It was suggested recently by data analytics someone who heard my podcast, who was outside of the industry and wasn’t familiar with the terminology, that we hadn’t defined some of the words and acronyms we use. So I thought I would take a moment to do that.
I think there’s a broad application for this, not just for people who are just getting started in analytics or some of the financial aspects of revenue cycle management from a healthcare standpoint. I hope that this has benefited those who are much more advanced in their careers in this particular subject. Hopefully, there’ll be some nuggets here that’ll help you perhaps communicate what you’re doing and dispel some myths and misinformation that you have to deal with in the industry there’s so much of that going around.
What do you need to know?
I think starting with the term “metrics.” This means to measure. I shouldn’t say “obviously.” Let me back that up. Not obvious. It implies a measurement, and that means numbers, that means data. Typically, when people are talking about metrics, though, that presumably will be some measure of something specifically related to, in this case, the revenue cycle management or something financial, so it’s a financial measurement. Again, it has to include numbers.
That means that when you see a consultant or an article that talks about KPIs or talks about metrics and says, “Oh, you need to make sure that you do pre-authorizations for all of your patients,” that’s not a metric. A metric would be the percentage of patients who received a pre-authorization, or the percentage of patients who needed a pre-auth or got one, or the number of denials you got for not having a pre-authorization. Those would be metrics because, again, they’re numbers. So that means numbers. We can’t let people sort of mix that up and uses subjective things in place of metrics. I think that undermines our industry.
Key Performance Indicators
In terms of KPIs, that stands for key performance indicators. The concept here, I think, would be. Again, there’s no strict definition of all of these things. There’s no, and I don’t know, jargon police out there, although it’d be kind of funny if they showed up at your door, and you’re using the wrong words. KPIs, in theory, should be some subset of the metrics that you use to keep track of the most critical aspects of your business, the things that determine whether or not you are successful or you’re going to be successful.
Think in terms of a dashboard kind of stuff. There’s a smaller number of things that you want to look at all the time. If they go into a particular zone, if they set off a red flag, something must be investigated. Those are key performance indicators.
Then, we get into a much more nuanced and much more complicated one, which is analytics. The reason why I say that is the term “analytics” is thrown around so loosely by organizations that it’s been so watered down, and it’s become almost meaningless. I think we’ve seen this over even the last 15 years with many different things.
A decade ago, we were using Oracle Business Intelligence as our reporting solution. A business intelligence solution is probably a more accurate term. That was a big complex system. We had to have analysts who could write SQL queries to pull the information we want. You had to understand the underlying data tables and where all that information resided. It was complicated, and it was challenging to diagnose or know if you had a problem in the reports that you were pulling because you would sometimes get information and not even realize that you had a problem. It required a lot of sophistication to effectively use that tool and not come up with a sort of false positives or false negatives.
The reason why I bring that up is business intelligence still is a thing, but I think reporting suddenly got termed “business intelligence” somewhere along the way because business intelligence sounded better and sounded like it had much more muscle and much more power. Therefore, we don’t have just reporting. We’ve got business intelligence because marketing, unfortunately, infiltrates and corrupts in some ways many of the things. I can say this because I’ve spent enough time with the marketing in our organization, and there’s a spin that can come out of things.
The point is that the word “business intelligence” essentially got co-opted for reporting, and that’s not accurate either. I think we’ve seen the same thing happen with analytics, which is so many software companies, whether it’s practice management systems, billing systems, other software entities, billing companies, so many of them are saying, “We have analytics.” Many of them are saying, “We have advanced analytics now.” They’re one-upping that even. It undermines what it is because it’s very hard then for providers who are hearing all of these things to understand what they’re getting and the distinction between them.
You can look up a definition, and it might say something like a systematic computational analysis of data or statistics. Okay, but that’s saying it’s analysis. I would say there may even be a more commonly used version of that, which is analytics, might be tools to allow you to perform analysis, so tools for analysis.
What is Data Analysis?
Then, we come down to like, “What is analysis?” Again, we’re back to something like “What is analytics?” So many organizations use this synonymously with reporting, and that’s completely inaccurate.
If you look at somebody like Merriam Webster’s dictionary, we liked their definition. It’s something along the lines of a detailed examination of anything complicated to understand its nature and determine its essential features. You can skip some of those words, but there’s sort of a subheading to that, which is a thorough study. If you think about a detailed, complex study using data, that’s a pretty good definition of analysis, I believe. Therefore, analytics should be that as well, which is a detailed, complex, thorough study of something using data or information, but in our case, real data.
If you’re going to perform analysis, that’s not just a report. Kicking out a report is not an analysis. The analysis is not a product. It’s a process. Therefore, it’s something that someone has to do using information. Consequently, we can have tools.
A carpenter isn’t a house. A carpenter is somebody who builds a house. So I think the analysis is more akin to a carpenter making a house than it is to a home. But people say, “Oh, we have analytics,” like we have a house. Okay, that’s the finished product. That’s the outcome of an analysis. Presumably, the analysis should help you understand something to answer a question that allows you to make a change in your business that makes you more money. That should be the driver for all of this.
Dealing with myth and misinformation Of Data
There are so much myth and misinformation and so much garbage going on in the marketing BS. How do you weed through it? The short version is you have to, at best, be a little cynical or, at least, skeptical, maybe even cynical of what people are presenting if they say they have analytics. I think the proof is in the pudding. We can talk about that in a different podcast: how do you evaluate all of that?
Analytics is not reporting; it’s not business intelligence; Not a report. It’s not a series of reports. Not data warehousing. It’s not big data. It’s not any of those kinds of things. An analysis is a process that you go through to get answers using data.
That’s a podcast for today. By the way, I’m doing this from a car. I thought I’d give it a shot. I’m on my way to have minor surgery so that I might be out for a few days, and this is my only opportunity to do a podcast today. I thought I’d try to get one in. Hopefully, the audio quality is not too bad, and you guys can understand me, and yeah. We’ll see how it goes. I’ll see you on the other side.