The healthcare industry has been undergoing significant changes for decades. A combination of factors have, however, accelerated the pace of change, including government initiatives to increase access to care, value-based payment models and digitization of healthcare information. With change has come a flood of data and increasing expectations from decision makers. Alteryx helps healthcare companies improve their speed of decision making by providing data analysts and line-of-business users the ability to prepare, blend, and analyze data themselves, without writing any code and without any IT dependence or delay.
Please join us in sharing experiences, best practices, and knowledge!
User Group Leaders:
• Lynsie Daley, Intermountain • Nathan Taylor, DataRobot • JR Segovia, PCPI • Sarah Golnik, BCBS North Carolina
Find tips to make the most of your User Group experience.LEARN MORE
When we were finishing up the Webinar, a really neat question came in about the Linear Regression output, and how to interpret it. I was having technical difficulties, and couldn't respond at the time. So, now let me answer that question.
The first section of the question asked where I got the accuracy of the equation from. At the bottom of the picture below, the adjusted R squared is circled in a red circle. This metric tells me how accurate the equation is. In this case, I would say that this equation can account for 88% of the variation that is seen in the Insurance Reimbursement rate.
The next question asked about how I understood what things were driving this equation. This is a more complicated question with no easy answer. I've sat thru way to many graduate level courses on statistics. The two rectangles that I've highlighted are the data points that I look at. The green one is called by my prof's the significance. The smaller the number, and the more stars it gets, the better the significance. Another word for significance is also consistency. The more stars it has, the more consistent and reliable it is. The second half of this is in the Orange box. The estimate of the coefficient tells me how much it will move the needle on Insurance Reimbursement. I could read this to say Diagnosis code 4 will decrease the Insurance Reimbursement rate by $110, and it is has a high significance, so I can be confident it will do that every single time.
Feel free to reach out if you need help.
Hello, I am not sure if it is only me, but I am struggling to hear the audio appropriately in the video provided. it breaks every few seconds.. is there any other way to watch it? I am very interested.