OVERVIEW

AGENDA

MATERIALS AND PRODUCTS / PRESENTATION SLIDES

HOW TO REGISTER

REGISTRATION FORM

HOW TO PARTICIPATE ON AUDIO CONFERENCE

Data Books for Monitoring the Safety Net

The First in a Series of Three Free Web-assisted Audio Conferences
for State and Local Health Officials

September 23, 2003

TRANSCRIPT

Cindy DiBiasi: Good afternoon. Welcome to Data Books for Monitoring the Safety Nets. This is the first event in a series of three web-assisted audio conferences on monitoring the healthcare safety nets. These events are designed for state and local health officials.

The series is sponsored by the U.S. Department of Health and Human Services Agency for Healthcare Research and Quality, also referred to by the acronym AHRQ or AHRQ and the Health Resources and Services Administration or HRSA. My name is Cindy DiBiasi and I will be your moderator for today’ session.

In 2000, the Institute of Medicine released a report describing the healthcare safety net as “in tact but in danger.” The safety net is as you know is the nation’s system of providing healthcare to low income and other vulnerable populations. In particular, the report emphasizes the precarious financial situation of many institutions that provide care to Medicaid, uninsured and other vulnerable patients. It also examines the changing financial, economic and social environments in which these institutions operate and it looks at the highly localized patchwork structure of the safety net.

One of the five key recommendations in the report focused on the need for data systems and measures to assess the performance of the safety net and health outcomes of vulnerable populations. In response, AHRQ and HRSA are leading a joint safety net monitoring initiative. This initiative involves a three-part strategy focusing on both safety net providers and the populations they serve. As a result, they resolved to create two data books that describe baseline information on a wide variety of local safety nets. They developed a tool kit for state and local policymakers, planners and analysts to assist them in monitoring the status of their local safety nets and identify the data elements that would be needed to effectively monitor the capacity and performance of local safety nets. Information related to the AHRQ and HRSA initiative is available on AHRQ’s Web site at www.ahrq.gov/data/safetynet.

John Billings: Excuse me. This is John Billings calling remotely. I am in New York and they just had an alarm go off in the building and I have to leave so I apologize.

Cindy DiBiasi: Oh, John, OK.

John Billings: In New York we pay attention to those things.

Cindy DiBiasi: Yes, I bet you do. Go ahead.

John Billings: OK, thank you.

Cindy DiBiasi: Hopefully we will be able to talk to him later in this broadcast.

As we talk about the safety net, it is important to make sure that there is a common understanding regarding what it encompasses. As I said, the opened healthcare safety net consists of a wide variety of providers delivering care to low-income and other vulnerable populations. These include the uninsured and those covered by Medicaid. Many of these providers have either a legal mandate or an explicit policy to provide services regardless of a patient’s ability to pay. Major safety net providers include public hospitals and community health centers, as well as teaching and community hospitals, private physicians and other providers who deliver a substantial amount of care to these populations.

In addition to today’s event, two more calls will be conducted as part of the series this week. The next call, scheduled for tomorrow, September 24th, will focus on safety net data collection strategies and the topic for the third call, scheduled for this Thursday, September 25th, will focus on How Data can be used to tell the safety net story. I will tell you more about these calls later in the broadcast, but right now let’s turn to today’s call.

One of the challenges in monitoring the nation’s healthcare safety net is that safety net services are provided in a myriad of different configurations, largely at the local level. Today we will be examining the newly-published Data Books, which include information at the county and metropolitan levels. It focuses on 30 states and the District of Columbia. Together these areas cover 75% of the U.S. population. The books use data from a wide variety of sources to describe the status of these safety nets in 90 metropolitan areas and 1,818 counties in these states. The books provide a broad range of measures for monitoring the status of safety nets and the populations they serve.

Let me begin by introducing today’s panelists. In the studio with me I have Robin Weinick, senior research scientist and senior advisor on safety nets and low-income populations at AHRQ and Robert Seifert, policy director at the Access Project in Boston. You heard on the phone was John Billings, the director of the Center for Health and Public Services Research at New York University’s Wagner School of Public Service. We do hope to be talking to John later in this broadcast. Welcome Robin and Robert.

Before we begin our discussion, I would like to tell the audience a bit about the format of the web-assisted audio conference. First we will talk with our panelists and then open the lines to take your questions. We will give instructions on how to send your questions to us later in the program. In the meantime, if you experience any web-related technical difficulties during this event, please click the “Help” function in your window to troubleshoot your web connection. If it appears that the slides are not advancing, you may need to restart your browser and log on again. If you are on the phone, dial “*0” to be connected to technical assistance. Also, if you have difficulty with the audio stream or if you experience an uncomfortable lag time between the streamed audio and the slide presentation, we encourage you to access the audio via your phone. The number is 1-888-469-5316. This is the same number to call to ask questions when we get to the question and answer portion of the program.

Now I think we are ready to tackle today’s topic, The New Data Books for Monitoring the Safety Nets. I would like to talk to Robin Weinick about what did you set out to accomplish with the Safety Net Monitoring Initiative? You were a principle collaborator on these data books and worked to gather this data.

Robin Weinick: Right, Cindy, thanks. What we really found was we started with the IOM reports that you described earlier. They were from the Institute of Medicine and one of their key recommendations was that the data really did need to be gathered and compiled because when they went out looking for information, they couldn’t find what they needed. So that was the motivating factor behind their recommendations. As a result, our goal is to begin to provide a national capacity to assess the status of the safety nets throughout the country and the populations they serve and access problems for them. In particular, to really help local communities and state and local health officials by illustrating approaches to how you might measure the status and performance of the safety net and by providing benchmarks that they can compare themselves to.

Cindy DiBiasi: What areas are included in these books?

Robin Weinick: Our goal was to include as many areas as we possibly could and we are limited only by data availability. So we are in 30 states. Within those states, we are in every county. We are also in 90 metropolitan areas, including more than 300 counties and 170 cities in those metropolitan areas, again limited only by the availability of data.

Cindy DiBiasi: To clarify, this data was all data that was existing data.

Robin Weinick: Absolutely. We didn’t collect any new data for this. What we did was to go to a wide variety of data sources where we could get information down to the county level and pull those together so people would be able to do additional analyses to understand what is happening with local safety nets.

Cindy DiBiasi: And this is the first time it has all been pulled together in one place?

Robin Weinick: It is the first time.

Cindy DiBiasi: Great. What was the conceptual model you had in mind when you started working on this?

Robin Weinick: Well, we know that safety nets are largely local. When you have seen one safety net, you have seen one safety net. So what you really need it for is our data at the local levels, but the boundaries that matter differ from place to place. In one area, the city might be what matters. In another area it might be a multi-county authority. So we wanted to get our data down to as fine a local level as we could.

We also think that the health of the nation’s safety net and its capacity to provide care to low-income populations is somehow the sum of all these different local safety nets. So we wanted to gather data for as many geographic areas as we possibly could. We also thought it was very important to focus on patient outcomes, which is something that hasn’t always been done before. Since the factors that influence those outcomes are complex, we knew we needed a broad range of data to tell the story.

Cindy DiBiasi: Tell us how you selected the measures that you included and what types of measures are included in this?

Robin Weinick: Well, Cindy, actually if you don’t mind if we talk for just a second about the model that we really used. When we talk about what contributes to optimal health in the safety net, we know that there are a wide variety of things that are components of optimal care, from genetic and the environment all the way down to how people manage their own diseases and conditions. The safety net plays a crucial role here in terms of care availability and provider performance. We know there are also a number of mediating factors such as personal circumstances and community resources that also influence optimal health. So when we picked the types of measures, what we were looking to do was to get as broad a range of these concepts representing the measures as we could.

Cindy DiBiasi: How is the information in these books structured, Robin?

Robin Weinick: Well, the book actually has two major parts to it. The first book has some beginning material, which I am going to show you actually some of the graphs and charts from that where we actually summarized the information that we have learned. We tried to present what the bigger picture is across a wide range of areas. We also have an extensive number of tables where we actually provide detailed information for each geographic area on a wide number of measures. So we actually have very, very large data tables, some for metropolitan areas and the second book is actually specific to counties and states.

Cindy DiBiasi: The books are very well laid out. There is a tremendous amount of data in the books, but as you are going through the books you can see the format is very easy to read and to locate specific information.

Robin Weinick: Right. That was really one of our main goals. We want to make these as usable as we possibly can for our audiences. So whether what you need to find is how two measures might relate to one another across a wide variety of areas or whether you want to know a particular measure for Lackawanna County, Pennsylvania, you can do either of those.

Cindy DiBiasi: I am going to ask you about that because that is my old hometown. I know you don’t have time to talk about all the measures, but tell me about what you mean by “demand for safety net services.”

Robin Weinick: Sure. We have a wide variety of groups of measures of which demand for safety net for services is one. We also have some information, for example, on financial supports for safety net services, how the safety net is structured, as well as I mentioned on patient outcomes.

In terms of our demand measures, probably the two most important demand measures that anyone I know who works in a safety net thinks about are the poverty population and the uninsured population. So this figure, I am going to actually show you some figures from the book. We have actually taken out the labels of some of the geographic areas just to make them easier to read. Many more of the areas are labeled in the book. So what this shows you is the percent of the population below 200% of the federal poverty line. That is about $35,000 a year for a family of two adults and two children. What proportion of that population is uninsured? What you can see here immediately is a tremendous geographic variation, even within regions of the country. You can see, for example, Springfield, Massachusetts, St. Louis, Tacoma, Washington, at the low end here where Jersey City, Augusta and San Francisco are at the higher end with a larger proportion of their low-income population being uninsured.

I also wanted to take a look at the relationship between poverty and uninsured because people often think if I know one of these two measures for my geographic area, I know what the demand for safety net services is. It was very important for us to point out. This is just a scatter plot that shows you these data relative to one another. Each little dot is actually a geographic area, a metropolitan statistical area. What this shows you is that there is virtually no relationship at the metropolitan level between the poverty population, the proportion of the population that is poor and the portion of the population that is uninsured. You actually need both pieces of information in order to understand what is going on.

Another picture shows you the percent of the population below 200% of poverty that is enrolled in Medicaid. Obviously Medicaid is a federal-state partnership and the states take the main initiative for things like determining who is eligible for outreach programs and that sort of thing. It really varies tremendously from state to state, but you really can’t see it here. Again, we have taken some of the labels out to make it more readable. It also varies quite a bit within states.

Cindy DiBiasi: You mentioned Lackawanna County, Pennsylvania. So let’s talk about within a state, if we wanted to find out what percentage of the population over 65 in Lackawanna County was living under the poverty line.

Robin Weinick: Right.

Cindy DiBiasi: You would be able to drill down to that?

Robin Weinick: We can do that. I can look up in the books. I can look up in the electronic data books or in the safety net profile school that I will share with you a little later on and tell you that 10.6% of the population of Lackawanna County lives below the poverty line. Compared to Scranton, which is a city right nearby, where it is 15%. So things are considerably worse in the central city of Scranton than they are in the surrounding county of Lackawanna. So we can actually drill down and get down to that fine a level of detail or we can talk at a bigger picture level.

Cindy DiBiasi: I understand you also have some measures of what the overall healthcare system is like in different communities. Can you talk a bit about that?

Robin Weinick: Right. Well let me tell you first about some measures of what we know about community health centers and what is happening. What this picture shows, very interestingly, is that community health centers are in fact located where the poor people are located because if you look in counties where fewer than 6% of the population lives below the federal poverty line, 15.9% of those counties have a community health center. By the time you get up to a county with more than 20% of the population living below poverty, more than 90% of those counties have community health centers. This is a measure of the resources that are available and what aspect of what the healthcare system looks like.

So let me tell you about two cities. I like to call this “A Tale of Two Cities.” We are looking at Portland, Oregon and Newark, New Jersey, which are cities that are roughly the same size. You can see how very, very different they are with much higher HMO market penetration in Portland but much greater healthcare utilization as well as numbers of physicians per thousand persons in Newark, New Jersey.

For those people who say that that is not a very fair comparison, they are in two different states. State health policy can have a real impact. This is “A Tale of Two Counties”. We are looking at Orange County and San Francisco. Again, you can see how tremendously different they are where in San Francisco there is considerable public hospital presence. In Orange County there are no public hospitals, but there is a considerable investor-owned hospital presence.

Cindy DiBiasi: What other data are included in the books?

Robin Weinick: We also have quite a bit of information on community context where we have pulled data in from the U.S. Census to tell us about population size and growth, age distribution and ethnicity of geographic areas, income, unemployment and education. So we really have tried to not only focus on healthcare, but on all of the miscellaneous things that also happen in a community that may impact on healthcare.

Cindy DiBiasi: Does this tell us how well the safety net is actually performing?

Robin Weinick: Well, it is very, very hard to tell how any aspect of a healthcare system is performing. For the safety net in particular, as you mentioned very early on, a safety net is a very amorphous kind of a thing. It involves lots of different institutions, lots of different providers in lots of different locations. But there are a few really well-accepted measures in general of access to care that can help us start to understand what is going on. In particular, understanding preventable or avoidable hospitalizations. These are hospitalizations where if patients are receiving really good ambulatory care in the community, they really should not theoretically wind up in the hospital. For example, if asthma is very well managed in an outpatient setting, you don’t expect to find people hospitalized with it. Obviously there are always a few extreme cases, but in general rates of preventable hospitalizations can tell us something about what is going on because we know that preventable hospitalizations occur disproportionately among low-income populations.

We also know that birth outcomes are a really great way to tell what is happening with care in the community. So where you are really looking at the percent of births that have late or no prenatal care or the percent of low birth weight births. That really just starts to give you a sense of what is going on in a community.

So, what we took a look at were preventable and avoidable hospitalizations. These are per 1,000 children, ages 0-17. You can see again just the tremendous, tremendous variation within geographic regions from one city to another. Then we took a look at what the relationship was to poverty because we know that there is a really tight relationship and what you can see here is the relationship for children. Then if you take a look at the relationships for adults, there is actually a much stronger relationship for adults than it is for children. We don’t have any way to actually test this, but we are wondering if what we are seeing is the impact of some of the Medicaid and S-CHIP state children’s health insurance program expansion is really starting to break down the relationship between poverty and preventable hospitalizations for children.

Cindy DiBiasi: Can we summarize some of these “big picture” findings from the project?

Robin Weinick: Yes we can. We really went to a lot of trouble to do that. First I think the first big point I would make is that federal and state financing of the safety net really does help. We know that greater Medicaid coverage and higher disproportionate share hospital payments are generally associated with lower preventable hospitalization rates and better birth outcomes. We also know that public facilities matter. A larger public hospital presence is associated with better outcomes.

We also found interestingly, that more providers are not always the answer. We know that more pediatricians are associated with lower children’s preventable hospitalizations, but we didn’t find the same to be true for adults or for the relationship between have more obstetrician/gynecologists and birth outcomes.

We also found the levels of personal distress are concerns. Higher levels of poverty, unemployment, disability, lower levels of education, all of these kinds of things are actually associated with worse outcomes.

Cindy DiBiasi: We are going to come back. We have lots more questions for you, but before you go any further we will let you take a breather. We are going to go to Robert Seifert from the Access Project in Boston. The Access Project supports local leaders in their initiatives by providing them with assistance designed to enhance efforts by a (unclear) Access. Bob, you work with organizations around the country whose primary focus is to strengthen healthcare access. How are these data books going to be helpful to that purpose?

Robert Seifert: Cindy, I think that the data that are collected and presented in these books provide a great common ground and measurable target for discussion of policy initiatives at the local level. Data like these are all too often absent in discussions of local healthcare system and health policy questions. The data can help shed light on where policy efforts might be focused and to support decisions that are based on concrete data rather than on anecdote, which is frequently the way that policy is made in local discussions. It helps us to get past the arguing about the data stage that often befalls a lot of problem solving attempts in local communities by providing this common ground.

The data also offers the foundations of a roadmap to safety net improvement through the analysis that Robin just talked about, the multi-variant analysis relating it to outcome measures and so forth. But also uses the data to remind us that there are a number of important factors such as local economic conditions and racial disparities that go beyond the realm of the healthcare system into much broader policy areas.

Finally, another great use I think of the data is that it can help combat the isolation that is felt by local providers and policymakers and advocates that are struggling with their own problems in their own communities. Providing this information helps to bind these communities together in a way and helps local actors understand their circumstances relative to other communities. It gives them a voice, a very important voice that needs to be heard in policy debates about the future of the safety net.

Cindy DiBiasi: Let’s talk a little bit about why aggregate data are not sufficient. What are some ways that the availability of local data improves on, for example, state or national data?

Robert Seifert: Well, Robin touched on it a little bit in your earlier discussion. Variation across geographic areas, regions and states across the country and so forth, is well documented, well known. What is striking in this data book is that it allows us to look at variation within geographic areas. This is crucial, of course, as we have been talking about that because safety nets are of course local facing uniquely local problems and local circumstances. Good information about these local situations is vital to meeting a community’s needs.

I think I can best illustrate this with an example that I have taken from the data book. If we look at the situation of people with limited English proficiency, this slide is looking at the rate of people with limited English proficiency in the Hartford metropolitan area in Connecticut and in the United States. You can see that the percentages are relatively the same. Connecticut is not necessarily known as a state with a high limited English-proficient population, but if we look beyond that, deeper into the Hartford metropolitan area, we can then see that the City of Hartford itself has actually a very, very high proportion of people with limited English proficiency. This large non-English speaking population signals a need for access to language interpretation service as part of the safety net infrastructure. This is information we would not have if we were just comparing the Hartford metropolitan area to other metropolitan areas or Connecticut to other metropolitan states. So the ability to look deeper and to look within local areas and the variation within local areas is a great advantage to people who are trying to make improvements in the safety net.

Just one other point that I want to make on this is that the diversity of the data in the book allows us to look at peer communities. For one community with a particular safety net situation to look at another community with possibly similar demographic information, for example, which maybe has better or worse safety net outcomes for comparison purposes, for benchmarking purposes, to look and see. Here is a community all the way across the country that looks like mine, but their safety net seems to be working better and what can we learn from that? Some of the profiling tools that Robin is going to talk about in a little while I think is a great way to make those comparisons using the data in these books in a very simple way.

Cindy DiBiasi: You talked a bit about how valuable the data are in these books and there are 118 different measures, yet you are saying that local data are elusive. Why would you consider that elusive?

Robert Seifert: Well, there is never enough. I think that people who are listening in and looking in on the web are already thinking of questions about “is there this in the data book? Is there that in the data book? Why isn’t there data on uninsured rates in cities and counties?” I think the point is, as Robin said, these are data that are compiled from existing sources. There is what there is; we’d always like there to be more. In the absence of some of those things, though, the fact that there are so many measures in this one place helps us because we can use substitutes. One of the things that Robin and John talk about in the book are indicators of personal distress, which actually turn out to be very good prophesies for uninsured, the uninsured rate in local areas that we don’t have. So, yes, we wish there were more. Maybe someday there will be if the resources are there to collect it. But for the time being, the fact that all of these data are in one place, we can look and have the data say things that we want them to say without necessarily having the exact indicators that we would like to have.

Cindy DiBiasi: As we talk about the purpose of these data books is to contribute to efforts to preserve and strengthen the safety net. Do you think that they are serving that purpose and what else would you like to see?

Robert Seifert: I do. Again, I think that the major benefit of these data is that they are all in one place. They give us a very local perspective. I meant to say the word “local” a lot more times than I have so far because I think that is critical to this and really the important point here.

I think these data are very useful for making comparisons with other communities, for providing warning markers of potential problems in local safety nets and as a way to monitor improvements or deterioration in safety nets over time.

I want to emphasize though, as a card-carrying data nerd, it actually pains me to do this, but the data don’t tell the whole story. No set of data can tell the whole story. They are starting points. As comprehensive as they are, they really can’t capture all of the important features of a local safety net. Some of the data aren’t there, as we have talked about, and some things are just not easily measured. I want to caution users of this data not to fall into the measurement trap of saying if there is not a measure for it, it doesn’t exist. Because there are important things that you can learn from the community. Go into the community. Learn from the providers and from the consumers in communities. Some of the texture that these data point to but really can’t tell you the whole story about. Use them as a jumping-off point, but then go and learn from the community itself what is behind the data. Why are the measures as they are? I think that is the step beyond the data book that I would suggest people take.

Cindy DiBiasi: Thank you, Bob, and we will come back to you. Before we move on, I would like to ask Robin about the availability of this new data. Now that all the data is available, how can our listeners access the product?

Robin Weinick: Well, first I really want to thank Bob. I am excited about this, obviously having worked on it for a long time. But he makes it sound like the best thing since sliced bread. We hope our users think that as well. So there are a variety of ways to access the data. We do have two print volumes available. The first book focuses on metropolitan areas with the beginning of that book providing some big-picture overview and then getting into all the details and a second book that focuses at the state and county level. This includes rural areas as well so it is every county in 30 states. We have a bunch of electronic files as well. The books themselves are actually available in an electronic version as well as Excel spreadsheets for folks who do statistical calculations we have the data available in a number of statistical formats as well. All of this information is available on the Web site, which is www.ahrq.gov/data/safetynet. The information we have there will tell you how to order copies of everything. It will tell you how to get a copy of the print books, which we will send to anyone for free. All they have to do is ask and there is a variety of ways to get that information. If you look at that Web site it is going to show you right on the first page of that Web site. Just scroll down. It is going to tell you how to order them. There are also ways, for example there, to get technical assistance with the data or provide feedback as well.

What I would really like to tell you about is the Safety Net Profile Tool. This is for people who just want quick, online access. I know it is a little hard to see on the screen. Unfortunately there are some technical difficulties. But what this tool lets you go in and do, you say I am going to start a query and then I am going to go in and I am going to choose what type of geographic area I want to look at. That could be a metropolitan area, a county or a state. Then what it will actually let you do is go ahead and compare different geographic areas. For example, if you happen to know, you mentioned you are interested in Lackawanna County, Pennsylvania, that that is an area that you are interested in and you want to compare to other counties that may be similar but you don’t know where else. For example, there could be a similar county out in California. We actually provide you with a tool where what you do is say find me some similar counties. It is going to look through the data set based on population, size and poverty rate which are two very key aspects to what the safety net might look like and it is going to find some suggested comparison areas for you. You can choose any or all of them or you can choose your own comparison areas from any of the states, any of the counties included in the data book. It will then ask you to choose which of the 118 measures you would like. You can get a few of them if you would like or you can have all of them. Then it is going to go ahead and actually produce a table that just has the information that you have asked for. So if you don’t want to page through a book, this is a quick and easy way. For example, if someone asks me what percent of all admissions in Polk County, Iowa occur in public hospitals? I can click through and in probably 30 seconds or less have the answer, 10.8%. It really gives you the ability to access just the data you are looking for, just when you need it.

Cindy DiBiasi: Sort of like the “Ask Jeeves” of data. (Laughter.)

Robin Weinick: Very much so.

Cindy DiBiasi: Hopefully our listeners are going to take advantage of all these new resources, Robin. It certainly sounds as though you have thought of everything when it comes to being user friendly. This is not data for data’s sake, that is for sure.

In a moment we are going to open up the discussion for questions from our listening audience. There are two ways you can send in your questions. We encourage you to ask your question by phone. If you are already listening by phone, all you have to do is press “*1” to indicate that you have a question. If you are listening through your computer and want to call in with questions, the number to dial is 1-888-469-5316 and just press “*1”.

When you are asking your questions on the air, please do not use the speakerphone to ask your question and if you are listening to the audio through your computer, please turn down your computer volume after speaking with the operator. There is a significant time delay between the web and telephone audio.

If you want to send a question via the Internet, simply click on the button marked “Q&A” and on the event window on your computer screen, type in your question and then click the “Send” button. One important thing, if you prefer not to use your name when you communicate with us, that is fine. But we would like to know what state you are from and the name of your department or organization, so please provide those details regardless of the way in which you transmit your question.

As you are formulating your questions or queuing up on the phone lines, I would like to say a few words about our sponsors. The mission of AHRQ is to support and conduct health services research designed to improve the outcomes and quality of healthcare, reduces costs, address patient safety and medical errors and broaden access to effective services. AHRQ’s User Liaison Program serves as a bridge between researchers and state and local policymakers. ULP not only brings research-based information to policymakers so that you are better informed, but we also take your questions back to AHRQ researchers so they are aware of priorities at the state and local level. Hundreds of state and local officials participate in ULP workshops every year. The audio conferences are being co-sponsored by the Center for Health Services Financing and Managed Care and the Department of Health Resources and Services Administration, HRSA. HRSA is the Department of Health and Human Services access agency. It assures the availability of quality healthcare to low income, uninsured, isolated, vulnerable and special needs populations. Its mission is to improve and expand access to quality healthcare for all Americans.

I would also like to recognize the special contribution of Rhoda Abrams, the director of HRSA’s Center for Health Services, Financing and Managed Care. I would like to take a quick moment to thank Rhoda, the director of HRSA’s center, because she has been instrumental in helping to develop and produce these safety net products.

We would appreciate any feedback you have on this web-assisted audio conference. At the end of today’s broadcast, a brief evaluation form will appear on your screen. There are easy-to-follow instructions on how to fill it out. Please be sure to take the time to complete this form. For those of you who have been listening by telephone only and not using your computer, we ask that you stay on the line. The operator will ask you to respond to the same evaluation questions using your telephone keypad. Your comments on this audio conference will provide us with a valuable tool in planning future events that better suit your needs. Also you could email your comments to the AHRQ User Liaison Program at ulp@ahrq.gov. Now let’s go to some of our questions.

On the phone with us we have Steve from Maryland. Hi Steve.

Steve Forstancer: Hi. My name is Steve Forstancer. I am with the Maryland Healthcare Commission. A question I have is if the key point for the safety net is state and federal programs, and the money has been cut in virtually every state and the federal programs, what do we do with the safety net next?

Robin Weinick: Well that is a pretty complicated question. Obviously big issues here, particularly in light of what is happening with the economy and what is happening with state and federal budgets. I would argue that there is no simple answer, but what the data books can help us do is understand the impact of those types of changes. We now have some baseline data to know where we are starting from so that as changes do occur over time, regardless of whether they are budget-related changes or policy-related changes, will understand what is happening.

Steve Forstancer: OK, thanks. I appreciate that because I think with a baseline now going forward, we will see the impact.

Cindy DiBiasi: Thank you, Steve. Also on the phone from Minnesota we have Sunny. Hello?

Stephan Gildemeister: Hello. It is actually Stephan Gildemeister from the Department of Health in Minnesota. Quick three questions for Robin. First of all, our compliments. This looks like a really interesting resource and we are going to definitely take a look at it.

Robin Weinick: Thank you.

Stephan Gildemeister: A couple of questions. I think the first question is, and maybe that is a tough one to answer, of the 118 variables that you are looking at, sort of what are the data sources and related to that, to what extent are they directly comparable across states? I would expect there are different measurement practices in each state. Lastly, what proportion of the measures are direct measures versus estimates from multi-variant analyses?

Robin Weinick: OK. I can answer all of those. I am actually not going to sit and list all of the data sources for you. I believe we are at about 15 or 16 different data sources. But what you can do is if you look in the back of Book One, the third part of the book, has a technical appendix that describes every measure, its definition and the data source that it comes from. So you will see we are using census data; we are using data from the Uniform Data Source; we are using data from the National Health Interview Survey, the current population survey. So we are in a wide variety of areas. We have really tried to work with only datasets that would be comparable across states so we have tried to use things for example that are collected nationally but where we can actually go down to a local level using those data so we know the methodology was the same across states. None of the measures in the book come from multi-variant analyses. So they are all estimates based on either survey or other data that are done directly. We have done no simulation modeling or anything like that to produce these numbers.

Stephan Gildemeister: Thanks.

Robin Weinick: Thank you.

Cindy DiBiasi: From Nevada, which is one of the 30 states included in the data book, Laurie Olson is on the line. Hello Laurie. Oh, is Nevada one of the 30 states? I am sorry.

Robin Weinick: Well, you answered correctly. (Laughs.) Nevada is one of the 30 states. Again, the data access tool, because I just found out about Nevada, very quickly lets you access some of the information so I can, for example, tell you right now that in a Las Vegas metropolitan area, the expenditures per person below 200% of poverty from Medicaid are $1,443 per person. So again, just a way to access those data and all I knew right now was you want some information for Nevada.

Cindy DiBiasi: OK. A question from Deborah Kleckly from the Jefferson County Department of Health in Alabama. “Do you have any suggestions on how communities, which are not included in the book, can best use the information? You had spoken earlier about proxy methodology.” Bob, do you want to take that?

Robert Seifert: I can take a shot at it. I would say that as Robin explained, the Profile Two on the web and also the book itself allows you to find communities that are similar to yours in the book and understand what the data is of those communities. It would depend on what you were trying to accomplish with the data to determine whether that was of any use to you or not. I would say though that the use of the data as a baseline is probably universal, even if your state or community isn’t included. You would be able to point to these data over time as the data are updated and trends become apparent to say there are communities like ours even though ours isn’t in there where the safety net is improving or deteriorating and we should be concerned about that.

Robin Weinick: I would also like to add that we will be doing one update of the dataset. I don’t know if we will be going beyond that but I know we have committed to one update of the dataset. We are happy to include additional state’s data as they become available. For example, one of the core things that we need for this dataset is to have hospital discharge data so that is the primary reason why states that are not included are not included. So as additional states become available, we will be adding them in. For example, Texas was not included in this round of data, however, they have since joined the Agency’s Healthcare Cost and Utilization Project, which collects hospital discharge data so we will be including Texas in the update of the dataset.

Cindy DiBiasi: Is that the best way for a state to get in, to get involved in that project?

Robin Weinick: On an ongoing basis, of course, we work with all the states towards increasing participation in that project. We do have a few states that have provided us with hospital discharge data directly separate from that project and we have included those as well.

Cindy DiBiasi: Tony from Minnesota’s Primary Care Association want to know, “Where are the city-level data available on the Web site?”

Robin Weinick: You have got several ways to access this. The city data are always shown under the relevant metropolitan area. So for example, for the Washington, DC metropolitan area it will show all of the surrounding counties, plus Washington, DC proper. Or you may be more interested, for example, in Minneapolis. But the way you find that is either to look at the books themselves. Again, you would go to Minnesota and you would look under Minneapolis metropolitan area to find the city of Minneapolis or the City of St. Paul in particular.

Or you can again use the Safety Net Profile Tools. If you look at metropolitan areas and you choose, one of the things it will ask you is if you would like to see all the components of the metropolitan area. You choose that, you choose your measures and you will see what you are looking for.

Cindy DiBiasi: Question from Shari Isert from Denver Health. This is a question that I think possibly could take up the rest of the web cast. A really comprehensive and good question. “What are you expecting, how are you expecting this information to be used by researchers and policymakers? What questions are you attempting to answer and what changes do you foresee occurring?”

Robin Weinick: Well, I can tell you that these data are ripe for use right now in a number of ways. For analyses in and of themselves independently or by merging them on to other data sets that people may have that they are interested in. We haven’t actually started doing a lot of digging around in the data beyond what I have presented to you here today. Accumulating the data and putting it in a usable format so people could understand the basics of what is going on in their local area was our big first step. So we have gotten to that big first step and what I would love to hear certainly from any members of our audience at any time, is their feedback on what kinds of questions it would be helpful for us to answer for them? What additional information can we provide? We have a number of ways to do that, but probably be easiest is to email safenet@ahrq.gov. That is safenet@ahrq.gov.

Cindy DiBiasi: Bob, you are on the frontlines of this. What do you foresee?

Robert Seifert: If I could just first of all add to what Robin said. If people would also, in addition to asking AHRQ, giving AHRQ the questions that they would like to see them answer, let Robin and AHRQ know what you have done with it yourselves. Local, local, local, local. How have you in your communities made use of the data and maybe there is some way of gathering that information and making it available to others so that they may be able to replicate some of these analyses.

Robin Weinick: That is actually very important to us to understand how you are using the data. We need to understand in what direction we should be headed in in the future. If you order a copy of the books, there is a business reply card that asks you a couple of basic questions about how are you using the information. Or you can email us from again, the same Web site that we shared with you earlier.

Cindy DiBiasi: We have a couple of people on the phone. Maybe they will share with us their insights on this. Sophie from New York. Is that New York? New Jersey. I couldn’t read that second letter. Go ahead.

Sophie: I am from the Board of Pharmacy in New Jersey.

Cindy DiBiasi: Sophie, could you talk a little bit louder, please?

Sophie: Sure. I really would like you to repeat the original web access code that you gave us because I didn’t catch all of it and I want to make use of the data books.

Robin Weinick: Sure, absolutely. It is www.ahrq.gov/dhea/safetynet. That should be up on your screen.

Cindy DiBiasi: Did you get that, Sophie?

Sophie: I have got it all. Thank you so much.

Cindy DiBiasi: Let me ask you a question. Are you still there?

Sophie: Yes I am.

Cindy DiBiasi: How are you planning on using the data?

Sophie: Well, that is what I am trying to figure out. Our particular agency isn’t really tied into the safety net to that extent, but we were interested in the project and the methodologies that you are using. We wanted to find out how you are communicating with such a large group and that is why I am monitoring this call, program.

Robin Weinick: Great, that is wonderful. We are happy to provide assistance to states or localities in using the data so if you have a question that you are trying to answer, let us know and we will see what we can do.

Sophie: OK, thank you.

Cindy DiBiasi: We have from Arizona, Howard on the phone. Hello?

Howard: Yes. Thank you very much. The question that I have is that we have been using data in trying to do a rural health assessment for the State of Arizona. One of the things that we are doing is the issue, in terms of your database, is whether or not that all the data that you are collecting are all at one point in time. In other words, they are consistent, for example, for the year 2001 for all your data or are they all mixed?

Robin Weinick: Different measures do come from different years. In general, they are from anywhere between 1999 and 2001. What we are hoping to do, the hard thing the first time is getting everything together. So the update, what we are hoping to do is move to the most recently available data year that we can for as many of the measures as we can.

Howard: OK. Thank you very much. I understand how difficult that is.

Robin Weinick: Thank you, I appreciate that. It is great when somebody knows what you are going through.

Cindy DiBiasi: Robin, is there a way to actually search for a specific timeframe?

Robin Weinick: There is not but you can certainly search for a specific measure. We actually have a whole list of the measures that is searchable on the Web site and it will actually tell you what year each of the measures come from.

Cindy DiBiasi: OK. A question from Nancy Libbyfisher. She says, “It appears that data have been segmented by age. Have they also been segmented by gender?”

Robin Weinick: Only some of the data are segmented by age, particularly information on uninsured poverty levels and on population size. They have not been done by gender.

Cindy DiBiasi: Is that something that you expect to happen in the future?

Robin Weinick: If people have a real need for it and we hear from enough people we could certainly include that as well.

Cindy DiBiasi: Richard Senlenson, the map showing data collection areas indicated data from Clark County and Esmeralda County. What about the rest of the State of Nevada?

Robin Weinick: That is actually just an artifact of what you are seeing on the screen. If we are in a state, we are in the entire state and we have data for every county. So that is just an artifact of how it is appearing.

Cindy DiBiasi: OK. So get the data and you will find out if you wanted to know about another one of the counties.

If the data books don’t have information on the state or area, does it meant that the state chose not to participate?

Robin Weinick: It does not. We did not go to the states and ask them in particular to provide us unique data to participate. We are using data that they have already made publicly available to do this. What it really means is the data weren’t there rather than the state didn’t, had not chosen to participate. There is really no issue of that.

However, if any state that is not included would like to work with us to provide us with more data, we would be happy to talk to them.

Cindy DiBiasi: OK. Tina Edward from the Oregon Health Policy and Research wants to know, “How often do you plan on publishing and updating these volumes?”

Robin Weinick: Right now we have funding for one update of the data set. It won’t be the books; it will just be the electronic data set as well as the profile tool being updated in early 2004. Unfortunately, we don’t have funding beyond that and so if you all think, in the audience, that this is a useful product and you let me know that, obviously that is something that we can consider because what we are primarily interested in is meeting the needs of our constituents in our audience. So the more you can let me know about what you need in the future, the better we can meet those needs.

Cindy DiBiasi: Bob, let’s talk a little bit creatively here. What do you see as some of the best uses, perhaps the biggest needs out there? How can this data really be used effectively?

Robert Seifert: I think I touched on it earlier, when I talked about the date providing a common ground for local discussions. I have been involved with local groups in communities that are working on access issues. So much time gets used and eaten up, really, arguing about whose data are right, what the real story is. It is a “they said, we said” kind of situation that really detracts from the substance of policy discussions that are going on. The fact that now here is a source that to the extent that it provides the information that people can base discussions on and agree on because these are from reputable, national data sources. It saves a lot of time. It saves a lot of potential acrimony in some of the conversations that go on. I think it really does facilitate making a lot more progress in improving the health system at local levels. So I see it as useful to all parties who are interested in improving the safety net and the healthcare system in general, in communities. That is not just policymakers and healthcare providers, but it is consumers and advocates as well. Providers of ancillary social services, really there is a whole network of people sort of at the periphery of the areas that the data really described that can benefit from it as well because it does provide this foundation of common ground for discussion.

Cindy DiBiasi: Are there findings in the data book that you found to be particularly surprising or counterintuitive?

Robert Seifert: I think that yes. I spent a lot of time when I first got the data just kind of thumbing through it in my leisure time. One of the things that Robin talked about before, I think was very interesting. The lack of association between poverty and uninsurance across the country. It is not very intuitive to think that there is no real relationship and...

Robin Weinick: Although Bob, I would like to say that that doesn’t mean there is no relationship for individual people. What it means is that a large geographic area level at a metropolitan area level that there is no relationship. You need both of those pieces of information to understand demand for the safety net.

Robert Seifert: So when you are in a city where, for example, you may not have the uninsured rate, as we talked about before. We don’t have that below the metropolitan area. You might think, “Oh, I will just go get the poverty rate.” If we have a high poverty rate, that means we probably have a high uninsured rate too. That seems not to be borne out by the data. That was surprising to me. But also the fact that there are these other proxy measures that are available, these personal distress measures that are noted in the book, gives another opportunity to go and understand what the access issues are, what the uninsured, that sort of “phantom” uninsured data might be with something with which there is a better, a stronger association.

So that is one area that I thought was very interesting.

Cindy DiBiasi: One of our listeners, Tim Burac, says, “I have looked at some of the measures hoping to find data related to homelessness. I can understand why it is difficult to get standardized data on homelessness, but is there anything on the horizon that might allow additional data about housing status to be included in the data set?

Robin Weinick: Well, I will tell you my favorite answer to these questions is if you can tell me where to find the data, we will include it. The problem is actually not that we are unwilling to. We are having to put in any measure that is relevant but finding data on homelessness at all to begin with is a particularly difficult topic but much less to get it down to the county level, which is what we need. It is virtually impossible. There may be for example, one state that has done a survey of its counties to try to estimate homelessness, but we know of no data source that goes across all the states that were in that could give us that information down to the county level. So if you can share information with me on where to find the data, we will include it.

Cindy DiBiasi: One of the things in your last comment, Bob, that seems to lead to the question of, we have to be careful. Again, as you said, this is data and we could draw a lot of conclusions from this data. Once people start to analyze these numbers and try to make assumptions from these numbers, we are just as likely to be going off in the wrong direction as the right direction if we are not careful. So there is more to it than just the numbers. It is how we are analyzing these numbers.

Robin Weinick: Absolutely. And as Bob said, the data can only give you part of the story. If you find out that a particular measure looks what you think is high for your geographic area, the first thing I would suggest doing is looking at some neighboring areas and looking at some other similar areas to see whether you are really high or low compared to then. But then also looking around your community to start to understand the “why’s”. Data can tell you a lot about what is happening, but it can’t tell you a lot about why it is happening. So understanding for example, that three bus lines just shut down that used to run from one neighborhood to a particular hospital so people could get their care in the outpatient clinic. You are not going to find that in our data set or most other data sets. But if you know that is what his happening in your community, it is going to tell you a lot about what is going on with the safety nets.

Cindy DiBiasi: A question from the Department of Health in Massachusetts. Nancy Wilbur wants to know, “Is it possible to download SAS files and import them into our system, recode or do what we would need to do on our end, and use your data set in combination with ours. For example, loading in local Medicaid per-person costs, that they don’t exist in the data set (unclear).

Robin Weinick: Absolutely. Nancy, I can tell that you, like Bob, are a big data enthusiast. Yes, we have the data available in SPFS and stata format, as well as in ASCII formats. You can download those off the Web site. We do include FIPS codes, Federal Information Processing Standards, which are the standard way to identify a geographic area so that you should be easily able to merge our data on to any other data set that you have that also has FIPS codes. Again, going back to our Web site, www.ahrq.gov/data/safetynet and I will tell you something, Nancy. Bob just wrote me a little note that says, “That is so cool.” (Laughter.)

Cindy DiBiasi: We are glad you like it. From Lincoln Lancaster County Health Department, “How can a state become a part of the dataset? How can Nebraska contribute?” By the end of this call, we are going to have all 50 states. (Laughter.)

Robin Weinick: That is right. I had said the best way to do that is you are going to have to get in touch with me personally and we will talk to you about getting involved with all of our different data collection efforts. Again, you can just send an email to safenet@ahrq.gov. I am Robin Weinick, again, and I will be the person answering all those emails. Given the number of people on this phone call, I may have a large number of them to respond to next week so be a little bit patient. I would be more than happy to work with you to get your data included.

Cindy DiBiasi: How current is the information and is the data set based on lowest common denominator? Are we talking about comparing 1999 data in Arkansas, for example, to 2002 data in Missouri?

Robin Weinick: No. Actually we are not. We are better than that. So what it is if a measure is in the data for 1999, it is for 1999 for every state and every county that we include. A different measure, however, a different variable or data observation, will actually be for a different year. So for example, if we are talking about the percent of uninsured and we are talking about data from 1999 through 2001, it is a combined estimate for those years. It is for those years for every geographic area that we are in.

Cindy DiBiasi: A question from Thomas Solina. “Is this data also available on a national level so we can compare local data to the national average?”

Robin Weinick: Some of these data are. We do not actually include a national average because we only include 30 states, we didn’t want to be misleading about that. For some of these data, however, the readily published information is available at the national level. There are a number of data sets, for example, that provide information about the percent of the population or percent of the low-income population that is uninsured. You can go to the Census Web site to get information on the percent of the population nationally below poverty. The national statistics are actually the easy ones to come by. It is the state and local and particularly getting down to the county levels that are harder to find.

Cindy DiBiasi: How long were you working on this, Robin?

Robin Weinick: It has been more than two years.

Cindy DiBiasi: Did you find geographically, the states that are not involved in this, was there any consistencies among those states?

Robin Weinick: Not really. Mostly it just has to do with sort of what kind of data and information that they have available, particularly the availability of hospital discharge data, which different states have felt a different extent of need for. Some states have very well-developed systems, and some states have systems that may meet their needs but may mot give us the information we would need to include them.

Cindy DiBiasi: You mentioned earlier that the data book should not be expected to capture all of the important features and demand structure, extra outcome community safety net. What are some of the other issues to examine and how would you go about doing that?

Robert Seifert: I think the issue of access to healthcare, access to the safety net is complicated and often as much psychological as actual. There are issues in communities that I am familiar with. Access versus perceived access. How do people feel about whether or not they are welcome at healthcare providers in the community? Cultural barriers to access. Language barriers to access. Financial barriers to access are something that we have come across quite frequently recently, the issue of medical debt and whether people feel comfortable going back to facilities that they owe money to. We don’t really have very comprehensive data on a lot of those things, so you need to go to the community and you need to ask the people who are using the services and the people who are providing the services. What are your policies on paper and then how are they, the people who are responsible for implementing those policies, how do you do that?

Cindy DiBiasi: For example, let’s be specific. When you say, “go to the community”, who are you talking about? At a community level, who would you go to?

Robert Seifert: I would go to people who use services at a particular facility. I might work with a local community organization to survey community members. Come up with a short survey to ask them about particular access issues that people in the community might understand to be an issue but don’t have a lot of hard data about. I think that there is a great opportunity here to use the data in the data book to then jump off at your own community level and make new data, collect data, not just rely on this secondary data that is provided here but to answer specific questions that are specific to you.

Cindy DiBiasi: This data really can be used to shine a light on a problem in a local community.

Robin Weinick: Absolutely. We are hoping that is how people use it. Our goal here is to provide state and local policymakers, planners, analysts, health officials, local community access coalitions, with the information that they need to meet their local goals. Sometimes that means you need information on how big the problem is or what resources are available to resolve it. So the whole goal here is to put that date out there and as people will see on the next two conference calls that you discussed earlier, and I am sure you will mention again later, we actually wanted to provide some tools as well so we have made those available to people in addition to making the data available.

Cindy DiBiasi: I would like to remind people also that we would like to hear from you to get your ideas for how you might use this data. You were talking about, and I don’t want to jump ahead to the next book that is coming out, the updated version, but talking about there is funding for at least one more book. How soon do you see that and what types of comments, changes will you be making in that book?

Robin Weinick: We actually will be starting to work on that as soon as this is done. So we want to get the whole first one wrapped up before we moved on to the second one. At the moment, we don’t have, at the moment, any new data to include because we haven’t learned about any new data sources since we have gotten started. We will be adding some additional states, as I mentioned. Texas in particular will be joining the data set. We would love to hear from people, “Hey, we know a data source that has information on topic X at the county level.” We want you to include it and I am happy to talk to people about the grant.

Cindy DiBiasi: We would love to hear from people right not just in terms of just giving us some ideas on how you might use this data and some of the things that you would like to see. We encourage you to ask your question by phone, and if you are already listening by phone, it is very simple. All you have to do is press the “*1” to indicate that you have a question. If you are listening through your computer and want to call in with questions, dial 1-888-469-5316 and then press “*1”.

Richard Fenleson, State of Nevada Emergency Medical Services, has a data collection system known as REMSTAT that is used by ambulance and fire departments. Was any of this information used in your data book?

Robin Weinick: No, because there is no single national source that I know of to obtain those data for all the states. That is wonderful for Nevada, but we are trying very hard not to include data that are only available for one state because it makes it very hard to compare what is going on across all the other states. Unfortunately, I don’t know of any national system to collect those types of EMS data in a consistent way across states that would enable us to be able to include them. But if he knows of one, I would be more than happy to hear about it.

Cindy DiBiasi: Let’s talk a little about your project and how you would be using this data.

Robert Seifert: Well, I think I am going to be using it in much the way that I have been talking about. Our project works with local groups in communities across the country that are trying to promote improvements in access to healthcare, particularly for uninsured people but not exclusively. There really is, as my first slide pointed out, a thirst for local data in those communities, a need to know about certain measures and how those measures compare to other geographic entities. So I think that what I will be doing with it is taking it and making the groups that I work with aware of it and helping them figure out how it can help them in their efforts to improve access in their communities. I haven’t made specific plans yet, but I will be. On the plane on my way home.

Cindy DiBiasi: You’d better call in tomorrow or Thursday and let us know. On the phone with us we have Deborah from Illinois. Hello, Deborah.

Deborah: Hi there. I am with our state child welfare agency and certainly this data looks great and ripe for exploration. One thing that pops to mind about how we can use it is to look to see where our kids are compared to places of poverty and access or not to the safety net. Certainly Medicaid is our insurance program, how our kids get services. So the question I have, not having had a chance to look at the different measures is does this information include info about Medicaid providers, the different types? For example, dentists. Access to dental care is extremely important and if this information could note how many enrolled providers, whether they are dentists or any other Medicaid provider, knowing where they are and looking to see how that matches up with just general population as well as the poverty population using them would be very helpful.

Robin Weinick: Great. That is a wonderful suggestion, thank you. One of the biggest problems that we have had with the safety net as well as most other descriptions of the healthcare system is we don’t know terribly much about what happens in the ambulatory care settings. We know a lot about what happens in hospitals, but there aren’t very many consistent data sets. I don’t actually know whether information on enrolled providers at the small geographic level is available from the Centers for Medicaid and Medicare Services, but I will certainly be making a phone call to them to find out. If it is available from one dataset, we can certainly do that. What we can’t do is go to each of the states to get that information directly.

Deborah: OK, thank you.

Robin Weinick: You are welcome.

Cindy DiBiasi: From Arizona we have Howard back on the phone. Hello?

Howard: Yes, thank you. I have a question. Does the database also include the American Indian population on reservations? Our state has 21 recognized tribes and it also has about 5% of our population is American Indian.

Robin Weinick: Great. It is very dependent on the particular data set that is used. So for example, all the information from the census would include people living on reservations. I couldn’t tell you. I would actually have to go back and look it up for each of the individual data sources, but it is very dependent on what their data collection methodologies involved.

Howard: Just as a follow up related to that, do you also include information regarding federal facilities?

Robin Weinick: We have actually very little information about facilities in particular. Is there some particular piece of information you would suggest that we include?

Howard: Well, I was thinking, for example, the VA system could also be part of that safety net.

Robin Weinick: We could certainly add something that would look at the presence or absence of a VA facility.

Howard: OK. Thank you very much.

Robin Weinick: Thank you for the suggestion.

Cindy DiBiasi: Robin, let’s be really honest right now. What do you think is the strongest group of data in the book and what would you like to see improved?

Robin Weinick: I would love, the particular area I would love to see improved is any information we could get on ambulatory care services. There is just so little data out there that exists at all, much less down to the local level. So that is probably to me where the biggest holes in the data set are.

Obviously, like everybody else, I would love to be able to see uninsurance rates down to the county level, but that is very complicated for a large number of reasons and Lynn Lewitt will talk about that tomorrow during the phone call. She will give you some real data there.

Cindy DiBiasi: You can go down to the strongest one since you have been so disarmingly honest. (Laughs.)

Robin Weinick: Obviously, the data that come from the Census are very, very strong data. Very, very detailed data. Big, huge numbers of people contributing to all of the estimates, so they are probably the most solid data that we have. But I will tell you that our hospital discharge data are pretty amazing. Just the fact that the information that we have on preventable hospitalizations that are included in these products, come from what we call discharge abstract data. That means there is one piece of information, one line of data, for every single hospital discharge in that state in that year. It is an amazing data set. It is very, very strong. It is very reliable information.

Cindy DiBiasi: Charlene Gaster wants to know, “For small states with limited sources of data, how could your database book help us obtain data that illustrates health needs and services?

Robin Weinick: Right. Well, go in and take a look and we are going to give you every measure that we discussed here and a whole bunch we haven’t. As I said, there are 118 measures. We have small states represented; we have large states represented. So again, often the issue is that smaller states may have smaller levels of resources to go out and collect their own data. Maybe that means that they can make better use of these data that we are already making available to them.

Cindy DiBiasi: Vicki Wilson from Washington wants to know, “As we assess the capacity of our non-Medicaid safety net to respond to custom public programs, do you have suggestions about specific data elements in the book that would be useful?”

Robin Weinick: Well, I will take a shot at that but then I am also going to turn it over to Bob who may have some really good ideas. But we do have information, for example, on the presence or absence of community health centers, which are crucial providers. We have some information on disproportionate share hospital funds and some information on the presence of public hospitals and the extent of their market share that may be helpful.

Cindy DiBiasi: Bob, do you have any thoughts?

Robin Weinick: I am the one who has all the data, all the measures memorized, right?

Robert Seifert: I don’t have anything to add to that right now.

Cindy DiBiasi: The book has left him speechless. “I am a little concerned”, this is an email we have just received, “I am a little concerned about people moving to the locality where the safety net hospital is available. Is the locality defined by the healthcare clients or by the healthcare provider address?”

Robin Weinick: That is very dependent on which measure it is and I am going to have to refer you back to the appendix of the book. So for example, when we are using census data to talk about poverty rates, we are looking at the area where the individual people live. Same with uninsurance rates, as the area where the individual people live. I don’t happen to remember what we have used for the preventable hospitalization rates, so we are actually going to have to look that up and I would be happy to answer that question at a later time.

Cindy DiBiasi: Let’s talk a little bit about the physical book since people do not have it yet. We are talking about how many pages is the book?

Robin Weinick: Oh, I don’t know how many pages. Somebody over here has a copy. I think there are 370 pages in the first book. Let me look that up for you and I will give you a number. 378 pages in the first book and 695 in the state and county book. So we are talking about a lot of data here. Particularly in that second book with 695 pages. There is nothing in there but data. We don’t include pretty pictures in that one because we put them all in the first book so it is just a ton of data. Again, 1,818 counties; that is every single county in 30 states plus the District of Columbia.

Cindy DiBiasi: But the book is laid out in a very user-friendly way. Let’s talk a little bit about that.

Robin Weinick: Right. What we have tried to do there is we are presenting tons of information to people. The question is how do you use that information? How do you understand what is going on? So on the one hand it may be very helpful for you today to look up a piece of information about what is happening in Sacramento, California. Maybe it would also help for you to understand in a bigger picture, in some of the ways that I have shown you in some of the graphics here today, how those measures relate to one another or how much geographic variation there is in some of those measure. So we are hoping that is what those pretty pictures in that nice lay out in the front of book one can really do is help people understand what is going on, get a sense of the bigger picture.

Cindy DiBiasi: So context is provided. There is some analysis. It is not just numbers.

Robin Weinick: Absolutely. For those of you who are, Bob said he was a self-described data nerd. We have not only descriptive results, but also multi-variant results and for those of you who are not data nerds, what that means is we give you some analyses where we have taken into account all of these different factors simultaneously to look at what is associated with better outcomes and what is associated with worse outcomes.

Robert Seifert: Just to elaborate on what Robin is saying, I am a data nerd but spend a lot of time working with non-data nerds and just want to point out that this multi-variant analysis that is in the last chapter of the analytic section of the first book is excellent and very clear and very helpful. As I said before, laying out a road map and an idea for understanding what factors affect at least the outcome measures that we have for the safety net in the data set.

Cindy DiBiasi: Even though you are just surrounded by data, you just learned a lot.

Robert Seifert: I learned a lot and it is written in plain English and I feel like I am in an infomercial right now. (Laughter.) Go to your phones, no, considering the amount of data that is involved in the analysis that went into it, it is very clear and very helpful.

Robin Weinick: Even when the analysis gets complicated, we talk about all of it in plain English so actually those multi-variant results, which might sound like an awfully fancy word if you are not a data person, are presented in words only. No fancy statistics needed.

Cindy DiBiasi: OK. A question from Amy Blackwell. “Does the data book include the amount of uncompensated hospital care provided in each state and county?”

Robin Weinick: We do have a number of measures of uncompensated care and since the calculation of them is fairly complex, I am actually going to refer you back to the book or to the Web site to take a look.

Cindy DiBiasi: Any last thoughts or comments before we sign off and we were going to talk about the next couple of days. Anything you would just like to leave the audience with, Bob?

Robert Seifert: Get it and use it and give Robin your comments and really tell her what you would like to have in future updates and try to generate some demand for further work on that. I think it is well worthwhile.

Robin Weinick: Thank you. I think the biggest message I would like people to walk away with is the tremendous variation that exists in the safety net. If there is one message if you are going to hand somebody this book or say hey, there is this new product out there, the biggest message is probably how much things vary from one place to another and then need to look at these issues at a local level. Again, to reiterate what Bob said, the more information that you can provide to us on what you need, the better we can meet those needs.

Cindy DiBiasi: You can help author the next book. (Laughter.) Well, thank you both for joining us this afternoon. If you have any unanswered questions, please send an email to ulp@ahrq.gov. Depending on the number of questions, we will try to answer you directly. We also encourage you to send us any researchable questions that you are facing at the state or local levels for AHRQ’s consideration as the agency plans its future research priorities.

As we wind down, let me mention that a number of products from the audio conference will be available at a later date. Around the middle of November, an audio streamed archive of today’s call, a written transcript and all of the presenter’s slides, including those used in the question and answer session, will be posted to the ULP Web site at www.ahrq.gov/news/ulp/ulpdistn.htm. Text versions of the slides will also be available at the same web address. An audiotape of this event will be available for purchase in several week’s time. The cost for a set of three audiotapes from the series will be $10. To order a copy, call the AHRQ Publications Clearinghouse at 1-800-358-9295 and ask for AHRQ03-AV12A. It is entitled Monitoring the Healthcare Safety Net.

Also remember that information related to the AHRQ and HRSA initiative to monitor the healthcare safety net is available on the AHRQ Web site at www.ahrq.gov/data/safetynet. Specific questions regarding the data book can be emailed to safenet@ahrq.gov. The data books are available now. To request a copy of the data books, please send an email to the clearinghouse at ahrqpubs@ahrq.gov or call 1-800-358-9295.

Please mark your calendars for the next event in our safety net series, tomorrow, Wednesday, September 24th, we will focus on Safety Net Data Collections Strategies and Thursday, September 25th from 2-3:30 PM Eastern time, we will be addressing how you can use data to tell the safety net story.

Finally, before you log off, don’t forget to take a few minutes to fill out the brief evaluation form that will appear on your screen at the end of the broadcast. Easy-to-follow instructions are included and for those of you who have been listening by phone only and not using your computer, please stay on the line because the operator will ask you to respond to the same evaluation questions by using the keypad on your telephone. You may also email your comments to us at ulp@ahrq.gov.

Back to Top