If I were going to design the worst possible health care analytics department in a health plan, TPA, or benefits consultancy, this is what I would do. First, I would go out and buy all the hardware and software licenses I needed, not to mention the database administrators and IT personnel necessary to support it. Why use the cloud? That's just a trend, right? And what about data security? The cloud can’t be nearly as secure as my data warehouse, right?
I would then determine that data management, analytics and reporting was a core expertise that I, as a single healthcare entity, could perform as well or better than any vendor that exists. So I would hire as many people necessary to respond to my ever increasing data demands and map all of the exponentially increasing data files into my data warehouse and pray that none of them quit. Because if they did, the data would start backing up in raw files outside of my warehouse like shipping containers in a dock strike. And if I get hopelessly behind? No problem. I'll just hire a large consulting firm and they'll send in new grads at $300 an hour to get me caught up.Then I would take it to the next level. I would hire as many analysts as I could afford. Maybe they would work in excel, or maybe they would write SAS or SQL spaghetti code to create reports. The language doesn't matter. And these reports would take hours or days to complete, and would not be correct half the time. The critical inefficiency I would strive for is to have these analysts prepare every report for all internal stakeholders and support every department in my company. And to really maximize inefficiency, I would have them run all routine reports repeatedly to insure I never realize any economies of scale.
In addition, I would insist that any report request from anyone in the company flow through this analytical department. This would accomplish two key objectives. First, the demand for reports would constantly outstrip the department's ability to produce them. There would be a hopeless backlog, ensuring job security. Once that backlog is in place, I would have full confidence that anytime someone from the C-Suite requested something, their request would immediately leapfrog all the reporting requests from middle management employees who are in the trenches dealing with my customers. Not only would customer satisfaction suffer, but the C-Suite would be clueless, as all their requests would be satisfied timely and they would never believe there was a problem.
Ok, so maybe that's not a good idea. And I'm half joking of course. But surprisingly, we still run into this scenario in the marketplace on a somewhat regular basis. Many health plan and payer IT departments just evolved and grew without much thought. And many know they have a problem, but are not sure what to do, so they keep investing in old technology and band-aiding a dying, outdated solution.
In fact, it was this exact mess that first motivated me to participate in a startup in 2001 to offer a solution. And nine years later we started Deerwalk. Why did it take so long? Because we had to wait for the right technology to catch up to properly solve the problem – modern data management, rules engine and search engine technologies like AWS, RedShift, Apache Spark and Elastic Search. When we embarked on the Deerwalk journey, we decided to build a population health analytics platform for the next 40 years, not the last 40. What we do is help clients take two step backs from the fray, focus on their core business, and leave the data management, analytics and reporting to us.
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To learn more about Deerwalk's Population Health Analytics solutions, please visit us at www.deerwalk.com, or click below to schedule a demo.
