AG: Are there other ways CIOs can leverage the information (from HIMSS Analytics benchmarking)?
DG: We’re seeing an uptake of it that is dramatically higher this year than it was last year and higher last year than it was the year before. We had a bunch of very large healthcare organizations, which blew me away, coming into the booth in Orlando saying we’ve got to get our data (into the model), especially when we showed the stage six hospitals on the wall of our booth. There are 11 of them in the United States that we have validated already. It turns out that there is probably twice that many. But we didn’t have good enough data on the other 11 to be able to put them on the list. So when you start saying here are the top 11 healthcare organizations in the U.S., at least from our perspective, that are at the highest level of the EMR adoption model, it becomes something competitive.
We had a bunch of CIOs coming in and saying, ‘We think we’re there, but we have to get you decent data so that you can tell us whether we’re there or not.’ I think it’s an important for healthcare organizations themselves because you can't be creating strategies within a vacuum. And what you don’t want to do, if you're a CIO, is you don’t want to be out there on the bleeding edge unless your organization is a bleeding-edge organization, and most healthcare organizations aren’t. You want to do what's rational. By the same token, you don’t want to be lagging very far either because it’s a competitive environment.
So I’m happy that CIOs are into using this tool to help them figure that stuff out because that’s what it does. What's nice about this particular tool is that it’s a census of the acute care hospitals in the United States. It’s not a sample survey where we've interviewed 150 of them and then extrapolated it out for the whole country. There is date from 5,073 hospitals in this thing. This is a census survey.
AG: Do you have any idea what the total of number of hospitals in the U.S. is?
DG: It depends on what kind of hospitals. There are rehab hospitals and stuff like that. Most of those are not in the database. We don’t have the federal hospitals in there either. We’re working on that very hard. That’s VA and DOD, Indian health services, and those kinds of folks; they're not in there either. These are the acute care medical/surgical facilities in the U.S.
AG: How many of those do you think are missing?
DG: I don’t think there is any missing.
AG: So you're saying you have everyone in there for the acute care medical/surgical facilities in the U.S.
DG: That is correct. We added over 1,100 hospitals to the database last year. It was huge, and most of them were under 100 beds. Medical/surgical hospitals are in the database, that’s what we’ve gone after, and then there are some specialty places like heart hospitals, cardiology hospitals, children’s hospitals are already in there. Anything that’s a medical/surgical hospital is in the database.
AG: You mentioned that some CIOs came up to you from large organizations and said we have to get our data in there. What is the process? What could you tell to our readers that want to get in there that just aren’t sure what they're supposed to do?
DG: They can give me a call or send us an e-mail. Probably the best person to send the e-mail to is Patti Harris (patti.harris@HIMSSAnalytics.org). She runs the data collection group and the quality group. My guess is we’ve already got data on all these organizations; it may not be as complete as it needs to be. So all that people would need to do is make sure that it is complete and accurate. It’s not that they’d have to start from scratch and input all their data. That’s what we did in Canada last year. That takes a long time. If all they're doing is making sure that what's in there is correct and completing anything that’s deficient, it isn't that big a deal to do it.
They get scores back and they get 48 benchmarking reports for free. They log onto the site and all these benchmarking reports. They can pick their peers, not by name or organization, but by bed size or revenue or operating budgets. There is all kinds of criteria that they can use to pick peers, and then they run 48 benchmark reports, and if they don’t like those 48, they change the peers and run 48 more. They have the ability to do what they want to do trying to compare themselves to other organizations that are similar to them in the U.S.
AG: So this is self-entered data?
DG: There are a number of ways it can be done. Yes, they can do it that way if they want to. The survey instrument now is Web-based and it’s a very sophisticated survey instrument. It’s got all kinds of roles built into it and error checking stuff built into it and dropdown menus.
For example, if you said that the question is 'what have you got for an emergency department system?' and you put in Microsoft; it will pop back and say 'no.' Microsoft doesn’t have an emergency department system. Here is a list of vendors who have emergency department systems, pick one off the list. And then if they say 'no, it really is Microsoft,' then we go chase down Microsoft and say, ‘Have you just recently come out with an emergency department system?’ and if they have, we add them to the list.
We’ve got a separate database that’s got 1,400 products and services in it from all the vendors in the U.S., so that we think we know who has what in what areas across the board. It’s good for the U.S. and Canada. By the way, we’ve been adding all the Canadian vendors to it as well. So we use that database for the dropdown menus.
You can do it on the Web, which is the easiest way to do it. Or, if you don’t want to do it that way, we will send you smart spreadsheets. We've built all this stuff into Excel spreadsheets and they're smart. They’ve got the dropdown menus in them. If you want to talk to somebody and have them key it all in, we’ll do it that way too.
I think there are quite a few things out there that are gamed. It’s going to be much harder to game this one because we look at multiple points when we’re doing the algorithms to figure out where people are. Then, if we find somebody that we think is a Stage 6, Mike Davis (HIMSS Analytics executive vice president) calls them. He’s a very smart guy. We spend a considerable amount of time with the organizations that look like they’re 6s, and we found a bunch that weren’t — they were missing one little thing or something like that. Then what happens is as soon as they get that implemented, they make a phone call to Mike and say, ‘Okay, it’s up.’ Then they get Stage 6 status.
AG: Sounds like the microscope comes out when somebody is a possible Stage 6.
That is correct. We look at the other ones too. We look at 4s and 5s pretty carefully. Mike and I look at the data and, quite frankly, we know most of these organizations. We know who they are and we know the CIOs, and we do some error checking — that’s just us doing it, as opposed to all the stuff that’s built into the tool itself. There is a whole slew of automated error checking that’s in there. We know what's happening in most of these healthcare organizations, and we make phone calls to the CIOs and say. ‘Where are you?’ Because we’ll have CIOs call us saying, ‘Hey, we think we’re there.’ I’ll say, ‘Okay, do you have blank, blank, blank?’ It’s a collaborative thing, and it’s a cooperative thing with people. We’re not making awards here. We’re just trying to reflect the truth. It’s not something that CIOs can apply for. It’s a function of the data that’s collected in a very, very, very rigorous way.
AG: Why do you think that after Stage 3 there is such a dramatic drop off in where people are?