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MONAHRQ's Preventable Costs and Hospitalization Mapping Tool

Webinar Transcript

The following is a transcript of a technical assistance conference entitled MONAHRQ's Preventable Costs and Hospitalization Mapping Tool held on July 21, 2010.

Select to access the full-length recording of the Web conference. (Flash File, 1 hour, 14 minutes)

Margie Shofer: Thank you, Zac. Good morning or afternoon, depending on where you're located. I'm Margie Shofer in the Office of Communications and Knowledge Transfer at the Agency for Healthcare Research and Quality, otherwise known as A-H-R-Q or AHRQ. Thank you for joining us for this Web conference on MONAHRQ, My Own Network powered by AHRQ, and its "Preventable Hospitalization Costs and Mapping Tool" component. Let me first say that if you haven't already downloaded the slides for today's presentation, please open the "chat" box for instructions on how to do so. That's located on the right-hand toolbar on your screen. 

MONAHRQ software can be used by State and local data organizations, health systems, and payers to provide Web access to quality and utilization indicators based on their inpatient administrative data. MONAHRQ analyzes, summarizes, and presents information in a format ready for use by consumers and other decisionmakers on quality of care at the hospital level, health care utilization at the hospital level, preventable hospitalizations at the county level, and rates of conditions and procedures at the county level. 

Any organization with inpatient hospital administrative data can use MONAHRQ to generate their own Web site for internal use or public release. Organizations host the new tool on their own Web server, populated with their own hospital administrative data. The Web site generated by MONAHRQ is an interactive querying site that users can navigate to learn about health care in their area. 

In addition to an overview of MONAHRQ, this Web conference will provide a live demonstration of MONAHRQ's preventable hospitalization costs and mapping tools. This Web conference is the second in a series of events highlighting several AHRQ tools created to help you identify and support areas for health care quality improvement, and I know some of you participated in the May Web conference on HCUP and HCUPnet. 

If, after hearing about MONAHRQ and its Preventable Hospitalization Costs and Mapping Tool today, you're interested in learning more or receiving technical assistance, please let us know. Our contact information will be provided on the last slide. Separate from this project, AHRQ is supporting a MONAHRQ Learning Network, which will serve as a forum for participants to share their challenges and information needs, particularly with respect to using MONAHRQ as a tool for creating a public reporting Web site. To learn more about this opportunity, please E-mail by the end of this week, as letters of interest are due on July 30, and this E-mail address will also be on the final slide, so don't worry about writing it down now. 

Today's Web conference will be presented by Anne Elixhauser and John Bott. Anne is a social science analyst in the Center for Delivery, Organization, and Markets at the Agency for Healthcare Research and Quality. Anne will begin by providing a background on the tools, describing the core paths of MONAHRQ, and briefly explain maps based on DRG and CCS codes. 

John is a quality indicator measures expert also at the Center for Delivery, Organization, and Markets at AHRQ. He will give an overview of the Preventable Hospitalization Costs and Mapping Tool component. We will take a few questions after Anne's presentation and again after John's. We will wrap up the Web conference with a presentation from Brooks Daverman of the Tennessee Division of Health Planning. We were also going to have a presentation by Trish Riley of the Governor's Office of Health Policy and Finance in Maine, but unfortunately, Trish was not able to join us today. 

After Brooks' presentation, we will have a third open Q&A period, during which time we will address as many of your questions as possible. We would really appreciate your active participation, as the primary purpose of today's Web conferences are to introduce you to MONAHRQ and the Preventable Hospitalization Costs and Mapping Tool, explore practical applications for the tool, and address any initial questions you may have about these tools. 

As I just mentioned, the Web conference will have three question-and-answer periods, and as Zac said, there are two ways you can ask a question of our presenters. You may submit a question at any time throughout this Web conference by typing your inquiry into the "Q&A" box located on the right-hand toolbar on your screen beneath the participant list. These questions will be entered into the queue and answered during the Q&A period, so feel free to submit them at any point during the presentation. 

Or during the question-and-answer periods, we encourage you to ask live questions, which you may do by clicking on the "raise hand" button located at the bottom of the box containing the participants' list. This will place you in the queue of questions and we will notify you verbally when your line is unmuted so that you may ask your question. As a reminder, you need to have the telephone icon next to your name if you want to ask a verbal question. While we encourage questions, regardless of their format, asking a live question can be easier if you have any followup questions or if the presenters will need clarification from you. And there can be a bit of a lag time as information is typed into a chat box that doesn't exist in a live person-to-person exchange. 

We will try our best to get to all questions, but if we don't get to your questions during this call, we surely will afterwards. We will also respond to all questions we receive after the Web conference, and again, the E-mail address to send something to us will be on the final slide. So without further ado, I am going to hand this over to Anne.

Anne Elixhauser: My name is Anne Elixhauser, and I'm going to be giving you a brief description of MONAHRQ. John Bott is going to follow after a few minutes, describing more details about the Preventable Hospitalization Costs path of MONAHRQ. You can see that we have a Web site, so please visit us there. If you're interested in getting on the MONAHRQ mailing list or if you need any kind of technical assistance or have any questions about MONAHRQ, that's our E-mail address,

MONAHRQ stands for "My Own Network powered by AHRQ." It's literally a piece of software that will allow you to help transform your health care data into information about health, costs, and quality of care. MONAHRQ is designed to be a tool where you can input your data and output a Web site. 

Why did we create MONAHRQ? Why did we develop this piece of software? We had been asking ourselves for quite a long time why should it be so expensive to generate and put out basic information on quality of care, on utilization, on rates of conditions and procedures? Why should this kind of information be so difficult for the public to get? And lastly, why does every organization that wants to present this kind of information based on hospital discharge data have to reinvent the wheel every time they want to do this? 

MONAHRQ started with hospital discharge data, which were already being collected by almost every State in the country from all the hospitals in those States. We all know that hospital discharge data can generate a lot of really valuable health care information on utilization and costs of care in hospitals, on rates of diseases and procedures in particular areas, on quality of care in hospitals, and on preventable hospital stays that indicate a breakdown in care. This is where the hospital data are really being used as a window into what is going on in the community. All of this information based on the hospital discharge data can be used by a lot of people to make different decisions. 

So, these are the key features of MONAHRQ. Mentioned earlier, currently based just on hospital discharge data, the first version of MONAHRQ was released in June. We are planning another release of MONAHRQ, MONAHRQ 2.0, to be released within a year, and that will include other data, specifically data from CMS, the kind of information that you see on the Hospital Compare Web site. But version 1.0 of MONAHRQ is based just on the hospital discharge data, the hospital administrative data. 

The host user is the organization that collects the hospital discharge data. It could be an individual hospital or it could be a hospital association. It could be a State data organization that collects hospital discharge data from all the hospitals and their States. That organization is the host user that downloads the MONAHRQ software from the AHRQ Web site. You, as the host user, will then apply the MONAHRQ software to your own data locally on your own computers, on your own servers. You will then create a Web site, again, on your own server. It doesn't require uploading any data. It doesn't require sharing any data outside of your organization. You control the entire process. 

So you download the software. You apply the software to your own data. You create a Web site based on your own data on your own server, and then you can make that Web site available any way that you choose. You could just use it internally to better understand your own data, to answer questions from the public, from reporters, from legislatures. You could make it available just to your member organizations, to the hospitals that submit data to you; for example, through a password-protected Web site. Or you could make it available publicly to provide information on hospital care to the community. 

I'm going to go through three parts of MONAHRQ. Margie alluded to this earlier. There's information on quality indicators by hospital. There's information on utilization statistics by hospitals and for specific health care conditions and procedures, and there are also rates and maps of conditions and procedures by county. John is then going to take over and go into more detail, showing you maps by county, looking at potentially avoidable hospitalizations. 

Let's start with the first path of MONAHRQ, looking at quality indicators by hospital. There are two quality paths that the end-user will be able to choose from. The Web site that you're looking at right now is an example of a Web site that was generated using synthetic data, so none of the data is real. The information that you see up in the top panel where it says "State Health Care Information Portal" is where you would actually put your information, your organization's name. The stethoscope picture there is where you would put your logo. 

The system can be customized and modified. You can change the colors. You can change the flow of things. But what you're seeing here is an example Web site based on the synthetic data. This is the Web site that you would actually be presenting publicly or that you would have as an internal Web site that you would use for your own staff or for your member hospital. 

You would first choose which view of hospital quality indicators you want to use. This is as an end user, perhaps someone in the community. Do you want to look at information for consumers or do you want to look at more detailed statistics, which is aimed at analysts and the health care profession. In this example, we're going to stick with information for consumers. 

The AHRQ Quality Indicators form the basis of the quality indicator path. These Quality Indicators, or the QIs, have been grouped into health topics that have been consumer tested and cover topics like heart conditions and health, childbirth and hip replacements and brain and nervous system, that sort of thing. 

What we're going to be looking at here in this example is medical complications for adult patients having operations or procedures. Once you select that, you can select among specific Quality Indicators within that topic, and here what I have chosen to do is to select all the Quality Indicators under medical complications. Then you can select specific hospitals that you want to look at. You can select hospitals from the entire dataset or from within specific regions. 

The default in MONAHRQ is to actually list the hospitals by name, but the names can be mapped, and we have mapped them in this example. Under the consumer path and quality indicators, what you get is information on up to four hospitals for the indicators that you've selected. What you see here is the hospital names would be in the column headers and the indicator names are here, as a row label. It tells you, then, how each hospital performs on each indicator, worse than average, better than average, or average.

You can click on the indicator name to get more detailed information in graphic form. What we would get here is a graphic that shows the actual names of individual indicators and then provides the numeric values for each of the hospitals compared to the nationwide average and the State average. 

The detailed path provides more information on each of the indicators, and here the first thing we get is overall results for the State, and you can see there's a lot more information here. You get exact numbers of numerators/denominators, you get observed rates, expected rates, risk-adjusted rates, and you get confidence intervals. Then you click on the indicator and you get hospital-specific information, and again, you get the very detailed information. 

Then you can select for these data in a chart, and this is the kind of chart that you would see. Under the consumer path, it would be only for those hospitals that say "Consumer selected." But in the detailed path, we provide information on all the hospitals, again, compared just to the State average. 

The next path will provide information on utilization statistics. If you're familiar with HCUPnet, this is similar to the kind of information that you get from HCUPnet, and the same developer who developed HCUPnet developed this path as well. You can get utilization across all conditions for the entire State, so what you're getting here is information on the numbers of discharges, both all listed and principal diagnosis, mean charges, mean costs. The ability to convert charges into cost is built into MONAHRQ. You also get information on mean length of stay. You get information on the total U.S. You get information for the region in which the State is sitting. Then you get information for the State as a whole, and then for all conditions, and this is for the State as a whole for each of these individual conditions using the clinical classification software. 

You can also get detailed information on individual conditions. Here we have selected to look at specific diagnoses. We're looking at septicemia here, a blood infection, and we're going to be looking at all hospitals. You could look at individual hospitals if you wanted to. What we get here is, again, number of discharges, charges, costs, length of stay. For all hospitals, individually, you get the benchmarks, as well as individual hospitals. Then if you click on individual hospital, you get more information by age group, gender pair, and race, if that information is included in your data. This is, again, just for septicemia. 

Looking at rates of conditions and procedures, MONAHRQ has embedded within it county population numbers so that all you have to do is input your hospital discharge data and you're able to generate rates, county population-based rates for conditions and procedures. What you can do is to look at conditions or procedures by DRG, by MDC, which is just groupings of DRGs, or by the CCS, the Clinical Classification System that we have developed here at AHRQ. Again, we're going to just choose the CCS here. You can search by keyword, by typing in lung, and then it drops down to cancer of the bronchial tubes and lungs. If that's what you want, then you proceed and what you get here is for all counties in the State, you get the number of discharges for all listed, for principal  You get rates of discharges per hundred thousand persons, again, for all listed and principal—this is lung cancer—as well as the mean cost in dollars.

Each of these columns is sortable, so you can resort the columns by any of these. You can also get detailed information for each of the States, and you can also click on maps of counties for all listed or principal to get a graphic view of this. Here what we see is all listed diagnoses for cancer of the lungs for all the counties in this State where the light-colored counties have the lowest rates and the dark-colored counties have the highest rates of lung cancer. 

Let me just briefly describe how you actually get there. How do you build a MONAHRQ Web site? MONAHRQ is based on a number of AHRQ tools. There are six, seven, maybe even eight AHRQ tools that have been brought together in one package. One of those AHRQ tools is WinQI, the Windows version of the Quality Indicators. If you're a WinQI user, this will look familiar to you. We've basically just embedded the MONAHRQ capability to build a Web site into the WinQI. 

The first thing that you would do is import your data, and this takes you through a very simple step-by-step process of importing your data and then mapping the data to the format required by MONAHRQ, et cetera. First you select your input file, then you map your data elements, which is the click-and-drag process where you map your data elements to what is required by MONAHRQ. Then you map your input values, again, to those values understood by MONAHRQ. If you understand your data, this is a pretty simple process. 

This is probably the process that is most labor intensive from the perspective of the host user. But MONAHRQ saves all that, so once you have that information in there, you don't have to do it again unless your input values or input variables change. 

Then you load your data, and this is the step where you start the process and then you go get a cup of coffee and have a chat, because it will take a while to load the data. Then you go through the process of running the analysis, and this is the part that you want to do at the end of the day because you start the process and then go home, because it takes a number of hours to go through it. Hopefully, by the time you come in the next morning it will all be done for you. Then you go through a hospital load process. This is where you would map hospital names if you want. If you have your own cost-to-charge ratios that you would rather use, rather than the ones that are built into MONAHRQ, you could input those. 

Then you go through the process of building your Web site. The Web site wizard, again, is a step-by-step process of going through your data and building the Web site. Here is where you specify which QI, which Quality Indicators, you want to include. Those that are endorsed by the National Quality Forum are identified here with an asterisk. You could just use those if you wanted to. Then you customize your Web site. 

This is where you tell the system where you want the Web site to be stored, what server, what folder, which pages you actually want to include, and what specifics about the style that you want. This is where you insert your logo. This is where you tell the system what you want the Web site to call your data. We used "Health Care Portal." You can call it whatever you want. This is where you can change the colors to sort of blend it in with an existing Web site that you may have. Then you have your Web site, and it's literally that simple. 

We went through beta testing with 14 different people, 14 different organizations, including a number of State data organizations, a number of hospital associations. We had beta testers from the private sector, as well as from Canada. The Canadian Institute for Health Care Information was a beta tester. They tested it on a number of provinces in Canada. For many of them, they were literally able to generate a Web site in 1 to 2 days. For some, we had to provide some more technical assistance and it took a little bit longer, but the feedback that we're getting so far is that things are working pretty well with the folks who have downloaded the software and are inputting their data and building their own Web site. I'm open now for questions if you have any questions specifically about MONAHRQ. 

Margie Shofer: We have now entered our first Q&A, and as I mentioned earlier, there are two ways you can ask a question of our presenter. You can submit a question any time throughout this Web conference by typing your inquiry into the "Q&A" box located on the right-hand toolbar of your screen beneath the participant list, or by clicking on the "raise hand" button located at the bottom of the box containing the participants' list. Again, we'd really love to hear your voice, so I encourage you to ask your questions verbally. 

Anne, I do have a question for you. "What future changes do you expect in MONAHRQ?" 

Anne Elixhauser: O.k. I alluded to it a little bit earlier. We are currently working on the version 2.0 of MONAHRQ where we're going to be including the ability for host users to very easily go to the CMS Web site to download all the measures that are currently in the Hospital Compare Web site to subset the data file that you would download from the CMS Web site to just those hospitals in your State or in your data that you're interested in. Then MONAHRQ is being modified so that the CMS measures are being integrated with the Quality Indicators. 

We're just going through the process right now of merging those measures together so that, for example, all the heart conditions are in one group, and so you will have in-hospital mortality measures from the AHRQ Quality Indicators, and the 30-day posthospital mortality measures from CMS, and the heart process measures all included in one big package. We're incorporating also the HCAPS measures, the measures of consumer satisfaction, so that all of the CMS and the AHRQ quality measures can be brought into one place. We're also incorporating some additional, and what we're hoping to be, some fairly innovative ways of presenting the results so that the results—the tables and the graphics—are visually interesting and really easy for consumers to understand.

Margie Shofer: O.K. We have another question, a typed in question. "Can this be used for multiple hospitals?"

Anne Elixhauser: It's actually designed to be used for multiple hospitals. The ideal organization that would use this has hospitals from an entire area; for example, an entire State or several contiguous States. MONAHRQ has been developed so that, for example, if New York and New Jersey wanted to have a united Web site that provided information on all of their hospitals together, all of the hospitals in the hospital data for New York and New Jersey could be put together into one big dataset. The maps that you would get would show New Jersey and New York next to one another. The county paths of MONAHRQ, like the rates of hospitalizations, are based on the patient origin, so for patients from New Jersey who go to New York hospitals, you would actually see that the rates of conditions would reflect the fact that those patients are coming from these counties in New Jersey. MONAHRQ is really at its strongest when it contains multiple hospitals and all hospitals from a geographic area. 

Margie Shofer: I have another question. "What is the difference between MONAHRQ and the SAS version of the QIs?" 

Anne Elixhauser: As I mentioned earlier, MONAHRQ is based on the Windows version of the Quality Indicators, and the Windows version of the Quality Indicators is based on the SAS version of the Quality Indicators. The SAS version of the Quality Indicators was the first version that was released. Then in order to make the software as accessible as possible to as many people as possible, the Windows version of the QIs was developed, and this is the third generation of that. The information that you get out of MONAHRQ should be identical to what you get out of the SAS version of the Quality Indicators and what you would get out of the Windows version. 

Margie Shofer: I have another question. "Can each hospital get its own report?"

Anne Elixhauser: As I mentioned earlier, if you only wanted to make MONAHRQ available to participating hospitals, what you could do is create MONAHRQ using all of the hospital data, and then if you wanted to keep that data masked from all of the other hospitals, you could mask the hospital name, so it's just hospital A, B, C, D, et cetera. Then you could allow each individual hospital to know which masked identifiers are for them, so you would tell St. Mary's that they're hospital A, and then St. Mary's would be able to go into MONAHRQ and look at exactly what is happening for their hospital. They would then have the added benefit of seeing how they fared compared to other hospitals in the dataset in that State.

Margie Shofer: The questions are pouring in, so I have another one. "What kind of format will our data have to be in for MONAHRQ to read; example, SAS, dataset, or Access database?

Anne Elixhauser: Right now it could be an ASCII file or a CSV file, a Comma Separated Value file. I believe that the next version of MONAHRQ is being developed so that it can accept an Access database as well. I will actually have to get back to you on that. I know it doesn't accept the SAS dataset at this point.

Margie Shofer: Another question. "If we use MONAHRQ as a hospital system, will the statewide data be there for us to compare to, or will that only happen if there is a statewide entity to accumulate the data?" 

Anne Elixhauser: Yes. When I refer to the statewide average, that is actually an input file average, so what you would be getting there is the average for your input file. If it's only the hospital system, then it would be the average for your system. Remember, what I mentioned on when you create the Web page. There's actually a part where you have to say, "O.k., what do you call your data?" If it's data from Maryland, it would say the Maryland State average, but in a case where it's a hospital system, you would be inputting St. Mary's Hospital system average.  

Margie Shofer: I have one final question for you before we move onto John's presentation. "What sort of technical support can users get?" 

Anne Elixhauser:  We have very active technical assistance. There is an E-mail address,, it's on the very first slide, so you will have that available to you. We really try to get back to you within a day, no more than 2 days. We will provide you pretty much whatever technical assistance you need to get the system going. It's been very successful. I haven't heard any complaints about things being too slow or not being responsive. If you have questions about what form your data needs to be in or how do I do this, someone will respond to you by E-mail. If we need to look at output, you can send us that. If we need to get on the telephone with you, we'll do that as well.

Margie Shofer: I'm just going to add that that E-mail address is also going to be on the last slide that you will see before we end the Web conference. Thank you, Anne for your presentation. Now, I'm going to turn this over to John Bott.

Proceed to Next Section

Page last reviewed August 2010
Internet Citation: MONAHRQ's Preventable Costs and Hospitalization Mapping Tool: Webinar Transcript. August 2010. Agency for Healthcare Research and Quality, Rockville, MD.


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