**Transcript of Cyberseminar**

**VIReC Databases and Methods Seminar**

**Measuring Veterans Health Services Use in VA and Medicare**

**Presented by Kristin de Groot, MPH**

**January 6, 2014**

Moderator:	It looks like we are just at the top of the hour here. I would like to introduce today’s presenter. Kristin de Groot is a senior analyst at VIReC on the VA’s CMS data for research project. She has over ten years of experience working with Medicare data and CA research. Kristin, I would like to turn things over to you. 

Kristin de Groot:	Thank you, Heidi. Good afternoon or good morning. I hope all of you are staying warm. Quite cold where we are here in Chicago. So I am going to be talking today, as Heidi mentioned, about measuring veterans’ health services use in VA and in Medicare. So our topics for today, first we are going to talk about an overview of Medicare claims, then the Medicare claims data that are available for research, how to identify healthcare use using the Medicare claims, some common ways of measuring healthcare use in the Medicare claims, and some research examples using the data, and then how you can get access to the data and where you can go for more—for additional assistance. 

So first we want to ask about your experience knowledge of the Medicare data. So so far it looks like a majority of you have not used the data. And this goes—this is a pretty—this presentation is—this will be a good overview for you. So I am assuming since most of you have not used the data you probably do not have a lot of knowledge on it. And that looks about accurate. Great. So first an overview of Medicare data. It is important to recognize that many veterans who use VA healthcare also use healthcare outside the VA. This is important because researchers need to know about all healthcare use to draw accurate conclusions in their studies. And while it is difficult to get a complete picture of healthcare data on younger veterans, almost all veterans sixty-five and older are enrolled in Medicare. So when we use VA data in conjunction with Medicare data we get a pretty complete picture of healthcare use by older veterans. 

So before we get into discussing Medicare data I want to provide some background information. And please keep in mind this is a very simplified view of things but for the most part when a patient is enrolled in both VA and Medicare and receives care at the VA, the VA pays. Likewise when the same patient receives care outside the VA Medicare pays. The VA does not bill Medicare and for the most part community providers do not bill the VA. There are exceptions to this such as in emergencies or if VHA services are not available but this often requires pre-approval. We often hear about research results moving from bench to bedside but I want to explain how the Medicare data move from bedside to bench. 

So first the Medicare beneficiary receives care at a community or non-VA provider. In this presentation the term provider refers to any provider that bills Medicare. So it could be individuals like physicians or chiropractors or entities like laboratories, hospitals, home care agencies, suppliers, there is a long list of providers. So the providers submit bills or claims to the centers for Medicare and Medicare services, or CMS, for reimbursement. After the claims are processed and the provider has been paid CMS stores the information from the claim in databases and then they create analytic datasets for use by researchers. The analytic datasets that are made available to researchers have both strengths and limitations. Since each claim record is actually a bill submitted by a provider data directly related to billing is likely to be most accurate and complete. Examples of data that are likely to be accurate and complete are the social security number or in the VA you can get the data with scrambled social security numbers. 

And these are obviously important for CMS, or I am sorry, it is important for research because it allows the Medicare data to be linked with the VA data. You will also find charge and payment amounts, dates like discharge dates, admission dates, other dates of service, diagnosis codes, procedure codes and dates, and provider information like provider type for specialty and provider location. In contrast, data that is not needed for billing is not likely to be included in the claims. Or if it is included it is likely to be incomplete. For example, there is limited demographic information and no clinical information. The claims will not have any information about services that are not billed including services not covered by Medicare. In addition, claims are not regularly submitted for people enrolled in managed care plans or HMOs. Because of this you will often find that researchers exclude HMO enrollees from their analysis. 

Another limitation of Medicare claims is that they can often be more complicated to use than other data because the relationship between the claims and the healthcare services can be complicated. One example of this complicated relationship is that there can be multiple Medicare claims submitted for single inpatient stays. In this example two claims were submitted for the stay, maybe so the hospital could be reimbursed more quickly or maybe it just made things easier for accounting to end things at the end of the calendar or fiscal year. In some cases this might have been submitted as a single claim. There is a lot of variation on how services are billed. Another example of a complication is that sometimes two claims will be submitted for a single event. This often happens when an event occurs in a facility and both the facility and the physician bill separately. And we will go into more detail about this in a few minutes. 

In contrast to the previous slide many Medicare providers are paid using the prospective payment system where a single payment is made to cover all services. Depending on the type of service providers may not be required to itemize all services provided. It is important to be aware of what level of detail is required for reimbursement to know what information may or may not be included on the claim. There are many types of prospective payment systems and the type of system used is based on the provider type. So here are a few examples of prospective payment systems used in Medicare. Hospices are reimbursed based on the number of days of care they provide in each category of care. 

Categories are like routine home care, continuous home care, inpatient respite care, and general inpatient care. And it is based on the number of days of service regardless of what services are provided on those days. Another example: skilled nursing facilities are reimbursed based on both the number of days and the patient’s resource utilization group or RUG which is a case mix group that anticipates how much and what type of care the patient will need. And a third example, acute inpatient stays are not reimbursed on length of stay or number of days but on the diagnostic related group codes or DRG codes. And a simple definition of DRG codes are why was the person hospitalized. The DRG could be based on—well, it is based on patient—the patient’s diagnoses and procedures performed and whether or not there were any complications or comorbidities. 

For example, a DRG could be primarily based on a procedure like hip replacement or a symptom like chest pain or a diagnosis like stroke. So for example, a hospital that is being reimbursed based on DRGs must list diagnosis and procedure codes on the claim to support the DRG they are requesting reimbursement for. But on the other hand prescription drugs probably would not be found on the claim. So if you are interested in studying inpatient prescription drugs it is important to know that you are not going to find those in Medicare claims. So next we are going to talk about the data that are available for research, [coughs] excuse me. 

So as I mentioned already claims are billed submitted by providers. There are two types of bills that providers use to submit claims and the type of bill is determined by whether the provider is considered institutional or non-institutional. Some examples of institutional providers are hospitals, psych and rehab facilities, skilled nursing facilities, home health agencies, and hospices. These providers use the CMS 1450 which is also known as the UB-04 which was formerly known as the UB-92. Some examples of non-institutional providers are physicians, clinical laboratories, ambulances, and suppliers of durable medical equipment and prosthetics. These providers use the CMS 1500 form to submit claims. The reason the type of bill used is important is because it determines which dataset we will end up in, the claim will end up in. And we will get to that in just a moment. 

One other thing I wanted to point out is that I have heard researchers refer to the institutional providers as Medicare part A and the non-institutional as Medicare part B but this is not always the case. Services provided by institutional providers can be covered by either part A or part B depending on what the service is and—for example, if an x-ray was taken by a person who is an inpatient it would be covered by Medicare part A but if the person was outpatient it would be covered by part B even if it was in the same hospital. Home healthcare can also be covered by part A or part B. Services from non-institutional providers is almost always covered by Medicare part B. I did not want to say always but there could be an exception but I could not think of one. 

So here are the seven analytic datasets that all Medicare claims are found in. And you can see it is primarily based on provider type. Claims submitted by institutional providers are found in the five institutional files: inpatient, skilled nursing facility also referred to as SNF, home health agency, hospice, and outpatient, outpatient services within an institution. Claims submitted by non-institutional providers are found in the carrier file which was previously called physician supplier and the durable medical equipment or DME file. One other file I wanted to mention is the Medicare provider analysis and review file also known as MedPAR. This is an institutional stay level file or summary file created from the inpatient and SNF files. So now I will go into more detail about each of the claims files. [cough]

First is the inpatient file. It contains services provided both by short and long term hospitals like rehab and psychiatric hospitals. Because this is an institutional file it contains charges and payments to the facility. If you remember our example a few slides back we saw that sometimes a facility may submit multiple claims for a single stay. So when you use the inpatient file you must combine claims to make sure each stay is only being counted once. Next is the SNF file including services provided by skilled nursing facilities. It is important to note that not all stays in SNF are covered by Medicare. For example, Medicare will cover skilled nursing and rehab care for a short time following hospitalization but Medicare does not cover custodial care like when a person needs help with activities and daily living. Just like the inpatient file the SNF file includes charges and payments made to the facility and also like the inpatient file a stay in a SNF may involve multiple claims which would need to be combined. 

So at this point you are probably wishing you did not have to deal with this extra step of combining claims to study hospital or SNF stays. So if you do not want to have to—if you do not want to deal with that step you can use the MedPAR file. The MedPAR file is an alternative to combining the claims in inpatient and SNF. It is created from the inpatient and SNF claims but claims are combined or sometimes the term rolled up is used, rolled up to the stay level. So each record represents one stay or one admission. But the MedPAR file is not for everyone. It will not meet all researchers’ needs. It contains a lot of summary variables and it does not have the same level of detail as the inpatient and SNF files do. Also only the diagnosis and procedure codes from the last inpatient or SNF claim are included. So for example, if a person had a SNF stay of three months, say, January, February, and March and the facility decided to bill three separate claims you would only get the diagnosis and procedure codes from the March claim. 

[coughs] Going back the institutional files the third file is hospice. A Medicare beneficiary can elect to receive hospice services when a doctor has certified a life expectancy of six months or less. The majority of hospice care is provided at home but it is sometimes also provided in an inpatient setting. Next is home health agency which includes nursing, therapy, and home health aide services provided at home. And this is another example of a service that has a complicated relationship between the care and the claim. In this example sixty days of care are submitted on one claim. So if the person has only one claim that does not mean there is always just one service. The last institutional file is the outpatient file. Most of the services are provided by hospitals but it does include services from a few other institutional providers like dialysis facilities or rural health clinics. The most common types of services include laboratory, radiology, physical therapy, dialysis, emergency room services. Just like in the other institutional files the outpatient file includes facility charges. And in just a moment you will see why I keep emphasizing that these files only include facility charges. 

If you are interested in the other services, the physician services, you need to use the carrier file. The file was previously known as physician supplier which is a little more descriptive than its current name. The term carrier refers to Medicare contractors that process claims on behalf of CMS. So the claims processed by the carriers end up in the carrier file. We have a little bit of everything in here. As you can guess from the name, from the original name, [cough] it includes claims from physicians which include a wide range of services that can be provided in both outpatient and inpatient settings. On the outpatient side you will find office visits and procedures. On the inpatient side you will find consults and services provided in hospitals or nursing homes. You will also find physician services provided in emergency rooms. In addition, claims submitted by ambulance providers and clinical labs are also found in the carrier file. 

The last claims file is durable medical equipment or DME. This file contains equipment and other products covered by Medicare. Some examples listed here are equipment such as wheelchairs and hospital beds which can either be rental or purchased, prosthetics and orthotics, oxygen equipment and supplies, diabetic testing supplies, and some drugs. But it is limited to drugs provided in an outpatient setting administered by a provider. And mostly these are injectable drugs including some chemotherapy drugs. And while we are on the topic of drug coverage I want to talk a little bit about Medicare part D. [cough] 

Everything we have talked to—we have talked about up to this point is covered by either Medicare part A or part B. So we are going to switch gears a little bit. Medicare part D started in two thousand six and covers prescription drugs. While almost all VHA enrollees over sixty-five are enrolled in Medicare’s part A and part B, only about a third are enrolled in part D. Also the part D program is run different than Medicare part A and part B. Under part D beneficiaries enroll in a part D plan through an insurance company. When the beneficiary fills a prescription the claim is paid by the insurance company, not by CMS. CMS never sees the actual claim. But CMS does require the insurance company to submit data on all of the prescriptions that have been filled. 

CMS makes this data available to researchers in a file called prescription drug event file. CMS also has data on the drug itself, the dispensing pharmacy, the prescriber, and the insurance plan that paid for the drug. CMS has also created a subset of the prescription drug event file called the slim file which is the data elements most commonly used by researchers. If you want to know more about Medicare part D next month’s Database and Methods cyber seminar is about pharmacy data and will include more information about part D. 

So now that we have seen the files that are available which files should you use for your research? As we have seen inpatient and skilled nursing care are provided by institutional providers which is the hospital or the SNF and the claims for the facility charges can be found in the inpatient and SNF or MedPAR file. These claims will include services provided by the facility and the staff. When care in an inpatient or SNF facility is provided by physicians not employed by the hospital or by the nursing facility the claims are submitted separately and end up in the carrier file. A question that often comes up: should I use the MedPAR or inpatient and SNF files? And there is really no right answer. It depends on what you are studying. The MedPAR file is advantageous when looking at the big picture like number of stays, length of stay, total cost. On the other hand, if you need more detail such revenue centers which are like hospital departmental charges which are listed on the claim you will want to use the inpatient and SNF files. [cough] In addition if you want all diagnosis and procedure codes you will want to use the inpatient and SNF files since MedPAR contains only the diagnosis and procedure codes found on the last claim of the stay. 

Some researchers find it beneficial to use both MedPAR and inpatient. Use the MedPAR for studying number of stays and those types of things and use the inpatient file when additional details are needed. In addition, if you want to know about consults or—that occur during the stay or any procedures that may have been done by a non-staff physician you also should use the carrier file. As we have seen outpatient care can be provided by both institutional providers like hospitals and non-institutional providers like physicians. The claim submitted by the hospital will end up in the outpatient file and the claim submitted by the physician will end up in the carrier file. In most cases you will want to use both the outpatient and carrier files. One of the most common mistakes I see is that researchers want to study outpatient care and they request only the outpatient file. There are some situations where you might need only one or the other like if you want to study physician visits you would probably be OK with just the carrier file. But in most situations you probably want to use both. 

And keep in mind that for some events you might find a claim in each file like with emergency room visits. Depending on the type of service you are studying you also may want to consider adding home health agency file if the services you are interested in might be provided at home like certain types of therapy. Our next topic is measures using Medicare data and providing some research examples. But first we are going to pause for a minute to get some input from you. So the question is what do you want to measure using Medicare data? And I think—

Moderator:	Yes, I am pulling it up right now. For the audience, on your screen here you should have some annotation tools. At the top there is a capital P, just click on that and bring that down to the screen and you can type right on the screen. We will not see what you have typed until you hit the enter button but that is how you do it. Kristin, you may want to say what the question is again. 

Kristin de Groot:	Yes the question is what do you want to measure using Medicare data? Cancer treatment, demographics, utilization of services following discharge from residential treatment, ESRD events, number of admissions, length of stay, number of visits to emergency department, dual care, laboratory, utilization and cost, admissions, hospice, I am hoping the next section will be able to provide you some guidance on how you can measure some of these things. Some of them are a little more straightforward than others. Types of services, types of diseases and conditions being treated, location of treatments, I want to wait just a few more seconds. 

Moderator:	I am sorry I am moving them around. I am just trying to keep it readable on the screen. I know it is a little confusing as I am moving them around. [crosstalk] [laughter]

Kristin de Groot:	That is OK. I think a few of these I had mentioned earlier some things are not included in the claims like glucose levels will not be included in the claims because it is considered clinical information. DNR orders will not be included in the claims but a lot of these other things will be. So let us move on to some measurement issues. So there are many types of analysis that can be done with Medicare data. But we are going to focus on four common ways of measuring—using the Medicare data: procedures, costs, inpatient stays, and outpatient visits. And for each of these measurement methods I am going to show an example of published research using VA and Medicare data. 

The first one we are going to talk about are procedures. There are two types of procedure codes in the Medicare data: ICD-9 procedure or surgery codes which are primarily used in an inpatient setting and found in the MedPAR and inpatient file. The other type of procedure code is the Healthcare Common Procedure Coding System also known as HCPCS. HCPC codes are a combination of CPT procedure codes and codes developed by CMS for Medicare covered services and products that are not already included in CPT. And you know when you are dealing with these CMS developed codes because they all begin with a character while the CPT codes are strictly numeric. These codes are used in outpatient, home health, carrier, and DME files. 

An example of a study using procedures is from Dr. Walter and colleagues published in two thousand nine. They wanted to determine whether colorectal cancer screening was targeted to younger and healthy patients and was avoided in older patients and those with severe comorbidities and limited life expectancy. Their cohort was VHA outpatient users who were seventy or older and were due for a screening. They excluded those who were enrolled in Medicare managed care. Remember that Medicare claims are not routinely submitted for those enrolled in managed care so their data would be incomplete. Their final cohort was about twenty-seven thousand. They used diagnosis codes found in the VA and Medicare inpatient and outpatient data to calculate comorbidity scores. Then they followed the patients for two years to determine whether they had received colorectal cancer screening. They searched the CPT codes in the VA data and the HCPC codes in the Medicare and outpatient files. 

Here are a few results from their study: overall forty-six percent of patients received colorectal cancer screening and a third of these were done in Medicare. They did find that screening incidence decreased with age and with comorbidity score. But the study emphasized that more of the younger health patients should be screened and fewer of the patients with limited life expectancy should be screened. Another common thing that Medicare claims are used for studying is cost. There are two main types of cost data in the claims: charges and payments. Charges are what the provider submits to Medicare but often what they are actually reimbursed is quite different than what they are charged. More often researchers study payments made to providers. This includes payments from Medicare, from beneficiaries in the form of deductibles and copays, and from primary payors which are insurance companies that pay before Medicare. And these are often employer based health plans. 

Users should keep in mind that claims do not include payments that are made after CMS has paid like payments by Medigap or other insurance plans. An example of a study using cost is from Dr. Hubbard Winkler and colleagues published in two thousand ten. They wanted to compare purchase prices of assisted technology devices in Medicare and VA. Their cohort consisted of twelve thousand veterans sixty-five or older who were hospitalized in the VA for stroke. They followed the patients for two years after their stroke. There were six products they wanted to compare purchase price between VA and Medicare. They used HCPC codes to identify these products in the VA’s National Prosthetic Patient Database and Medicare’s Durable Medical Equipment file. 

This table shows the six devices they studied and the corresponding HCPC codes. We can tell that these are the CMS developed HCPC codes because they all begin with a character. As you can see VA provided the devices at about the same or lower cost than Medicare in all cases. A third thing that Medicare claims are used for looking at is inpatient stays. And here I have listed some common measures that are used when studying inpatient stays and data elements that can be used when studying them and I am going to highlight a few of them for you. 

The Medicare data does not contain exact times of when things occurred but it does contain admission and discharge dates which can be used in calculating length of stay or time between stays. The facility number found in the data can tell you the type of facility and its location. The facility number can be linked with the publically available provider of services dataset to give you information about the facility like its size and the types of services it provides. To determine the type of care provided during an inpatient stay you can look at procedure codes, revenue center codes which are hospital department codes, and they can tell you which departments were involved in the patient’s care. And sometimes the DRG code can give you an idea of what type of care is provided. The DRG along with the diagnosis codes will also tell you about the patient’s condition. And finally the inpatient data can tell you whether the patient was discharged to home or another facility or died during the stay. 

One thing you will want to keep in mind when combining VA and Medicare inpatient stays is that there are differences in VA facilities and Medicare facilities. Sometimes a single VA facility can provide a wide range of care, for example, both acute care and rehab in a single stay. But outside the VA in Medicare this might be split between two facilities and two stays. So it would appear that there is more admissions in the Medicare system. So if you are looking at inpatient stays it is a good idea to know what took place during the stay to be sure you are counting the same thing in both systems. An example of a study using stays is from Dr. Weeks and colleagues published in two thousand nine. They wanted to determine whether rural veterans have a higher rate of readmission than urban veterans. They looked at admissions in VA hospitals and admissions covered by Medicare fee-for-service, meaning the hospitalizations covered by HMOs were excluded. 

They limited their study to admissions resulting in a discharge to home, to veterans sixty-five or older, and those living in rural or urban areas and the intermediate areas were excluded. This resulted in two point eight million veterans. They looked at all inpatient care in the VA patient treatment file which is sometimes known as the inpatient medical SAS dataset and the Medicare MedPAR file. In this example the MedPAR file is preferable since they are primarily interested in admission and discharge dates and did not need to know the detail of what occurred during the stay. They identified readmissions occurring within thirty days of being discharged to home. This analysis looked at readmissions both within either VA or Medicare systems and also between VA and Medicare systems. Overall the readmission rate for both urban and rural veterans was just shy of eighteen percent. For VA to VA readmissions the rate was higher among the urban veterans. But for the other three scenarios the rate is higher among the rural veterans. 

One thing I want to point out here is that these results would look very different if only VA hospitalizations were used, only this line. We would not know anything about the readmissions that occurred in the non-VA hospitals and we also would have miscategorized some of these readmissions as index admissions because we would not have known about this hospitalization. Lastly we will discuss outpatient visits. Here I have listed some common measures that are used when studying outpatient visits and data elements that can be used when studying them. The Medicare data contained from and through—claim from and through dates which are usually the dates of service. When a claim spans more than a single day you can use other dates found in the claim like expense dates or revenue center dates to determine exactly when events occurred. The data also contain provider numbers like the unique physician identification number or UPIN that was used through two thousand six, and after two thousand six the National Provider Index or NPI number for individual providers. 

And this can tell you the provider specialty and location. In addition the non-institutional claim file, the carrier, contains place of service so you can determine whether it took place in a physician’s office [cough] or in another place. The institutional claim file, the outpatient file, contains the facility number to help you determine where the service took place. To determine the type of care provided during a visit you can look at HCPC procedure codes, the BETOS code which is a way of grouping HCPC into useful categories, a type of service code, and just like when you are looking at inpatient stays you can look at the revenue center codes to tell which departments of the hospital were involved. And lastly you can look at diagnosis codes to inform you about the patient’s condition. 

In the title of this slide I use the term outpatient visit but there are other terms we could have used: events, encounters, whatever terminology you use it is important to define what you mean. In the VA often several appointments are scheduled on a single day like seeing a primary care physician, a specialist, and a therapist. If you are familiar with the MedSAS data you will know that this could be counted as one visit with three events. Depending how you are defining a visit in your study you might want to count each of the three events as a visit. [cough] It could be one visit or three visits depending on how you are counting things. On the Medicare side regardless of whether three services are on the same day or on different days they will be submitted at three different claims which would probably be counted as three visits. 

Sometimes you will also see them measure days of care received. But when combining VA and Medicare use like in this example days of care really is like combining apples and oranges. So regardless of the terminology you use it is important to determine that you are counting the same thing in both systems. An example using—studying outpatient visits is from Dr. Liu and colleagues published in two thousand and eleven. They wanted to examine longitudinal changes in Medicare eligible veterans’ reliance on VA outpatient care. Their cohort was made up of fifteen thousand Medicare eligible veterans who used VA primary care and were not enrolled in Medicare managed care. [cough] Similar to the study by Dr. Walter this study used diagnosis codes in VA and Medicare to calculate comorbidity scores. They looked at VA and Medicare outpatient utilization from FY01 to 04 and developed an algorithm to classify each visit into one of four categories. The categories were primary care, specialty care, mental health care, or other care. 

And the algorithm used provider specialty and procedure codes to determine which categorize the visit would go into. Once they determined the number of visits in each category they calculated the proportion of these visits occurring in the VA. The research found that the number of primary and specialty care visits in the VA decreased. So primary care visits decreased, specialty care visits decreased, whereas both types of visits increased under Medicare. Where so in total the reliance, VA reliance decreased for both primary and specialty care. So lastly I am going to talk about how you can get access to the data and where to go for more assistance. 

VIReC’s VA CMS data for research projects is the data steward for all CMS data including Medicare data used for VA research. VIReC warehouses CMS data which we call our VA/CMS data repository and it includes both veterans and non-veterans. VA researchers with R&D and IRB approved projects can submit a data request to us. Due a policy change a few years ago VA researchers may not obtain CMS data directly from CMS or ResDAC. If you need assistance learning about what CMS data are available from VIReC our website is shown here. Our website contains a description of all the CMS data that are available including documentation for the data such as data dictionaries, links to data dictionaries, SAS Proc contents, and variable frequencies. We have a description of the various cohorts that are available, links to download public use files such as providers of service file that I mentioned earlier, and you will also fine here our request process and forms. 

If you need additional help you can contact the VIReC help desk which will forward the questions to the VA/CMS data for research project team. And our help desk email is shown here. Also you can use the HSRData listserv which is an email based discussion among over eight hundred data stewards—data managers and users within the VA. All of the messages are archived on the internet and you can sign up for the listserv on the VIReC intranet. If you want help specifically about the CMS data there are two resources. The first is ResDAC, they are a CMS contractor based at the University of Minnesota. They provide free assistance and training to researchers using CMS data. You can submit questions to their help desk. They have a web-based knowledge base. They have webinars just like our cyber seminars, and they also host in-person workshops. 

The second resource is the Chronic Conditions Data Warehouse which is run by Buccaneer, another CMS contractor. And this data warehouse is actually the source of the data that VIReC receives that we then distribute to researchers. So all of the documentation on their website applies to the data that you would be receiving from us. They have data dictionaries, summary tables, and really helpful user guides and technical guides and their website is shown here. And just one last thing to mention, there is a cyber-seminar next month, February third, about pharmacy data and Medicare part D data that I had mentioned earlier. So we hope to see you all there next month. And now we will open it up for questions. 

Moderator:	We actually had one question but then you answered it a little bit later so we do not have any pending questions right now. But for the audience: if you do have a question please use the Q&A screen at the lower right hand corner and you can submit your questions right in there. Question: who or where to contact for the data access?

Kristin de Groot:	All the information about accessing CMS data within the VA is through VIReC’s VA/CMS data for research project and the link is shown here. 

Moderator:	And that is a live link on there so if you need it go ahead and click on it now and save that for a little bit later. Next question: do VA researchers have to pay for access to Medicare data?

Kristin de Groot:	The vast majority of the time no you do not have to pay. If you need data that we do not have we will submit a special request to CMS on your behalf and then you would have to pay. But that is quite rare. But you can contact us to see—or actually just I would first go on the website to see if the data you need are available. Or if you are not sure you can send an email to the VIReC help desk. 

Moderator:	Great, thank you. The next question: when does Medicare shift from ICD-9 to ICD-10?

Kristin de Groot:	I believe it is October first was it twenty thirteen or twenty fourteen? I cannot remember off the top of my head. 

Moderator:	Thank you. The next question here: how adequate are Medicaid data for measuring receipt of evidence-based practices or guidelines?

Kristin de Groot:	Well, Medicare—the Medicare data is pretty accurate for looking at a particular procedure or particular visit. You would have to know outside of the data what is considered—what is the best practice. Does that make sense? I mean, you would have to know this is what we are looking for and then the data will be pretty accurate in terms of whether or not something occurred. 

Moderator:	Thank you. We did get a comment in here. ICD-10 CM starts October first, twenty fourteen. 

Kristin de Groot:	Thank you. 

Moderator:	Thank you. The next question here: how confident are you with race and ethnicity data from CMS?

Kristin de Groot:	There has actually been a few papers studies about the quality of race and ethnicity data in Medicare. If you are looking at—there have been some suggestions that say you should just categorize as black/non-black because the groups white, Hispanic, and Asian are less reliable. But let me see, I am trying to think of the best way to—I do not have the information off the top of my head but I know there have been studies about, non-VA studies, about the quality of race data in Medicare. Basically if someone is categorized as black, Hispanic, Asian, or Native American you can be pretty confident it is accurate. However, there are a lot of people classified as white who are actually other races or ethnicities. 

Moderator:	Great, thank you. The next question here: do we have data on veterans using non-VA providers?

Kristin de Groot:	If—well, all Medicare—all of the Medicare data is veterans using non-VA providers. Assuming that Medicare paid for the service we will have data on it. We also have data on services covered by Medicaid but that would be for another presentation. But if it is covered by private health insurance we do not have that.

Moderator:	Great, thank you. And that is all the questions that we have received in so far. If anyone else does have a question get that into us quickly or we are going to start wrapping things up here. I am not seeing anything else coming in. Kristin, do you have any last minute comments you wanted to make while we are stalling for a little time to see if we get any more questions? 

Kristin de Groot:	No, the only thing on our website, the VA/CMS data for research website, we have information about a lot of the other data we have available in addition to Medicare. I mean, Medicare is by far the largest portion of the data we have. But we also have Medicaid as I mentioned. We have some assessment data for people who are in nursing homes or are receiving home healthcare. We have some survey data, Medicare current beneficiary survey. And we have data from about patients receiving end stage or patients who have end stage renal disease, data from United States Renal Data Systems. They are all through VIReC. 

Moderator:	Great, thank you. And we have not received any other questions in here and since I am not seeing anything else come in I am going to wrap things up a little bit early today. Kristin, thank you so much for presenting in today’s session. I just realized I need to grab the feedback link. We really appreciate the time you put into this and I know we really appreciate you coming in on an incredibly cold day out in Chicago. 

Kristin de Groot:	Well, let me say if it were not for this presentation I would be at home right now. [laughter]

Moderator:	I honestly thought this morning well, we may not be having the session today because I do not know if I would be coming in today so we really do appreciate you doing that for us. For the audience, everyone thank you very much for joining us today’s session. I am going to stick this back up really quickly. Our next session is February third and Kevin Stroop will be presenting on pharmacy data and Medicare part D. We will be getting registration information out to you on that as soon as possible. As I close the meeting out today I will be putting up a feedback form. If you guys could hang out for just a minute or two and fill that out we really do read through all of your comments and we really do try to implement as much as we can. Thank you everyone for joining us for today’s session and we hope to see you at a future HSRD cyber-seminar. 

[End of audio]

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