MBA for government, which is a lot more pragmatic than the theory degree. ![]() So I wasn’t even on the, the hard statistical side of that discipline. My bachelor’s is in political science where I focused in political theory. Jason: I actually have a humanities degree. Ginette: Data Crunch is produced by the Data Crunch Corporation, an analytics training and consulting company. Ginette: and you are listening to Data Crunch,Ĭurtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world. Jason Kolaczkowski: But rather than sort of be the good steward and try and anticipate the problems and make sure that the business never feels any pain from those problems, I found eventually it’s sort of the opposite-that you have to expose the business to the pain of those problems to create the level of urgency required to get them to participate. He shares his perspective as senior director of healthcare analytics at NextHealth and former Kaiser employee on the importance of streamlining data definitions-and many other helpful insights. Jason Kolaczkowski has worked in both a large-company data shop and in a company trying to help large companies fix their problems.
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