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eClinicalWorks has a dashboard in their online reporting system, in their eCW cloud that is called the daily scorecard. I wanted to give you a quick breakdown and review of this and whether it works well or not.
Learn more about the layout
First, we need to explain or give a little bit of what this layout looks like and what’s in it. Well, it seems like a series of boxes (four across and many down). Each of the little individual packages has a metric, or a little chart, or something like that, which is part of this dashboard. You’ve got a series of eight boxes at the top that has one number in them along with some associated data. Then, you have a series that is effectively some small graphs, where you’ve got four pie charts going across. Then, you’ve got a table below that, and then you’ve got another table.
This is an excellent example of what’s not a great dashboard. We need to dive in more deeply rather than make that sort of a general statement because I think what’s relevant is the specific details.
Understand the goal
As I’m looking at this, the first thing I think of is, “What do you do with this?” I mean, what’s the goal? What’s the objective? I’m sure somebody has a purpose. It’s just that it’s not entirely clear precisely what that is. It’s not like I’m not in the business or I don’t have any understanding of this. Presumably, based on the name, the daily scorecard. For instance, this is something that a manager or somebody will look at daily. Why? Well, to get an idea of what’s happening in the practice or the billing. I don’t think it meets that goal very well because it certainly doesn’t communicate clearly and efficiently.
Going through these in detail, I think, trying to break it down, I’ll give you an idea of what these are about. This may take more than one podcast to go through.
The first little box in this dashboard at the top left is “Charges.” It’s a single number. Again, this is just one example that says $21,045.00. Then, there’s a green up arrow to the left and a red arrow down to the right of that. Yet, it’s all still within that same little box. It says, “Day before $7,845. 60-day average $22,947.” Now what?
Manage the data correctly
Before we even get to the “What do we do with this information?” First, are we even comparing apples to apples? In other words, what information is being evaluated within just this one little box of the dashboard? Are we comparing data that is helpful, that is continuous, that is comparable? There are several factors that you want to look at. I think very quickly. We’ll realize that no, we’re not looking at apples-to-apples information here. By apples-to-apples, I mean something that is taking into account variances or things that would skew your data in a way that might misrepresent something.
The next field, the next little box, is “Payments.” We’re going to get into what the red arrows and all other information mean a little bit later, but the next box is “Payments.” It shows $153.00, and there’s a red arrow down to the left. Also, there’s a red arrow down to the right. The day before was $15,943. A 60-day average is $17,000. So we’ve got the day before $15,000, 60-day average $17,000, today $153. I shouldn’t say today. In this case, it isn’t today. It was the day that we selected, which happened to be November 11.
It’s very clear from this data then that there’s something wrong because it felt like, “Oh my gosh, what a collapse! Payments are $153 in a day when it’s averaging $17,000 over the last couple of months. There’s a disaster. Something went wrong.” I thought, “Okay! Well, maybe this isn’t taking into account weekends because maybe the day we selected was a weekend.” No, the day we selected wasn’t a weekend, so it’s not that. We ran this on a Friday, and we decided the day before, which was a Thursday.
Take holidays into account
Then, I realized, “Oh, yeah, yesterday was a holiday in the United States.” We worked at Apache. Further, please don’t report us to the federal authorities. In addition, we worked. I think it was Columbus Day or something like that. It’s a holiday that we don’t recognize, even though it’s a federal holiday. That’s not a political statement. I don’t want to go there.
We worked. It didn’t occur to us that there was a holiday. This practice did not work. What that means is that there’s a real problem with the data. They’re not taking into account holidays. They’re probably not even taking into account weekends either since it doesn’t seem like they’re doing weekdays only. Since 60 days is not a multiple of seven, depending upon whether even just one additional weekend is included or not. Why? Because as that 60 days rolls, you’ll have one or less one weekend depending upon what period you select. Moreover, that can change your average by as much as 5%.
Read the dashboards
If you’re comparing something to an average that varies by 5%, 6%, 7% based on what period was selected for the rolling 60 days, that’s not very helpful. If your business is changing by 5%, 6%, 7%, that’s a significant change in your industry. Yet, you can’t even see that because it’s drowned out by insufficient data here. Wouldn’t you think that was a big deal? If your revenue went up 5% over the last couple of months, you’d be like, “Great! That’s a huge improvement.” Oops, well, it didn’t go up. That’s just a reporting error that misrepresented it. That doesn’t seem very smart to me.
It’s so essential in reporting that they don’t represent the data like that.
The purpose of dashboards of reporting of any type is to give us actionable information to do something with it. But we haven’t even gotten to the “Is it actionable yet?” And the other question, “What are we going to do with this information?” If the data is sufficiently skewed or bad or misrepresentative that you can’t rely on it, what good is it? It’s completely nuts. This is an excellent example of insufficient, bad data.
Going back to the point of these boxes, is it an apples-to-apples comparison? Is it consistent data? Is it useful? I don’t even trust the data in here, forgetting even whether or not the dashboard is well designed or whether or not the information is presented well, whether it’s clear, whether it’s concise. The data is garbage. What do you do with this? I don’t understand how people put up with this. This is one of the big reasons why people don’t use reporting and analytics much in revenue cycle management and healthcare. It’s because they don’t trust the data. It’s not helpful. It doesn’t represent things accurately.