**Transcript of Cyberseminar**

**VIReC Database and Methods Seminar**

**Measuring Outpatient Pharmacy Use in the VA Using VA Pharmacy Data**

**Presenter: Denise Hynes, Ph.D.**

**April 1, 2013**

**Measuring Outpatient Pharmacy Use in the VA Using VA Pharmacy Data**

**April 1, 2013**

*This is an unedited transcript of this session. As such, it may contain omissions or errors due to sound quality or misinterpretation. For clarification or verification of any points in the transcript, please refer to the audio version posted at**http://www.hsrd.research.va.gov/cyberseminars/catalog-archive.cfm**or contact**virec@va.gov*

Moderator: Welcome to VIReC’s database and methods cyber seminar entitled measuring outpatient pharmacy use in the VA using VA pharmacy data. Thank you to CIDER for providing technical and promotional support for this series. Today’s speaker is Denise Hynes, Director of VIReC and research career scientist at the HSR&D Center of Excellence here at Hines VA hospital. Denise Hynes holds a joint position at the University of Illinois Chicago as Professor of Public Health and as Director of the Biomedical Informatics Core of the University’s Center for Clinical and Translational Sciences. Questions will be monitored during the talk in the Q&A portion of GoToWebinar as will be presented to Denise Hynes at the end of the session. A brief evaluation questionnaire will pop up when you close GoToWebinar, we would appreciate if you would take a few moments to complete it. I am pleased to welcome today’s speaker Denise Hynes.

Denise Hynes: Thank you Erica and thank you Molly, I am going to, it should be able to show my screen and I will switch over here, please let us know if you are having any trouble hearing in our message box, we can monitor that as well. And let us know if we are going too fast or too slow today. Today’s topic will be measuring outpatient pharmacy use in the VA with particular focus on using some of the various VA Pharmacy data that are available in the VA. Hopefully you can see my slides, if you cannot let us know and we will try to adjust. 

Moderator: You are coming through just fine.

Denise Hynes: Thank you, so our first is an audience poll, this will give us a sense of your experience with using pharmacy data in the VA. So our first question shown on the screen here is have you ever-used VA pharmacy data. This is a broad question, any pharmacy data local, national, corporate data warehouse, DSS, any kind of data, have you ever used it in health services research, in your research? And then the second question...

Moderator: Excuse me Denise Hynes.

Denise Hynes: Go ahead Molly.

Moderator: Sorry to interrupt, we had an eighty percent response rate so I will let you talk to that.

Denise Hynes: The second question is going to be how you would rate your overall knowledge of VA pharmacy data. This will give us a sense of not only your experience using it but how comfortable you are using it on a scale from one having never used it to have used it very frequently and you are very familiar at a five.

Great, while we are waiting for the remainder of our responses to come in we will just go over the answers for number one real quick. It looks like we had sixty four percent respond yes, they have accessed the data before and thirty six percent responded no. and we have had eighty five percent of our audience answer this question at this time so I am going to go ahead and close the poll and share the results. Denise you should be able to see those now.

Thank you, so we have in the liker scale how would you rate your overall knowledge of VA pharmacy data, thirty percent have never used any VA pharmacy data, twenty two percent ranked themselves at a two, twenty two percent ranked themselves at a three, fifteen percent at a four and twelve percent are very familiar. So it looks like we have some folks who are very new at using VA pharmacy data. That bodes well for the kind of information we have put together today, we have an excess of examples that will be good if you will homework for you to do. We wanted to include it in our slides so that you would have some specific research examples. I am going to talk through as many as I can do today but probably the major ones that we will go into detail will be two studies. Here is our session objective for today, how has outpatient pharmacy use been measured in VA research studies. We will also provide an overview of VA pharmacy data bases, I will talk a bit about finding specific information in the VA pharmacy data bases based on some of the help desk questions and frequently asked questions in previous lectures we have done oh this topic and give you some examples. And then I will go into detail on some examples of VA studies that have been published that have used VA pharmacy data bases and that is where I will probably focus on just two examples although we have given you about five and then end today’s session with where to go for more help. 

So lets start with this first topic, how has outpatient pharmacy use been measured in VA studies and what I am going to do is just give you an introduction to the published research of which we will highlight in greater detail at the end of today’s lecture and you can look offline as well. I also want to point out today that we will try to do some questions at each of the points along the way; I will turn to Erica for highlighting any questions that have come in and some questions that we have prepared in advance in case you cannot think of any questions. So if you put your questions in as we go we will try to attend to some of those rather than waiting for all the questions at the end today.

 So lets dive in, so the first example is focused on an article actually that came out of a group that I am a part of, looking at trends in anemia management in lung and colon cancer patients and this particular article published in 2012, the citation is shown here, looks specially at trends in medication use. In particularly use of erythropoietin stimulating agents which is a parenteral medication given either intravenously or subcutaneously and looked at the use of this medication over time. Another example is listed here by Dr. Pugh and colleagues, this also was published in 2012 in the Journal of the American Geriatrics Society and they look specifically at medication exposure and outcomes. They looked specifically at the association of a specific medication with potential adverse events. So again a time dimension that can be possible when examining pharmaceuticals and use patterns. Another example which we will highlight in detail today is by Hoyt and Colleagues, I hope I am pronouncing that name correctly and if not maybe that would be something that someone could type it for us with some phonetics for us because I will be referring to this paper a little bit more later. 

Published in 2010 looking at chronic obstructive pulmonary disease patients, they looked at medication adherence and they specifically looked at adherence using information from VA’s medications refill for pharmaceuticals, the patterns there. Another medication use example is from Gelled and colleagues, they looked at specific drug class use in nursing home patients what they term as community living centers, and they looked at antipsychotic use in this population. Sometimes this population is a little more challenging to identify prescriptions and medication use because they are in nursing homes and we will talk about this particular example in detail later. And one more example here by colleagues in 2012 published in arthritis care and research Ng and colleagues, they looked at a specific drug type in order to improve case identification of a cohort of rheumatoid arthritis patients. So they actually supplemented drug data with information that they gathered from other sources to identify disease classes and evaluated whether the additional information could better identify cases with rheumatoid arthritis. 

So drug information can be used in multiple different ways, these are just some examples that we highlight here from the last couple of years of papers that have been published. Now let me just continue and we will go into some of the specific VA pharmacy databases that have been used in VA research, just to give you an overview of the types of databases that are available. And we will try to talk in overview format some of the example of variables that are often used and we will get into some more details when we get into the examples. So first of all some local databases, and for those of you who might not have been on previous lecture series for the database and methods done in our series when I talk about local databases, I am usually referring to databases that are defining and describing your local VA medical center or local community based outpatient centers. So affiliates within a local medical center, so we think of Vista or CPRS, the electronic health record as a local database. We also think of the regional or the VISN warehouses as local, those data sources do have information on particular packages with regard to pharmacy management, orders for medications, the VISN warehouses are a regional example of a local database that might have some information from Vista or CPRS regarding medication administration. National data sources would be those sources that might actually rely on some of the information very extensively from the local sources whether it is the VISN warehouses or the Vista or CPRS packages but these are available at a national level from a centralized source that brings together information from all local databases or all regional sources. So for example, the pharmacy benefit management service includes and maintains data that comes from all of the local sources. DSS, Decision Support System has created a pharmacy dataset garnered from all the local DSS data sources. The corporate data warehouse includes information that comes from the Vista packages and from DSS and includes information in there about pharmacy as well.

Other key pharmacy data sources include some reference material that you should keep in mind. DSS product table has information about the types of pharmaceutical products that is included in DSS. Similarly, the national drug file includes information about the types of medications and medication supplies that are included in the pharmacy data sets. Let us just pause a minute before I get into some more of the detail about the types of information that are available in these data sources and pose another question to our audience. Which national sources of VA pharmacy data for those of you who have used them in the past, have you used? We list here the DSS; national data extract pharmacy data, the pharmacy benefits management pharmacy data, both or neither.

Moderator: Thank you we have had about third thirds of our audience vote and the answers are still streaming in so we will give people just a few more seconds to get their responses in.

Denise Hynes: Thanks Molly, in the future, we will add to this poll some of our other data sources go ahead Molly.

Moderator: Not a problem I am just going to share the results with you real quick, we had a bout and eighty percent response rate. So about fifteen percent have used the DSS NDE pharmacy data, eighteen percent indicate they have used the PBM pharmacy date, about seventeen percent indicated both and fifty percent that indicated that they are not familiar or have any experience using either of those.

Denise Hynes: Thanks Molly, now can you see my slides okay, or do I need to switch those back?

Moderator: Just a second, no you are okay, I just need to...my apologies let me take, okay now you should be able to share your screen.

Denise Hynes: Thank you, there we go, so let me talk a little bit about some of these data sources in a little bit more detail. Keep in mind this is an overview you will not be an expert in using VA pharmacy data sources by the time we finish today’s lecture. But we do hope that you will be more familiar with range of data sources and the type of information that these data sources can offer to your research project. The first VA Decision Support System, NDE’s National Data Extract, these are in SAS format and these are still available although they are now being produced by the corporate data warehouse or will be soon. The data structures are the same, these became available in 2003, and the data are available from fiscal year 2002 until currently. They have improved over time so the anecdotal that more recent data tend to be if you will more reliable, we do not have anything concrete about fiscal year 2002 but since it was the first year the data are available one would be cautious about that particular year. The primary source of data is Vista that is the Pharmacy package that feeds the DSS system in Vista. All inpatient and outpatient prescriptions are dispensed by a VAMC or the VA consolidated mail out pharmacy, I did not do that very well, the CMOPS is how we are better known. So the prescriptions that are included in both the facility and the CMOPS and these data for DSS NDE are housed at the Austin Information Technology Center and they are directly accessible currently in SAS format. The pharmacy benefits management database has been available since 2000, these data are from fiscal year 1999 to present, and these data are sourced also from Vista. They contain both inpatient and outpatient prescriptions. 

One might ask how PBM and DSS are different. A couple aspects to highlight here, the PBM database versus DSS database is highlighted here, information on cost is available in both datasets. PBM provides the drug supply cost, DSS provides information on three dimensions, and not only the supply cost but also the dispensing cost and then what is called the actual cost. Access to the databases are different, to access the PBM database researcher needs to request and extract from the pharmacy benefits management service whereas with the DSS SAS data sets permission can be granted to directly access the DSS SAS datasets. Date availability comparison is highlighted here and one important difference in terms of the substance of the data, the PBM database includes information about indications for use and what is called the SIG that provides instructions so it includes the schedule, the dosing and the dispensed units, that level of information is not available in the DSS database. Another key difference in PBM and other pharmacy dat\a is that the PBM updates the VA product variable for new national drug codes and the national drug code is the best source used for purchases as opposed to individual prescriptions. Since the pharmacy benefits management group assigned the VA product, name it therefore follows that the PBM data are the most complete and the most up to date for this variable. I will highlight some of the variables a little bit later but you should know that individual stations may also identify a prescription by station name and when those data get to the pharmacy benefits management service, if the VA product is missing then PBM assigns one. So using VA product is the best way to insure complete prescription capture and this is part of the reason that there is also a delay in the PBM data for this sort of cleaning if you will. 

Lets see I wanted to jut highlight some of the information again so that you can just see the kind of information that is available, the day supply, the drug description he quantity, the NDC, the medication class are both available in DSS and PBM with some caveats that I mentioned. Now some other DSS and PBM pharmacy data that you should be aware of the DSS product table I mentioned earlier some key variables are listed here and this provides a bit more detail about the kind of information that is listed in the DSS dataset. It also has information about the specific feeder key so that you know exactly how many characters are there for the VA product file. And then the last 12 characters are actually the NDC number and this detail is provided on the DSS website. And then the national drug file lists some critical variables that you need to keep track of. Other pharmacy data in the Corporate Date Warehouse are listed here, Corporate Date Warehouse is a new data source, newish for most researchers and we know that there are lots of discussions and basically becoming familiar with these data. I just want to highlight today two key product tables that are important if you are going to utilize data from the Corporate Date Warehouse. Currently there is the pharmacy BCMA data which is the barcode administration coding system and that indicates information about the dispensed drug, the medication log, medication variance and also missing dose information. And then there is also a product table related to pharmacy outpatients and that includes outpatient prescriptions, outpatient bills, the outpatient SIG information and also the medication instructions. So let me pause here before we move on to our next section Erica and see if there are any questions that we wanted to insert at this point.

Moderator: There are a couple of questions, as a non-VA employee, how can I get access to one of the pharmacy data sources mentioned?

Denise Hynes: So a non-VA employee would have a couple different options, three I believe, one is to collaborate with someone in the VA, you still might need to become either, you have to establish some sort of standing in the VA either as a without compensation employee or in some sort of a paid way as an interpersonal agreement. But you need to have some sort of standing in the VA. We also recommend collaboration because collaboration will also afford you access to colleagues who would have extensive knowledge using these databases. It is not always to straight forward to understand the best application of these databases. There is also an option I suppose if you did not want to go with those first two routes and can make a freedom of information act request, I cannot really speak to how much of this information in the pharmacy databases are actually afforded through the FOIA approach, I would definitely recommend the first two approaches.

Moderator: and a second, how do we access the VA formulary list, I found the list from the link on the Pharmacy Benefits Management Service website, however it does not have the medications that I am studying?

Denise Hynes: That is a good question, I am not sure I will have a complete answer to that. Probably if you, this is going to be a guess and maybe this is something that we can fill in on our helpdesk. The VA formulary information is available as you have indicated and if there are aspecific medication that you cannot see, we probably need to go directly to PBM to find out if these specific medications are available currently in the formulary. Keep in mind that the formulary is changing; it may not be the same from year to year so if there is this particular medication that you are interested in the availability of it through the VA’s formulary could have changed from year to year. The other aspect that we can check on is how often it is updated, I am not sure if it is updated annually or at some other interval. So thank you for that question and we will try to get some more detail about it for you, thanks Denise. Okay we will go ahead and move on to a topic on finding information in the VA pharmacy data sets. Our slides are just moving a little bit slowly today, there we go, and hopefully I did not skip over too many. So let us try to look at some of the questions that we often get, where can I find cost variables and we highlighted this a little bit but I wanted to highlight some of the specific kinds of a little bit more down in the weeds where you can at least have this information available for reference offline. There are two sources that really provide good information and have been used extensively over the years because these data have been available and have been used in research. So most of my responses to the questions if you will that I will highlight today are from DSS and PBM. Cost of the drug from the supplier is definitely available in the PBM database. The DSS data can provide information on dispensing costs; specific variable name is listed there. This provides direct pharmacist labor for dispensing the prescription and the mailing cost. It also provides detail about the supply cost which is the DSS product drug cost and the cost of supplies used in preparing the prescription, for example bottles and labeling. And then it also provides the actual cost and this is the product cost, the cost of the supples such as the bottles, but also the indirect costs and any overhead that might be attributable to having this pharmacy service at the VA.

Why is the NDC for the same prescription different from the PBM record compared to the DSS record? You have to keep in mind a little bit these are although the source of the information is comparable; there are some updates that are a little bit different and a little bit different in terms of time. First of all the NDC’s or the National Drug Codes are obtained from different sources, so although the medication information and the prescriptions information might be from the same Vista source, the actual NDC information may come from different places. So the differences can result if the local drug file has not been updated to reflect supply that was stocked when the medication was dispensed. There could also be different NDC’s that refer to the same drug or medication or the dosage and the strength but might indicate a different manufacturer and or package size. So you have to keep in mind what the NDC codes, I also called out a difference that PBM alerted us to about the updating. So depending on which data source you use the most up to date information with regard to NDC’s will be the PBM record, the DSS record might have been compiled a little bit before the PBM record might have been fully updated. So keep in mind it may not hurt to use both sources depending upon what the nature of your study is. 

So let us go into some of the examples and maybe what I will do Erica is pause after the first one and see how we are doing on time. So these are just some more examples of the types of questions that are often addressed with pharmacy data, we highlighted some of these with some of the examples at the front of our lecture. Cohort identification, can pharmacy data be used to identify specific groups of patients and we will see in an example that yes they can be, it just depends on if you are defining your cohort. That way you may want to be careful about whether that is something that you really want to look at as an outcome measure but it certainly can be used to improve and has been used  in case ascertainment and identifying specific cohorts. Medication use has been used to look at a recent year, sometimes-historical views, and longer periods of time. It has also been used to look at policy changes whether there are drug alerts, safety alerts that come out from the various regulatory agencies or if there is some sort of policy change, for example reimbursement policy to see if that might have an impact on medication use. Certainly questions related to healthcare quality have been addressed using the pharmacy data such as our patients being prescribed medications in accordance with quality measures or with evidence based guidelines. Medication adherence is also a topic that these data can be used for, for example how much of a prescribed medication are patients actually using. There has actually been metrics developed around how much medication a patient might actually be holding on to whether they are actually looking at using all the dispensed medication, whether they are using it in accordance with the SIG and the instructions.

Exposure to specific medications or medication classes might also be studied, for example are specific drugs associated with better or worse outcomes. Combining outpatient and pharmacy data to identify events for example, can we identify acute exacerbations of chronic obstructive pulmonary disease with outpatient and prescription data? So some medications might actually be administered in an outpatient setting not necessarily prescribed and self administered so you might need to look at both sources of medication use. And also assessing comorbidity or case mix with medication data. So these are just some examples of the types of areas and research questions that have been addressed in the past working with pharmacy data and specifically with VA pharmacy data. Why do I not pause here Erica and see if we have any questions so far to see if we have any questions on some of these just overview examples.

Moderator: We have a couple of questions, is there data in either of these data sets which will tell me concurrency of outpatient medications, release for any opiate or for overlap of two or more opiates and by degree of overlap for instance one week?

Denise Hynes: Well it is possible, anytime a medication is prescribed, anytime a medication is filled, so for a prescription you can certainly look at the temporal relationships of prescriptions if they were administered at different facilities or even if they were administered at the same facilities. And you would actually have a date stamp for a prescription, what is a little tougher to get access to is any kind of medications that were administered in an outpatient setting. So by that I mean parenteral medications typically or an IV administration or subQ administration or even I am unfamiliar with oral medications be it administered in an outpatient setting but something that is actually delivered during an outpatient visit, so that information is definitely tracked and for that matter administration during an inpatient event as well. That information is available within the local data, it is not available in DSS, and it might be available in PBM. It would certainly be available in the Corporate Date Warehouse but we as researchers have less experience with that and it may actually be in some of the early data preparation stages for CDW. So the short answer is you definitely can study the temporal relationship of opiates but depending upon how the medication is administered, oral versus parenteral you may have to compare multiple data sources, I hope that helps. Any other Erica?

Moderator:Yes one more, where can I find what variables are available in the PBM data set?

Denise Hynes: So thank you for that question, we will have a slide at the end that shows the PBM website and it should take you to information both PBM and VIReC for a list of variable that are available. Now the thing to keep in mind that I did not highlight earlier is the PBM database I do not want to make analogies but the PBM maintains and information system, so it is not like a SAS database where you have a view of a particular slice of data, it is a relational database and information system. So they might be able to provide information about the kind of information they track but they do not necessarily provide you and entity relationship diagram of all the data sources that they maintain in their information system. Corporate Date Warehouse does that but those data are not structured quite yet as they are in the PBM database. So the information that is available on the PBM website and VIReC describing PBM will list as a slide and for information that is more detailed you may have to talk with somebody either in VIReC or PBM directly if there is more detail that you require.

Moderator: Thanks Denise.

Denise Hynes: Okay so lets move on to the examples, thank you Erica, and we are going to try and highlight two in depth and the first one is by Mary Jo Pugh and colleagues, and hopefully you have the handouts that have these articles or you can get those yourself. These are recent publications, this one highlights how has patient pharmacy use been measured specifically with regards to medication exposure and outcomes. And this was published in the Journal of the American Geriatrics Society just this year and their primary objective was to examine the association between antiepileptic drugs which they abbreviate AD's and suicide related behavior in older people, specifically older veterans. And just to give you a little  bit of background about the topic, apparently in 2008 the FDA released an alert claiming that twice the risk of suicide related behavior was being observed in patients taking AED’s and they were concerned because elderly patients were under represented in the FDA analysis. So this particular study looked at patients who were 65 and older and specifically looked at the relationship between suicide related behavior in those with and without AED’s. Drugs were identified according to the generic name using the VHA product variable and then they used some modeling to compare time to event so the suicide related behavior, for patients with or without AED exposure. 

So it is a little bit animated here so you can just get a sense of what they actually did first, second, and third. They identified their cohort and the fiscal year is 2004-2006, they initially identified those veterans with an AED and then they identified veterans without an AED and they did a 12-month followup period. They also looked at prior VHA use and prior period so that they could identify those without AED’s, and then during this 12-month followup period, they observed suicide related behavior. In their study they found AED exposure was 4.2% and those with no AED exposure was the predominant almost 96%. And this is taken from their article, this is their table two and it looks at the hazard models specifically for the particular medications and you can see here there are some examples specifically those who were exposed to any AED versus non had a much higher hazard rate, 3.9 compared to those with non, and then their second model they looked at specific types of medications. You can see the medications listed here and they observed that in particular there are a couple of medications in there that have very high hazard ratios and those with the highest hazard ratios are indicating the highest relationship with suicide related behaviors.

Let us go to the next example and this example is studying COPD, Chronic Obstructive Pulmonary Disease, and they looked at medication adherence. This is by Heutsch and colleagues and they published this article in 2010 in the Journal of General Internal Medicine. And they specifically looked at predictors of adherence to inhaled therapies for COPD, so inhalants for patients on multiple inhaled medications and they tried to look at whether adherence to one class of medication predicts adherence to other classes. And just to give you some background the cohort consisted of patients with pulmonary function tests observed between calendar year 2004 and 2007 and they look at those who had spirometry evidence of COPD and those who had medication adherence measure known as Recomp for one or more COPD medications. Medication adherence was assessed for three class of drugs, inhaled corticoid steroids, ipratropium bromide which I will refer to as IP, and long acting beta agonists, LADA’s, and then the Recomp measure, let me talk a little bit about what this is so we are all on the same page. Recomp is an algorithm to measure medication adherence, a one indicates medication available to patients during all days during the period if interest and then the zero indicates no medication available to a patient during the period of interest. They also looked at a specific threshold and they looked at our Recomp value greater than or equal to 0.8 for this study considered adherence. And for baseline adherence, they ranked adherence on to these four levels, poor zero to less then .2, good and excellent as shown here. In their specific analysis they also did regression modeling to assess independent predictors of medication adherence, their primary exposure variable was medication adherence in the six months prior to enrollment. 

And the final model included the following covariant specifically the included age, gender, race, number of missed clinic visits, FEV1 measured as percent predicted, occurrence of greater than or equal to outpatient COPD exacerbations, presence of asthma, lung cancer, and total number of medication classes. And you can see here that they calculated medication adherence during the six months before enrollment therefore they established this baseline adherence and then calculated the recomb six months before enrollment and then they calculated medication adherence during the six months after enrollment, this is considered their outcome adherence that is the Recomp measure six months after enrollment. And then they used this to determine other medication classes that the veterans received in the 12 months before enrollment. And their results taken from the table three from their paper are shown here; baseline adherence to an alternate class of inhaled medication was not consistently associated or was minimally associated with for adherence to different classes of medication, so let us just bring this up here. So for example among those with excellent baseline ICS adherence the odds for outcome adherence to ICS was 4.79. Among those with excellent baseline LABA adherence the odds for outcome adherence to LABA was 6.6. And among those with excellent baseline IP adherence the odds for outcome adherence to IP was 14.13. So baseline adherence to one class of medication ICS, IP or LABA was strongly associated with subsequent adherence to the same class of medication but not necessarily to different ones.

So I am going to do a time check here and see if we have any questions just on these examples.

Moderator: We have a couple of more questions; does PBM data provide scrambled SSN?

Denise Hynes: Good question, I am not sure I know the exact answer to that, I am pretty sure that they do but we are going to come back with a specific answer to that question. It is important for those of you who know about the value of the scrambled SSN, it allow you to link data across information systems. I am certain that PBM will provide the scrambled SSN but we are going to double-check that and get back to this group with a definitive answer.

Moderator:And how often are outpatient prescription orders filled at a VA pharmacy updated at PBM?

Denise Hynes: That is a good question, I do not know the answer to that but we can get the answer from PBM as well. I mean the PBM definitely gets nightly feeds from Vista so anything that happens in a day goes to PBM. How much is updated in the PBM database versus DSS that may be where the distinction comes in., thank you Denise. I think what we will do in the interest of time is I am going to allow these other three examples to be your opportunity to dive deep. And I am going to jump to slide 47 so that we can get into the help and resources and then if we have more questions at the end we will have time to go through those. So I apologize for just skipping through these instead of jumping but I wanted to make sure that slides were available for your use. So let us go into our last topic, where to go for more help. I want to highlight the VIReC webpage here, this is an internet website page, and it provides information on VA data sources and how to access data. It also provides information in one of our resource user guides also known as RUGS for pharmacy data, and the RUG for pharmacy data includes information on both DSS and PBM information, probably more information about DSS but it does include both. It is important for you to notice that these are internet websites so whether you are at your university, whether you want to share this with colleges who are outside the VA, this information is available. We do have information that is available only on the intranet site, which does provide more links, and more in-depth detail that one can only get when you are within the VA firewall so just keep in mind that these links here are the internet. If you would like to get more detail we would encourage you to go to the intranet websites as well.

The HSRData Listserv has been around for a long time, currently it is more than 400 participants in the Listserv, and it includes data stewards including pharmacy benefits management colleagues, managers, users of data including users of pharmacy data. The past messages you should know are available on the intranet in an archive in a searchable format. So if you ever wanted to go back in time and look at threads of messaging, you can actually look at threads of messaging on the HSRData Listserv. It is a little more verbose than Twitter but we still find it very useful. VIReC helpdesk can certainly answer your questions either by email or phone call. We encourage you to go to email because we can track it a little bit better and it is always a good idea for you to articulate your questions in writing because I think it helps you think about how one might respond. but we are certainly willing to talk by phone as well.

So what I am not seeing up here are any of the links to PBM or the links to CDW, so that might be something we send out separately. I do have here some references that I am not going to go through, but we compiled references I believe they go back through, I think the oldest one I saw in here was 2005, these are in alphabetical order for you to reference offline. It also includes, in here some of the technical reports that we have made available on the websites and it also includes some information up through 2012. This is by no means a comprehensive listing of references that include use of pharmacy data, but these are ones that we have referenced in the past and have supplemented with ones that we found most recently. So let us pause now and see if there are other questions Erica.

Moderator: Yes we have a few, is the CDW pharmacy outpatient data most similar to PBM or DSS data, what would be considered the “Gold Standard”?

Denise Hynes: Well gold standard I guess it really depends on what your research question is and I hate to answer a questions with a  question but what you might consider a gold standard could be different if you are looking at medication refills or if you are looking at evidence based guidelines. It depends if you are looking at case ascertainment, you might have to bring in a whole other set of data sources for that. The PBM data, Pharmacy Benefits Management Service they are tracking and they manage the pharmacy package locally so they are really focused on making sure the information about dispensing. SIG is accurate because they also need to do their own internal monitoring of how pharmaceuticals are used in the VA as well as doing some of their own monitoring about potential adverse events, so PBM does some of that. So if you think about what a data steward is constructing a dataset for and you might just keep that in mind, context is always important using data. DSS constructed the NDE with the mindset of being able to track use of pharmaceuticals, track costs, remember DSS was originally intended to track inventory, cost, product use and it has been over time that we found that those data are extremely valuable for also linking with other sources of information. 

DSS data does not have SIG, does not have many of the detailed instructions that PBM has. Corporate Date Warehouse is new, and it is full utility I would suggest is not yet known. The BCMA table is available in the CDW and the product table, and I would encourage examples of research that compare sources, I think that is highly needed. We have increasing use of the CDW pieces of the data and as more of the information becomes available in CDW, I would hope that we will have more examples to compare the different sources for different purposes. That could be a whole other lecture I suppose, and in fact, VIReC is doing some miniseries on CDW, the Corporate Date Warehouse so as more information is organization and turned in to production level data for use in the CDW. That will become a topic for discussion in our miniseries, so I would encourage you to pay attention to those announcements. Any other questions Erica?

Moderator: Yes, is it true that the prescription outpatient file contains both inpatient and outpatient prescriptions fills along with an indicator for inpatient versus outpatient status?

Denise Hynes: Well now that sounds like it comes from one of our experienced users and I do not know the exact answer to that question because what is not completely clear in that question. To me is whether or not we are talking about the SAS databases or the PBM databases; is that more apparent Erica from the question whether it is DSS...?

Moderator: No it does not.

Denise Hynes: Some things to keep in mind, the outpatient pharmacy dataset does include information about, it is hard to know from this question, so I am going to defer on this question and maybe we can get more clarification from the questioner, any other questions?

Moderator:Yes, thank you to Madeline McCarran PBM does provide scrambled SSN.

Denise Hynes:Thank you Madeline we appreciate it, one less thing we have to followup with after our lecture today.

Moderator: Here is another question, how are prescriptions prescribed by VA provider and filled at an outside pharmacy captured in the VA pharmacy databases?

Denise Hynes:Boy if Madeline is still on we might have to ask Madeline for the answer to that question. There is a package now that is part of the Pharmacy Benefits Management package in Vista where they are trying to capture data from outside pharmacies. I know we have talked with some researchers who collected some of this in text like in some of the notes data and I am not aware unless PBM corrects us that this information is in any collected in any standardized way in the PBM local package, but it can be capturing in text notes.

Moderator: What options are available for CMS/VA pharmacy data?

Denise Hynes: So that is a question that we probably could cover in one of our medicare lectures but since it was asked here I can tell you that in the medicare data, you know Medicare data only reports information on those claims covered by medicare or medicaid. Recently VA has gotten permission to acquire the medicare part D slim file is what they are calling it and we can highlight this in one of our future lectures. But it will include medications that veterans who will have medicare coverage also have part D coverage for specific medications covered by medicare Part D. so not to cast aspersions on it but veterans who are dually covered by both VA and medicare and then also have part D. I would suggest that if you are interested in that you should look to see if the medications specifically that you are interested in are actually included in the Part David: program before you start requesting the Part David: data. But the Part David: data will be available on request for research through VIReC and through Operations research through the MAC, now you can request it. I am not familiar enough unless somebody from my medicare group tells me exactly what years are going to be available but it will be back to the start of Part David: and then probably lagged about two years.

Moderator: Great thank you Denise, we are at the top of the hour so we can answer the remainder of the questions offline. Our next session is scheduled for Monday May 6 from 1:00 to 2:00 pm eastern and is entitled Assessing Race Ethnicity, presented by Maria Moore.

Moderator: Thank you for joining us everybody and please as you exit the seminar do fill out the feedback survey that pops up on your screen, have a wonderful day everyone.

Denise Hynes: Thank you.

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