**Transcript of Cyberseminar**

**VIReC Good Data Practices**

**Sessions4: Reduce, Reuse, Recycle: Planning for Data Sharing**

**Presenter: Linda Kok, MA**

**May 29, 2014**

*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 www.hsrd.research.va.gov/cyberseminars/catalog-archive.cfm or contact virec@va.gov.*

Joanne Stevens:At this time I’d like to introduce today’s presenter Linda Kok. Linda Kok is the technical and privacy liaison for VIReC and one of the developers of this series. I am pleased to introduce to you now Linda Kok.

*Linda Kok:*Thanks Joanne. Good afternoon or good morning. Welcome to VIReC cyber seminar series for data practices. The purpose of this series is to discuss good data practices throughout the research life cycle and provide examples from VA researchers. Before we begin I want to take a moment to acknowledge those who have contributed to this series. Laura Copeland of San Antonio VA, Brian Sauer at Salt Lake City, Kevin Stroupe here at Hines, Linda Williams at Indianapolis VA, Brenda Cuccherini in ORD, Denise Hynes or Director at VIReC, Arika Owens our Project Coordinator here at VIReC and Maria Souden the VIReC Communications Director and of course none of this could happen without the great support provided by the cyber seminar team and CIDER. 

The research life cycle begins when a researcher sees a need to learn more, formulates a question and develops and plan to answer it. The proposal leads to the protocol and the IRB submission. When funded and approved the data collection begins, the data management then data management and analysis. It may end when the study is closed and the data are stored for the scheduled retention period or perhaps the data generated in the project are shared for reuse and a cycle begins again. 

In the four sessions that make up this years good data practices cyber seminar series we have followed the steps of the research life cycle. In the first session Jennifer Garvin presented the Best Laid Plans: Plan, Well, Plan Early, which looked at the importance of planning for data in the early spaces of research. Two weeks ago Mat Maciejewski presented The Living Protocol a managing documentation while managing data. That session focus on documentation of data during the various phases of data management. Last week Pete Groeneveld described ways to track decisions called Controlled Chaos: Tracking Decisions During an Evolving Analysis. Today I will present Reduce, Reuse, Recycle: Planning for Data Sharing. I’ll look at how we can share our research data for other research in the VA. If you find The Good Data Practices Series helpful and you want to know more about using VA data be sure to check out VIReC’s database and methods cyber seminars hosted by CIDER on the first Monday of every month. 

Before we jump into session four we’d like to know about today’s participants, about you. For this question we’d like to know about your role and also your experience. Our question is what is your role in research and level of experience? So in the polling panel look for the combination that best describes you. Are you a new or experienced research investigator. A new or experienced data manager or analyst. A new or experienced project coordinator. If your role is not listed please select other and enter your role and experience on the QA panel.

[Pause for poll answers]

*Linda Kok:*So we’re watching the results come in. Experienced data manger analysts are in the lead. 

[Pause for poll answers]

*Linda Kok:*Heidi do you think we’re just about ready?

*Moderator:*Yeah it looks like they’ve settled down a little bit there.

*Linda Kok:*Okay. So we have the manger analysts, the experienced manager analysts and experienced coordinators are the top two with experienced research investigators. So we’re hoping that maybe you can suggest to new project coordinators or data managers or new investigators that they might like to take a look at the recording of this presentation and all of the others in the series if you would. Thank you very much.

This time we have a second sort of general poll. We’d like to know how many of the good data practice sessions you’ve attended or viewed online this month including today’s. So the categories are simple. One, two, three or all of them.

[Pause for poll answers]

*Linda Kok:*Wow I think we’re settling down a little bit at it seems to be very evenly distributed. So if you haven’t caught the other, the previous presentations I think you’ll find that there’s a lot there of value and they are available as recordings. 

So let’s begin. Thank you very much Heidi. In today’s session we’ll explore why data sharing is important for research and the issues we should consider when planning for data sharing.  Here again we want to find out a little bit more about you. Our question is are you working on or planning a project that will produce a data set that might be shared for reuse? If yes for reuse by yourself or yes for reuse by others or not at this time.

[Pause for poll answers]

*Linda Kok:*Excellent I think that sharing for reuse by others is even beating out not at this time and that’s great. I think that combined the 21 or so and 27 that would be 47 that’s almost half or just about half of all the people online today with us have some plan for developing data in a project that might be shared. Thank you very much Heidi. 

Today we’ll focus on traditional project close activites, why we should consider reusing our research generated data, project close activities if we’re sharing data. We’ll describe what a research data repository is and what requirements are described in VA policy for research data repositories and things to consider when creating a research data repository. 

In a traditional project close you would notify the R&D Committee and IRB when you are ready to close the protocol. You would need to determine what data must retained. The obvious need is to have enough data so that if necessary you or someone on your team can replicate your findings to descend your research. This would probably include you’re analytic data and any unique data sources that cannot be readily recreated. These data must be, excuse me, I just got a frog in my throat. These data must be secured indefinitely until a schedule for their disposition is included in the VA record control schedule 10-1. Access permissions for you and your project team must be removed for all data, project data containing PHI. This project does vary from facility to facility so you have to check there with your IRB. You will be allowed to retain your tables and charts used for publications and presentations but there’s a new awareness in the VA of the increasing risk of re-identification of HIPAA the identified data. Keep these concerns in mind when you select the data you will retain. If there is any question about whether there’s a risk of re-identification consider verifying your decision with your local facility privacy officer or ISO. I’m going to put my phone on mute for a second and clear my throat.

*Joanne Stevens:*Linda this is Joann if you can hear me I believe your microphones still on mute.

*Moderator:*I’m wondering if we completely lost Linda. 

*Joanne Stevens:*That might be the case. 

*Moderator:*She is still in the meeting but no audio.

*Joanne Stevens:*I am communicating with her now a different method to see if we’ve got her back or not. 

*Moderator:*To the audience I apologize. We will try to get this resolved as quickly as possible. If you guys could just hold on for a couple of minutes that would be very appreciated.

*Joanne Stevens:*Heidi I’m going to go on mute for a moment...

*Linda Kok:*All right I’m back. 

Moderator:Oh wonderful.

*Linda Kok:*I’m back. I took myself off mute and pressed the wrong button. I am so sorry. Okay. To restart where we were. All right...so...we can...okay so we can reduce redundant and expensive data preparation and purchase costs. We can reuse research generated data and we can recycle our data sets by selecting subsets of the variables or the original cohort for study or we can develop a new model that addresses a different question and apply that to our research generated data. If we can do this we may be able to save our limited resources for other research activities. Having to recreate a data set already created by another researcher just wastes time and research funds.

So every day we create 2.5 quintillion bytes of data. So much that 90% of the data in the world today has been created in the last two years alone. This was statement made in August 2012, two years ago by IBM as part of their bringing big data to the enterprise presentation. We can only imagine how much data has been created since this statement was made. Creating all this data imposes huge costs of the VA and research service to the extent that we can reduce those costs through reuse of research data. We should try.

Open data can fuel entrepreneurship, innovation and scientific discovery that improves American’s lives and contribute significantly to job creation. This was from an executive order in May 2013. So the White House is clearly on board with the open data, open science initiative. Forbes Magazines reported that Johnson & Johnson recently agreed to release its data from clinical trials to researchers. That includes not just the results of the study but the results collected for each patient who volunteered for it with identifying information removed. That will allow researchers to re-analyze or combine that data in ways that would not have been previously possible. Access requests for the data are to be managed by the Yale School Medicine’s Open Data Access Project, YODA. Harlan Krumholz...at Yale...I have this here...says if science is to be progressive and self correcting it’s critical for multiple groups to look at the data and draw their own conclusions and put the results in public view. NIH’s view all data should be considered for data sharing. They feel it should be made as widely and freely available as possible while safeguarding the privacy of participants and projecting confidential and propriety data. NIH requires research applications from more than five hundred thousand dollars in a single year to include a data sharing plan or a statement explaining why data sharing isn’t possible. NIH explains to reasons for sharing data as these: expediting translation of research into knowledge, products and procedures; facilitating the education of new researchers permitting the testing as new alternative hypotheses and methods; supporting methods and measurement studies and reinforcing open scientific inquiry. So if the White House and Yale and NIH all have their reasons for supporting data sharing why make your data available for reuse? You may want to reuse the data yourself or allow access to a co-investigator. You may save considerable prep time and money in your next project. You data may be unique and not easily replicated. They may be too expensive to replicate or your study may include a unique population or be conducted at a unique time. Reuse by others will promote your own research program when they cite your study and your data set in their publications or presentations. Finally sharing your data may foster new discoveries in science.

So is your project ready for data sharing? In session one, two and three we heard about the importance of planning ahead and documenting as you go. If you’ve woven the documentation process into the work flow of your project as our presenters demonstrated you will have built an accurate, systematic record of the research project process that captures decisions, actions and the reasoning behind them. This may have made your research more rigorous and efficient but if you decide to share the data it will also provide the necessary facts for anyone who reuses the data later including your future self if you should decide to reuse the data. Among the documentation must haves have been described in this series is the a description of your project, the data and the methodology used to create the data. Before you can consider, excuse me, before you can consider sharing the research data you must have the appropriate authority. If you are collecting data for consented subjects be sure that the HIPAA authorization contains language that permits reuse for additional or subsequent research. The individual must be adequately informed of your intent. This is one more reason that it’s important to think about and plan for data sharing while you were still developing your proposal. If you haven’t consented subjects you must have a waiver of HIPAA authorization approved by your IRB for data sharing. The data owner or steward for each data source used in creating the final data set must grant permission before any of their data can be shared for reuse. This should be clear in any agreement you have with them. Finally if your project has an agreement with a non-VA data source such as the surveillance and epidemiology and end results or SER program of the National Cancer Institute that the agreement must include language specifically granting permission for the data to be reused for additional research. 

So...we saw at the beginning in a traditional project you would close the—you would notify the R&D Committee and notify the IRB and decide what data needed to be retained and arranged for it to be secured. To share your data once your study is completed you’ll need to notify the R&D Committee and get IRB permission to keep the project open for data sharing. To do this you will first need to identify the data you want others to be able to use. Unless you planned ahead, included this in your original protocol you will need to amend the protocol so that the project becomes an approved VA research data repository and to accomplish this there is more to do.

First what is a research repository? A research data repository or RDR is a data set or collection of data sets produced and managed under a IRB approved research protocol that can be reused for subsequent research and RDR makes it permissible to reuse research generated data within the VHA for IRB approved protocols only. Data collected for use exclusively for one specific research protocol which will not be shared do not constitute a research data repository. A research data repository can be made up of data generated during the course of one research protocol to prove or disprove a hypotheses and maintained after completion of the project to allow for other research purposes or an RDR may be created specifically to collect data to generate a new research data source for use by multiple protocols. Data in data research repositories come from various sources that may include data obtained directly from consented subjects or from reviewing subjects medical records. Data can also be obtained from other research data or may come from non-research data sources such as the CDW or MED test data sets in the VA. Data can also come from sources external to the VA such as the SER data. Note that for research data repositories the term data means information derived directly from patients or human research subjects or indirectly through accessing databases. It does not include information derived from research involving animals or other types of research that do not involve human subjects. 

There are two approaches to sharing your data. The PI can establish and new repository and manage it or deposit the data into an existing IRB approved research data repository and delegate responsibility for managing the data and access to the data. The data may only be deposited in an a research data repository that has IRB approval. Either way your protocol may need to be amended and so will the protocol of the IRB if you use a existing research data repository.

As this table points out that the key element to whether a research data repository is required is whether the data will be used for more than one protocol. Whether your data is de-identified or contains identifiable information, if it’s going to be shared it must be in an approved research data repository. So what are the requirements in the VA for creating and managing a research data repository? We don’t have time to review all of them but we’ll try to cover the primary requirements. A scientific or ethical oversight committee may be required for repositories that contain a number of different databases or provide data services such as storage, granting access or release of data. For other RDR’s the IRB may provide oversight. If you have questions about creating a research data repository, as I said before, consult with ORD. Remember research data repository is a resource for VA investigators and it must remain in the VA and under the control of the VA.

An RDR requires a VA investigator to be responsible for all activities of the dat repository. This cannot be a person appointed without compensation or WOC or under an interagency personnel action or IPA appointment. An RDR administrator must be named and the RDR administer will develop polices and procedures but it doesn’t have to be the PI. An RDR research data repository specialist is needed and it may also be the administrator, the PI or the someone else on the project. IT support is essential for granting access to data.

One topic stressed in the policy is administrative stability. It’s important to have continuity in the administration of an RDR over time. To this end both the IRB and the RDR Committee must approve changes in the RDR administrator. They must also approve the combining of research data from one research data repository to another. Research data repositories must have written policies and procedures that include the criteria to be used for the deciding whether to release data. They must also include a description of the review process for incoming requests and the procedures to be used for verifying that the requesting projects have R&D Committee and IRB approval if identifiable data are requested. A record of all data reuse requests and approvals must be kept and a data privacy and security plan for the repository data must be included in the policies and procedures.

To summarize VHA permits the use of reuse of research data for additional VA research protocols if the data are in an IRB approved VA research data repository. You can establish the repository yourself or you can deposit your data in an existing research data repository. Detailed requirements for creating a research data repository are described in VHA Handbook 1200.12 Use of Data and Data Repositories in VHA Research. As I said before ORD will provide help for you in establishing your research data repository.

So what’s involved in creating a research data repository? We’ll use an example here. We have an example of a research data repository created by Laurel Copeland at the San Antonio VA. Dr. Copeland had a large VA study surgical treatment outcomes for patients with psychiatric disorders or STOPP and she needed to access a lot of data for a lot of subjects from a lot of data sources to do this project and she shared her policy and procedure document with us and we can share it with you if you would send us a request. When I asked Dr. Copeland if it was difficult to set up the repository she replied to my email LOL, oh my no, it wasn’t particularly traumatizing. Dr. Copeland also shared the request review process document for her research data repository. We showed the first page here, she included a detailed description of the review requirements in the appendix of this document, which we also have if you’d like to request it. 

Okay so what do we need—before we move away from requirements all research data repositories really have to live somewhere. A host is a place where your research data repository will be stored and maintained. So what makes a good data repository host? It should provide data security, scheduled back-ups and a file recovery system. All of our existing VA network servers meet these criteria. It should also provide adequate volume capacity. Can it hold the data? This has not been an issue in the past but some changes are underway that might effect capacity. For example research severs not being funded at specific facilities, at different facilities. A host should offer compatible data formats that can be used with the data. Generally that means SAS and STATA in VHA Health Series Research. These have also been available in the past but some centers are seeing requests for continuing maintenance of the SAS licenses denied. A good host also provides long-term data retention capacity, which is also starting to become an issue at some facilities. Data access provisioning capability may be hard to find if you want to permit direct access even read only access to data in an RDR at your facility. VHA data repositories can be hosted on any VA network server but there is one venue that meets all of these needs. 

VINCI, the VA Informatics Computing Infrastructure currently provides access to data for research projects in VINCI Workspaces and these could be used to provide access to data in a research data repository to researchers based at multiple facilities. What you are seeing here is the opening page of a VINCI Workspace showing the analytics and other software available on VINCI. VINCI provides and according to the list that we just reviewed data security. All research data downloads must have permission and are automatically audited. The VINCI environment is firewalled off for added security and the environment is patched and updated regularly so there’s no maintenance required by the user. There are scheduled IO&T standard backups that include a standard IO&T file recovery system. There’s adequate volume capacity for current users and VINCI plans to add more storage and servers in FY 15. Of course all IT capacity at VINCI, as elsewhere, if dependent on the ability to regularly purchase additional server capacity. As you can see in this screen image compatible data formats, SAS, SQL, Stata are all available on VINCI. Long-term data retention capacity is part of the VINCI mission and data access provisioning capability is already in place. If a research data repository were to store it’s data on VINCI the PI who created the repository would remain responsible for ensuring that the IRB of record reviews and approves the move to VINCI. This is what my VINCI Workspace looks like. I put in just to illustrate how familiar it looks. It looks very much like our own desktops and opening our own files and folders. I’m part of two teams shown here. The WA MAC team and VA VIReC team and each project that you would have access to automatically will show up in your P drive on your VINCI Workspace. Data can be materialized to your workspace in the appropriate data folders so if you were requesting access to a research data repository and once that access had been granted it would show up here on your workspace. Remember that you may not download person level data without prior permission from the data stewards but you can upload data for your project to VINCI and use VINCI as your home base for data management analysis for the research data repository or...or for...data that you use—you obtain usual health care operations data once you’ve cleared the move to VINCI with your IRB and that’s important to remember that they need to know where you’re storing your data.

So now we have a fourth poll question. We’re going to have two polls right here. The first poll question for, our question is: If there were a central research data repository available in the VHA where you could deposit your research data, how likely would you be to share data from one your research projects for reuse? 5 indicates very likely; 4 indicates likely; 3 maybe; 2 unlikely and 1 never.

[Pause for poll answers]

*Linda Kok:*Likely is edging out the others just a tiny bit. I think things are settling down. It looks like...plurality of the you would be likely and if you combined the very likely and likely we have over...about 60%, which I think is really great and I know many of you are already planning to share your data. I hope that this presentation will make you feel a little bit comfortable about that. We’ll continue on.

The next poll question: How likely would you be to use data from someone else’s research data repository? Let’s see how, what you think. 5 is very likely; 4 is likely; 3 is maybe; 2 is unlikely; and 1 is never.

[Pause for poll answers]

*Linda Kok:*We’ll give it just a little more time. Thank you all for sharing all this information with us. Okay I think we’ve settled down. I think more of you are willing to share your data than to use data from other people’s research data repositories. That’s very interesting but it does seem like, at least 54% would be likely or very likely to share data or to use data from someone else’s repository. Thank you very much Heidi.

Now we’re nearing the end. We’re pleased to find that researchers who contribute—we were pleased to find VHA researchers who contribute so much to this series and we were also happy to find several good websites that helped us in our planning. The MIT Library guides online provided great information about creating a plan for data early in the research life cycle and the Inter-University Consortium for Political and Social Research or ICPSR data deposit form was enormously helpful to us by showing the detailed information that must be put together in an organized way before data can reused in any meaningful way. This completes my slides on sharing research data. I’ve included some detailed bonus slides at the end of the slide dec. Please stay with us as well be asking for your feedback. Here is my contact information if you’ve downloaded the slides you will have that information. VIReC has a help desk available to assist you with any questions that don’t get answered today or on other topics at VIReC@va.gov. VIReC hosts the HSR Data List Serve with over 800 data users and data stewards and managers discussing VHA data use and please visit us at the VIReC intranet website, which provides additional information about the content and use of VHA data sets and VIReC.research.va.gov. 

To recap, why did we do this series? Well we really wanted to be able to cover the entire research life cycle with some interesting and helpful ideas. In session one we learned that while we would like our research to take place in an ideal world we should plan carefully—we’ll cope with the reality of research such as unanticipated data problems, staffing issues and changes required by our IRB Jennifer Garvin took us through the benefits of early data planning for data needs, privacy and security and reuse of data. In session two Matt Maciejewski described a documentation model he calls The Living Protocol in which each decision, action and the reasoning behind it is captured within the protocol document creating the story of the research. He walked us through examples of managing secondary data and linkages of primary and secondary data to illustrate the value of documentation. He recommended the example he shared as he put it, after trial and error and begging and borrowing and stealing best practices from other investigators we did not have to invent our research practices alone. There are many experienced researchers who’ve worked out efficient methods for handling the unexpected issues that come up during research. 

Peter Groeneveld told us the ultimate objective of documentation was to explain everything clearly to your future self who will have to decipher these documents while writing a scientific manuscript in the distant future. He explained the importance of clear, well indexed study documentation and introduced a schema for research document organization. He described many detailed good practices for managing data during analysis and presentation and showed us why organization is vital to good research.

We’d like to thank Drs. Garvin, Maciejewski and Goreneveld for working with us to develop the 2014 series. 

Researchers tell us they want to better understand the planning and documentation necessary to great research. Our goal is to help fill this need by sharing examples and tips from experienced researchers and to provide additional supporting information from reliable sources. We hope that you have found something in this series this month that has shown you a new technique you want to try. We’d like to ask you for direct feedback on the things you’ve learned, things you will use in the managing your own research and your suggestions for additional topics for good data practices cyber seminar sessions. Heidi would you please describe what we want our participants to do here?

*Moderator:*Certainly. We have three basically poll questions here so each one on the left things that you learned, middle things you’ll use in your research and the right additional topics and you just need to type your answer in where it says type your answer and then hit the button to the right to send the answer and they will populate on the screen.

*Linda Kok:*And you can all do it all at once. You don’t have to wait for someone else. 

*Moderator:*Correct. I’m actually going to broadcast the results so that everyone can see the other answers that are coming in.

*Linda Kok:*Yeah and this can be things you learned from session one, session two, session three. Did you like the living protocol idea? Was the schema that Dr. Groeneveld presented helpful? Those are all good things...to comment on here. We’re really interested in things that we haven’t covered for developing new topics for future good data practices, cyber seminar sessions. So we’re seeing a lot about research data repositories. I know that there’s an effort underway to provide some guidance on that. ORD is working on providing a little bit more guidance for research data repositories. I think that will be helpful. 

I see in the things you will use the tracking decisions. The living protocol is mentioned. The organizing tips. Planning early. Thinking through and detail before you begin. Version control is always a topic and I’m glad that some of you have seen something here that you’ll use there. In the additional topics SAS coding documentation, okay that would be how to document your SAS code specifically. I think that’s really good topic. Some more experience. Sharing experience with sharing data. Yes I think we’d love to get Dr. Copeland or anyone else if you can suggest names of anybody that has research data repository. We found it difficult to find people on that. Collaborative research definitions examples and requirements. I’m not quite...sure what that one means. If you could add a little bit more...data extraction and coding for database studies. More examples and templates. Process coding. I think all of these have been very good. I like that someone said the things you learned what the people are willing to share and that’s always a good thing to know. So I think we’re about done. I hope we’ve been able to capture all of these Reponses. Right Heidi?

*Moderator:*Yes we do have all them captured on the back end so...

*Linda Kok:*Okay.

*Moderator:*...[crosstalk]

*Linda Kok:*Wonderful. So we can respond to that. So now I think we are ready for questions. I can’t see my screen here. 

*Moderator:*I brought it back here. There we go.

*Linda Kok:*Oh thank you. All right. Questions? So let’s see what we have on our Q&A. Joanne?

*Joanne Stevens:*Sure. So the first question Linda is, is there any suggested language for including and consensus or information sheets for obtaining patient authorizations for data sharing?

*Linda Kok:*I had one last year and I looked everywhere for it. I guess I’m not as organized as we preach. I will find that data sharing language. There was a good example that made it clear that the data developed and gathered—that your data used in this research will be used for subsequent research projects. Something on that order. It needs to be very specific that you have to tell them exactly what you’re going to do and I will try to get that information and we will make that available. I think probably the best way to do that would be in a data issues brief item in a future data issues brief. So look for that in the direct dib [PH]. 

*Joanne Stevens:*Thanks Linda. Next question: Are there differences between requirements for keeping data for the use of the same PI or team for use in a subsequent protocol?

*Linda Kok:*Not generally. There’s only one project that I know of that has a separate authorization process and that’s the VA CMS project here at VIReC. We have a slightly different way of doing it but generally with VHA data sources the—if you want to share the data for your own subsequent research protocol you have to create a research data repository and if you want to share your data with others you have to create a research data repository and it has to be IRB approved.

*Joanne Stevens:*Thank you. Next question: Is there oversight of animal data?

*Linda Kok:*Well the IRB over sees animal and other research but—well actually R&D Committee over sees...animal research but animal research is not...animal research data are not...defined as part of a research data repository. Animal research data are separate from research data repositories that we’ve been talking about here today. So I think, yes the R&D Committee over sees that research but we’re concerned with human subject research here.

*Joanne Stevens:*Okay. Thank you. Next question: Are there differences in data sharing compliance with local versus central IRB?

*Linda Kok:*Could you say that again Joanne?

*Joanne Stevens:*Yes. Are there differences in data sharing compliance with local versus the central IRB?

*Linda Kok:*Okay I’m thinking compliance means requirements. Are there differences in the data sharing requirements? No data sharing requirements are across the VHA. They cover all research within the VHA whether you’re going to a multisite study that uses the central IRB or your own local IRB.

*Joanne Stevens:*Thank you. Next question: Do you anticipate researchers having access to SAS software on the VINCI to actively create code and analyze data?

*Linda Kok:*SAS is already available on VINCI to create code and analyze data. They have, in fact, a whole SAS grid devoted to really working—it’s especially good for high volume processing where you can utilize parallel processing and make your programs much faster and they have staff that will help you do all that. So SAS is well supported up in VINCI and will continue to be.

*Joanne Stevens:*Thank you. Next. It seems people aren’t as willing to use other’s data. Could this be because data quality assurance isn’t being documented well enough in repositories?

*Linda Kok:*Well I think we’re still at early days in repositories. I think there’s not been enough experience with sharing in order to really feel confident in the data that you’re getting and that’s one of the reasons that we stressed everything we stressed in sessions one, two and three. What we would like to see in the VA is a data and project documentation at the end of the study that makes it impossible for a whole new team walk in and replicate the study and then if the data are amenable to it to reuse that data for additional research. This is not always possible and one of the reasons that we started on the good data practices series in the first place we were asked at VIReC to be host and curate a set of data that the VHA had paid a lot of money to create for a study. It wasn’t a research study but they wanted to make the data available for research. We could not get...adequate documentation on how the analytic file was created and because of that we couldn’t really offer it and we couldn’t put it up for others to share because we really couldn’t describe how the data had been collected and this was not collected by a VA researcher. It was an outside entity for the VA and we were very surprised at how inadequate the documentation was and that was one of the reasons that we became so interested in making sure that the data documentation and project documentation and that complete description of your methodology is available for every research project when it closes.

*Joanne Stevens:*Thank you. Next question: Should you inform participants that you plan to store their data for future use if the data will be completely de-identified?

*Linda Kok:*I’m not the person to answer that question. I think that-that would be for ORD to answer. So we would happy to send that up to Dr. Cuccherini for you if you’d like and if we take your name we can send you a reply or we can put in a dib tip [PH].

*Joanne Stevens:*Thank you. Is the VA considering the creation of a central research data repository?

*Linda Kok:*Interesting question. I don’t think the VA is really considering it right at the moment. VIReC is thinking about it and we kind of talked to VINCI every now and then about it so if there’s—it seems like there would be interest out there so we’re just trying to see what people are doing in...what researchers are doing with data sharing and finding out more and more. That’s why we ask so many polling questions to find out what the interest is. I think you’ve shown your interest here today in the polling questions and we will take those up the line and figure out what we might be able to do.

*Joanne Stevens:*Thank you. Next question: If the study is not yet closed can you share data that is not in a data repository?

*Linda Kok:*You cannot share data with another protocol...at all. So I would say no. Once it’s closed, you know, whether or not to share—if you’ve written a protocol that includes a research data repository, so you’d be developing data as you go along and you can—if your protocol for your research data repository says that you want to share the data before you actually closed the protocol, the original protocol, you might be able to do it that way but you want to make sure you’ve finished your research, if you have a research question and make sure that you can protect integrity of that data before you start sharing the data with other people. You’d need to think about it and you’d also probably want to touch base with ORD on that.

*Joanne Stevens:* Thank you. Next: If SAS is available on VINCI why does it seem that you presented that researchers not having SAS access/contracts renewed at a local level can be barrier to data sharing?

*Linda Kok:*Well if you had, okay if you were going to host your data yourself on your own local network server whether it’s in your facility or your VISN or your region, if you were going to host it there you would have to have SAS available for people who want to reuse to use it there. If you weren’t going to distribute it out to people but have it in one place protected and have them come and get you would need to have SAS on your local server, whatever you use for your research. In some cases SAS contracts or SAS maintenance contracts are not being renewed at local facilities for research and it’s not all, it’s not a lot but there have been some instances and...if you don’t have it-it would be very hard to let people use the data up on your server.

*Joanne Stevens:*Thank you. Linda this was comment. We would have immense interest in sharing data but if found that Handbook 1200.12 may be too onerous for us to take on with our current staffing resources.

*Linda Kok:*Yes. There is guidance coming for 1200.12. I think some people have done their best to interpret the things, you know, the major points, the things that I discussed today and just go item by item in the in the requirement section and just their IRB to be their oversight committee, name somebody as an administrator who can mange the data long-term, make sure that you have somebody who can...knows or learn about sharing data, about data repositories and then...get an IT person or an IT center or somebody to help you with the access to the data and you can do that by sharing the data by sending it out or by having people come to you, something of a single source. If you wanted to put it up on VINCI coming up there would be a simple matter. You can just get started and write up how you’re going to do it, what the requirements you’re going to use, how you going to check to see if the R&D Committee and IRB have approved the project that’s requesting the data? That’s your biggest requirement that you have a process in place for making sure you follow the rules. I didn’t touch on all the rules but if you go through the rules as they’re stated and just pick out the idea and follow that idea, get it on paper, send it to Dr. Cuccherini if you have real concerns and let her see it and just go. Have your IRB look at it, see if they think that’s ready and just go and do it. We want to hear about your experience.

*Joanne Stevens:*Okay thanks Linda. That’s it for today’s questions everyone. We’d ask Heidi to post the evaluation please. For additional questions or information regarding this topic or information on any of the prior sessions please email the VIReC help desk at VIReC@va.gov. Thank you to Ms. Kok for taking the time to develop and present today’s session. Archives of today’s sessions and the entire series are available on the HR&D website. Thank you for attending and have a great day everyone. 

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