 Today's webinar, which again is entitled, Accessing Linked CLSA Data at HDRN Canada Data Centers. We have a series of presenters. We have Dr. Andrew Costa, Dr. Sophie Hokeman, Carmen La, and Lindsey Gilbert, as well as Anne Hayes will be joining as part of the Q&A. Andrew Costa is an Associate Director of the CLSA, the Canada Research Chair in Integrated Care for Seniors. A legal research chair in clinical epidemiology and aging in the Department of Health Research Evidence and Impact at McMaster. Sophie Hokeman is the CLSA Data Linkage Coordinator. She works closely with HDRN Canada Data Centers and the DASH team to enable data linkage. Carmen La is a program specialist with Data Access Support Hub, which is the DASH acronym I've used previously. She's located at the Canadian Institute for Health Information in Toronto. Lindsey Gilbert has been working with the HDRN since 2019 as part of her role of Data Services Manager in New Brunswick. And finally, Anne Hayes is a Health Strategy and Partnerships Executive with over 25 years of experience delivering results through policy research and program initiatives. So there was lots more I could have said about all these presenters. I was trying to add a few quick key highlights. So I welcome you all and I'm sorry I didn't do justice to your bios, but I do want to get started for this very exciting webinar today. So over to you, I believe, Andrew. Thanks, Jennifer. And welcome everybody. We will queue slides and get started. That's wonderful. Today's, I think, a little bit of a departure from the typical presentation and content format for CLSA webinars. Whereas generally, these are discrete research presentations. Today, we're extremely excited. It's a milestone for the CLSA and HDRN to announce that linked CLSA data are available in multiple provinces for use by Canadian researchers. And so that's really the goal today. What we want to do today is also just describe a bit about the various components that made this possible, overview the CLSA and HDRN's data access support hub. Talked about linked data availability and talk about the process for accessing linked data across jurisdictions. Before I get started, I want to highlight a few things. First, this has been, this is ongoing work and but what we're presenting today around data availability is the culmination of a multi-year complicated process to securely and within ethical and legal guidelines link the CLSA data to provincial data repositories. And those provincial data repositories, as folks here I'm sure will know, are held under provincial legislation and particular privacy rules. It has been a multi-year, multi-individual team effort across jurisdictions to get this together. And we want to acknowledge everyone's work in as part of this process and today celebrate it. We continue the work as we go on and we expect that this work will achieve maturity in the next 18 months to two years. And together as part of CLSA and HDRN, we are going to learn an awful lot scientifically as well as I think procedurally about the process of accessing linked CLSA data. So that's the goal today. But the main announcement is linked CLSA data is available to I'll start off by over viewing the CLSA as a study and as a national data set. It is difficult to do that in the time I've got a lot of because it is an awful lot of data and it is an absolute huge platform. But rest assured that some of you are extremely knowledgeable of the CLSA and have access CLSA data through the existing channels already and are aware. Some of you, maybe that's not the case, but we have there are many resources available online, lots been published and we want to reserve time for lots of Q&A to discuss it. So what is the Canadian Longitudinal Study on Aging or commonly known the CLSA? It is a research platform that is designed a multidisciplinary research platform with a set of national infrastructure that is designed to answer questions of today and tomorrow around our aging population. And to answer as many questions as the platform can conceivably answer and of course it can answer. Many question it is a important thing is it is a longitudinal platform. And I'll go to next slide, Sophie, that is a major strategic initiative of CIHR planning for the platform began with many individuals, but chiefly, Carmen Durena, Christina Wilson, and Susan Kirkwood, Kirkland and many years ago in 2001 will overview sort of some of the dynamics of the cohort here. There are over 160 researchers and collaborators involved across 26 institutions. It is a pan-Canadian platform. It is multidisciplinary and so investigators and interest areas and working groups are established across biology, genetics, medicine, psychology, sociology, economics, epidemiology, nutrition and chief of concern today is a little bit around health services. And there are content available that address these domains through various primary data collection strategies that are a part of the platform, which I will overview, all of which provides an extremely exciting base cohort to do research and detailed research. And from the perspective of health services evaluation, provides an extremely valuable base cohort to do health services research, which is typically the domain of linkage with our administrative health data across jurisdictions. Its largest research platform was kind in Canada in terms of its breadth and depth and its unique internationally in that light as well. The key feature is that it's following over 50,000 individuals that were recruited at age 45 to 85 at baseline 20 years ago in 2011. And so we celebrated a 10-year milestone not long ago. Next slide, please. Two key features to know and folks who have access to CLSA know this extremely well. There are two cohorts within the King and Long Student Study and Aging of those individuals, over 50,000 individuals recruited at baseline in 2011. There's a tracking cohort and this is just over 21,000 individuals, as you can see, that were recruited from all 10 provinces. And these individuals are followed on a, let's call it a bit of a lighter protocol through computer-assisted telephone interviews, our CATI interviews, as we say, that are conducted at our partner institutions across the country that are, in fact, over about 60 minutes in length. And this information is available online. We will shortly share links, but many of you are aware of that. But essentially this covers domains of general health, smoking, your typical age and demographic characteristics, cognition, mood, activities of daily living, instrumental activities, social networks, care receiving, in terms of formal care, formal care, injuries, falls, retirement and labor, retirement planning, hearing vision, I can go on, it's all available online. And so though it's a lighter protocol, it is quite detailed, it is very detailed. The comprehensive cohort is the larger majority of the CLSA. Here you see over 30,000 individuals recruited at baseline. And these individuals are within 25 or 50 kilometers from a CLSA data collection site, which are academic institutions typically in multiple provinces across the country. And these individuals are followed with the same content as the tracking cohort, but on an expanded set through in-home interviews and uniquely physical assessments and biospecimen collection done at these data collection sites. And for these individuals, there is a greater commitment in terms of time invested. And of course, we always acknowledge the participants who make this study possible and donate their time to do this, without which we wouldn't have the CLSA. And so it's a very exciting platform with a lot of information. You're encouraged to look online and Link was just posted. Next slide, please. This is sort of like a, I maybe call this a CLSA tattoo, folks would be familiar with this. And so it's, here we have a very nice visual of the main mechanisms and data collection points of the CLSA. So as was mentioned, at 2011, over 2,000 individuals were recruited. There you see on the left, we have the tracking cohort, which are followed by questionnaire. On the right, you have the comprehensive cohort. And as you could see, the main mechanism of the CLSA was at baseline. In about 2011, there was a baseline interview or a set of data collection, rather, and there was a maintaining contact questionnaire in that same period. That is the baseline period and data collection. And then the protocol stipulates every three years of follow-up. And so at the moment, we are completing follow-up three and bridging into follow-up four. And this study is, we'll move forward all the way until 2033. So that's 20 years of data collection. Link data that are available are usable for 20 years thereafter established in the protocol as a minimum. And information is collected. The link has just been posted on on where you can see all the information collected. There's data preview portals on the information that has been collected. The important thing to mention is that as part of the CLSA protocol and in fact, there's publications on the approach to consent and data linkage that we can share, the data linkage was always conceived as part of the protocol. And in the CLSA, participants were able to consent and provide their health card number for linkage to provincial data centers, data through provinces. And if I'm not mistaken, and we don't have the number here, over 92% of CLSA participants did consent to that linkage. And where we have done linkage, we have extremely high linkage rates over 99%. And so that provides a fantastic mechanism. It's also an important mechanism to CLSA. As folks are aware, recall bias and issues around health services use is a challenge, particularly where there are three-year follow-ups. And so essentially data linkage provides the ability to understand health service use and those various factors on a very rigorous basis. Next slide, please. And so important to note that the CLSA is, of course, national on scope, national meaning, including the provinces in this case, not territories in terms of participants for data collection. Information on the original recruitment targets and methods are available and are easily referenced. There you see sort of the sites. And the next slide, I believe, right? So the data that are available, I think I over you probably appropriately enough. Many data are available. It's important to say what's not available. As part of the national infrastructure at McMaster University, there's a biorepository and bioanalysis site. And of course, those are not available to provincial data centers. Those are in cold storage. So of course, that's not available. There are information that are being characterized in terms of metabolomics and genetics that have not been shared. And information on Indigenous identifiers in the CLSA have not been shared with provincial data centers as well. And that is because provincial data centers have their own mechanisms or various mechanisms for collaboration with Indigenous communities. And so that is available on a case-by-case basis. But what has been shared is essentially all alphanumeric very data that are available through the CLSA already as part of our seasonal data collection, data application processes to receive data. And so all of that is available all the way up until follow-up to, which is what's available through the CLSA. The plan going forward is that whatever information is available through the CLSA will be available by update from the provincial data centers. And each provincial data center, who we have a data sharing agreement, will maintain the same data set. And it's also important to note that within each provincial data center, obviously only a portion of the CLSA data can be linked for citizens residing in that jurisdiction. But that provincial data center maintains the complete copy of the CLSA data, which is available to researchers who are having a single region access to linked data. But the CLSA encourages multi-regional access to the data. It is a national platform. And so that's highly encouraged. Next slide, please. You can have a look online. There are wonderful resources to understand the data. Many of you are very much aware. This is a good resource to understand essentially what is the data dictionary that is available. And much has been published on the CLSA, so not many surprises. Next slide, please. Okay, I think that's it for the overview. I'll pass it off to Carmen to discuss access at provincial data centers. Thank you, Andrew. And thank you, everyone, for attending today's session. So we can go back to slides just to the handshake slide, please. So just to start off, in February 2021, ACE during Canada and CLSA announced a new partnership. And so this partnership aims to streamline requests to link data through ACE during Canada's data access support hubs, also known as DASH. And so this enables the development of data access processes and methodologies that are consistent across different provinces and territories. So ultimately, linking the CLSA data to administrative health databases across provinces will enable researchers to make important population comparisons that will inform healthcare practices and policies over time. Next slide, please. So to provide a quick overview of ACE during Canada, we can go to the next slide, please. Presented here is ACE during Canada strategic framework. ACE during Canada is essentially a distributed network. And our mission is to bring together people and organizations across Canada for transformative and world-leading health data use. And so one of ACE during Canada's main goal is to develop and improve services and support for data access. As a result, DASH was established in early 2020. Next slide, please. And so DASH is a one-stop service where researchers can receive guidance on their study design and development and request access to multi-regional data. And so there are about 13 organizations from across Canada who hold data and are part of the DASH network and work together to support data requests. DASH helps the facilitation and coordination between research teams and the data centers to make the data access journey more efficient. So it is important to note that DASH does not hold any data. The data continues to reside at the data centers and we continue to follow region-specific legislation and policies when it comes to data access and release. Next slide, please. So this is just a quick snapshot of our current member organizations where we have data center reps from each data center who can support your data request within the DASH program. Next slide, please. So since the launch of DASH, we have developed streamlined processes to provide better support and coordination for researchers' access to multi-regional data. We've developed resources and tools which I'll touch later on in this presentation. But essentially over time, these solutions will help further automate the data access request process. Next slide, please. So as part of the DASH and HR and Canada partnership, a steering committee was created to understand how the DASH data could be brought into and held at our DASH data centers. But agreements need to be in place for data transfers and data linkages. And we developed processes and documented standard operating procedures to ensure a seamless data request from researchers. So in terms of the sales, they linked data availability. Currently, this is the status at each of our DASH data centers. So in BC, they have completed their linkage with a rate of 99.7%. In Ontario and New Brunswick, linkage is still in progress. But these three sites are anticipated to complete or to accept data requests linked to fill-as-say data by the end of January. All the other sites, except for to catch one, have all started their data sharing agreement process. And they're all in various stages. For example, in Alberta, the first draft of the data sharing agreement is still underway. Whereas in Nova Scotia, they've executed their data sharing agreement, but they're still waiting for local approval to transfer data from fill-as-say to HDNS. So if researchers are looking for linked fill-as-say data to administrative data, there are two routes that they can go through. If they are looking for multi-racial linked data through DASH, they would come to DASH. If they just wanted single-region linked data, they can go directly to the data center that is holding the data. So I'll now get into how DASH can help you with your multi-racial data request involving fill-as-say data. So essentially, this is DASH's process. So in phase one, as a first step, a member of the research team would submit an intake form through our DASH portal. After receiving the intake form, DASH will schedule an intake call with the research team to review the information provided in the intake form. And at this stage, we do try to bring in the local DASH reps from our data center to support any initial questions, provide some preliminary feedback, and after the intake call, researchers may be asked to refine their intake form before the proceeding. DASH will then review the intake form and confirm eligibility and feasibility of the project and develop cost estimates if requested. When the project is deemed feasible and the researcher has confirmed funding and they're ready to proceed, then the project would move into the data access request stage, also known as the DAR stage. So in this second stage, researchers would complete a DASH DAR through our portal, which will then undergo an initial review by our data center. Once the DAR is complete and ready for approval, the DAR will also be sent to CELAS A in which they would have 14 days to reject the approval. Otherwise, the project would proceed as usual. DASH and data centers will continue to complete the necessary local reviews and approvals, and then start drafting agreements, preparing the data, and then ultimately enabling the data access. If applicable, some data centers may provide analogical services as well. So then in stage three, researchers will be able to access data as per local data center policies, and they would also be reminded to review the CELAS A data user responsibility checklist. Once researchers receive the data, they would be invoice by each data center. They're receiving data from within DASH, and then in addition, McMaster University will also issue an invoice on behalf of CELAS A. So DASH has developed resources that can assist researchers in their initial development of their project. We have the data asset inventory, which is a repository of data assets available at our data centers, and it can be requested by researchers. So these data assets include administrative data, clinical data, social data, and once CELAS A data is available at our data centers, it will be added as a data asset as well. So this can be a great resource to get a sense of the data available when developing your project. We also have an algorithm inventory, which is another great resource which includes information from systematic reviews to identify published algorithms for measures of population health, health service use, and the determinants of health. All of these algorithms included in the inventory have been validated or tested for feasibility of implementation in two or more Canadian provinces and territories. We also have the COVID-19 data inventory, which includes information about the availability of COVID-19 related data resources at our data centers. We have an informed consent page that provides rich information and guidelines for researchers who are looking to conduct research that involves consent and or are currently designing consent form. We also have the privacy checklist that outlines requirements needed for data sharing agreement. And so we do encourage researchers to browse these resources before coming to DASH. All of these resources have been developed by DASH Collaborate with all of the different data centers. So one of DASH's greatest assets is that we've built the DASH portal, which is a web platform that houses forms that researchers will need to complete through the data access process. So these centralized forms are designed to take the burden off of researchers by reducing the need to complete multiple forms across different data centers. And so using a collaborative space allows for the data centers to work together to ensure data and service availability as well as data comparability. So the intake form will ask basic questions about your project, like what services you're looking for, what your timelines for data access are, what regions you're interested in obtaining data from. That way DASH can provide you with a feasibility assessment and cost estimate for your project. We then go into building the data assembly plan, some of the information collected, and the intake form will feed into the project's data assembly plan. This tool allows researchers and data centers to collaborate and document centrally the project's data requirements, their analytical plan, which will eventually inform local data creation plans. And then we have the data access request. So this new DASH form allows researchers to complete one single data access request form when requesting data from multiple provinces. So one caveat right now is that projects that involve CHI-HI or STATS-CAN data, researchers will still be directed to complete separate forms for those requests. However, the DASH DASH is a big step forward in reducing the number of DASH forms that need to be completed. So the DASH form builds on previous information that DASH has collected for your project, and you will also be asked to obtain and attach relevant supplementary documents such as ethics approval, consent forms, applicable funding letters that are all needed for review and approval of the project. And so these forms are all integrated with each other, and so information that was provided in the intake form will downstream into the DAR relevance. We are continuing to enhance the forms and the portal in general to further streamline and automate the process. So for those who may be interested in requesting CELAS-A linked data through DASH, we invite you to complete the following steps to initiate the process. Once DASH receives your intake form, we aim to conduct the intake meeting within five business days of receiving your form. Once we have everything we need, we can provide you with a feasibility assessment within two to four weeks. But also to note that timelines may vary depending on the readiness of the research team to meet, as well as the complexity of the project. So if you do have any questions along the way, you can always contact DASH directly and we'd be happy to support you through your DASH journey. So now I'll pass it on to Lindsay to speak about the single site experience. Thank you, Carmen. Hi, everyone. I won't take too much time. I know I'm excited to get to the Q&A as I'm sure everyone is, but as a participating data center in New Brunswick, I would like to highlight today some of the things that from our perspective have helped make this data sharing partnership so successful. Next slide. Yeah. So the first one is that the project felt to us to be truly collaborative and I mean that it felt like a true partnership in that HDRN, CLSA and the data centers were hands-on throughout the whole journey of coordinating agreement review, developing and reviewing standard operating procedures and just being available for meetings and troubleshooting issues along the way. I definitely found there was a lot of give and take with making our respective processes work to make this project move forward. In addition to HDRN data centers and CLSA, of course, having a lot of opportunity over the course of the project to learn from each other. From my perspective, there was also an added benefit of the data centers learning from each other. And for me, I know that learning a lot through the health data research network happens all the time, but being involved in a specific initiative like this one has really helped me apply the information that I learned and think about how we could be doing things differently, which was very beneficial to our team. And finally, consistent standing meetings with a focus on action items. I found that was really key for this project, even when we felt like we were stuck on a piece of the initiative. But that being said, we did adjust the frequency of the meetings that we had together according to the phase of the project that we were in. So we know that early reviews can take longer, so meetings could be less frequent, but we made sure to increase frequency of our collaboration to make things move faster once we were ready to do process development and actually transfer the data into each data center. And on the next slide, I'll just go through a few of the lessons that we learned from being part of this project. The first, of course, is to always include plenty of time for legal review in project timelines. Andrew alluded to the data sharing agreements that we completed, and I have to say that was definitely a very large portion of the work that we did in the beginning. It was very intensive. There's nearly always more back and forth than you think there will be. And in addition to agreement negotiation, when there are so many organizations on board, almost everyone had to deal with some sort of unforeseen challenge, such as legal counsel turnover, changes within their organization, competing local priorities, all kinds of things that made things go a little bit more slowly than anticipated. And as you know, just working on such a big project like this together with so many different data centers, we found that it was easier to make one person at each organization responsible for communicating within their site and then reporting on status and getting everything together to come back to the central group. So even if there were multiple teams within a data center that we worked on for different portions of the data sharing, we made sure that we had that central point of contact to be the common thread throughout. Maybe sounds obvious, but it really helped us. Another thing we did was mapping out data flows in advance. So if you're thinking about going through an initiative like this, we find especially having access to visual data flow diagrams really helps clarify how each data center receives and links data sets. Everyone here probably can appreciate that it's been a complex journey, especially when you compare multiple organizations at once. So having a visual is really helpful there. We also shared some key processes along the way for data access approval, receiving data, linking data to help us find some commonalities that we could start with in creating an approval process, which meant that we really didn't have to start completely from scratch. If we did the project again, I think there would be opportunities to do this in a more streamlined way upfront. So that's a key lesson that we learned. But some of the comparisons that we did as part of this work, which was quite novel, it allowed us to create procedures and other things that will be helpful, I believe, for future multi-regional data sharing initiatives. Also, we observed that common understanding of terminology is huge. I can't overstate that. Taking a step back and establishing common terminology in the beginning can save a lot of confusion. For example, we learned that even though the data centers use a lot of the same words to describe data and processes, the differences in meaning can actually be pretty significant. A special shout out there to the word linkage, who knew that you could use that word in so many ways, we found out that you can. Finally, I wanted to highlight this piece last. Not every organization's procedural details had to be exactly the same to make this collaboration successful. I wanted to point that out because I think for people thinking about participating in an initiative like this, it can seem very daunting to reconcile all these different needs. I think there can be a fear. I know there was maybe on our side that such radical changes would need to be needed to ever be able to participate, but we just didn't find that to be true. Even though collaboratively building our approach, starting with our processes as all of the data centers were helpful, I think more importantly, we were able to always make sure that we return to the big picture and assess what we really needed to accomplish and then determine common outcomes out of that that we would need to reach and then figure out how we can use our own processes to get there and meet in those common points along the way. This is a strategy that the DASH team uses quite a lot as well, and we find it very effective, and I have to say CLSA was wonderful to work with in making these things happen. So those are some of our lessons learned. There are many more, but for now I'll hand it over to Andrew to link things up. Thank you very much. Thanks Lindsay. And so in conclusion, we want to acknowledge the CIHR and the CFI who fund the CLSA, as well as the Government of Canada, and our supportive network of provincial governments and universities that make the platform possible and clearly HDRN, without which this would not be possible. And of course, HDRN includes just a variety of provincial data centers and similar groups and federal centers as well across the country. And I think Lindsay overviewed extremely well in terms of how that process went and it was fantastic. We also want to thank the McMaster Collaborative for Health and Aging and their funder, the Ontario Sports Support Unit, who supported some critical early work in Ontario that provided a little bit of a framework to get started. So we acknowledge that that was instrumental. We have time for questions. I know there's questions in the chat. Just to note that we may not get to all questions, but all questions will be answered and sent and shared. Please do include your questions. We oftentimes only get to sort of helpful answers when we have strict scenarios that you can maybe provide. And so feel free to do that. And we'll get to those questions now. I'm seeing one already, well more than one, from Helen. And the question is time taken for researchers to gain access to linked data. Of course, an ongoing concern that it can take years to get approval to access data. And I'm sure it depends on the jurisdiction. And you anticipate same for the CLSA linked data. And so data access is a little bit different across provinces. Before I answer this specifically, just to highlight to the group, CLSA data with the unlinked data, or rather not linked to provincial repositories, is more precise, is available through the CLSA. Linked data to provincial is not available through the CLSA through the regular data access mechanism. It is available, as Carmen mentioned, if you only want single jurisdiction linked data through that jurisdiction's data center, through their existing process. And for multi-regional data through the HDRN dash process that was mentioned that facilitates access. And so Carmen overviewed the steps. And essentially it is a federated and coordinated set of steps when you're looking for multi-region linked data through dash. And so we anticipate that that could be a little bit longer than single region data. Unfortunately for the CLSA, for the researchers who want to access data, and oftentimes even for the data centers themselves, they do not always have complete control over their time processes because their processes are changing and sometimes can change according to changes in legislation and how particularly privacy legislation. It's an ongoing concern around speedy access to this resource, but it is quite a resource. And so I would just offer to say that it's worth the wait. I think we hope that these processes will continue to improve over time. So not a great answer there in terms of exact time frames because unfortunately they're not warranted or we can't warrant a particular time frame. Where can we find data flow maps? You can find data flow maps on the websites for the CLSA that was shared. That information is widely available and then in particular domains of interest there's typically always a lot published already on the CLSA. With respect to the HDRN, what data are available on the provincial side that for linkage, those are available through the provincial data centers, but also HDRN has wonderful resources around what data are available across regions, including algorithms that you can compare. Is the linked data free for graduate students? Great question. The CLSA as folks might be aware provides for graduate students and you can find this on the website in detail, no cost access. Otherwise there is a data fee and the CLSA waves that fee for where graduate students are accessing linked data for their thesis projects within provincial data centers. But the provincial data centers do not provide free access to those data for graduate students. It is typical and they do not because there are particular hosting costs and the mechanism for which if folks are not familiar data are used across for digital data centers is with a high degree of security usually on secure portals and very, very often if not exclusively facilitated by an intermediary expert data analyst that has access to the data securely. Of course these modifying change over time and of course we could see changes there. So contact your local data center or be in touch with HDRN-DASH I think is the answer there. Any thoughts from panelists on any of my responses so far? Okay there's a comment on following up on New Brunswick's experience and why they decided to request the data, who paid for the data and what's the progress of the data analysis and so I'll try to clarify and so that as part of the CLSA protocol data linkage was always expected and it is optional for participants to consent to data linkage which the vast majority have. To facilitate that then we because health services data is held under provincial jurisdiction under provincial privacy legislation therefore the CLSA data must go to the provincial centers rather than the provincial center data coming to the CLSA and so as part of HDRN's activities and CLSA's mandate that's how this relationship came to be and the good outcomes to date. Who paid for the data essentially the CLSA has a mandate to for data linkage and so it was supported instrumentally through people time across HDRN the data centers includes Kaihai and ourselves in the CLSA. What's the progress of the data analysis? The data are linked in centers where that are available so there are three jurisdictions to date as you saw more will be added as data sharing agreements conclude and data are shared some in the next few months and so you can reference the various websites to understand what data are available at any given time and the data analysis so the data are linked and they are available in those centers so they're available to researchers to do research under the rules of conducting research in provincial data centers and so those analyses will now begin and so we expect that researchers will access those data build proposals to access those data separately within the mandate of CLSA and and our support for the platform through CIHR and CFI we're considering the possibility of conducting methodological analyses across centers over time in order to provide researchers with a greater sense around the possible questions that they can answer this is an ongoing consideration so for example where some analyses might be able to understand where the CLSA cohort is at in terms of transitions across housing environments into long-term care environments and so forth that researchers can understand the representative or the let's call the penetration rate of the CLSA cohort as they evolve throughout the lifespan how we're the represented in various provincial data but we expect of course they're obviously available in provincial data that's to do with hospitalizations primary care visits medications etc Andrew I just saw some questions in the Q&A on the same topic and just to clarify for the recording and everyone the analyses will have to be done separately in each province if you're making a multi-region request so that's one point and then secondly the mechanism to access the data will depend on each province and there's some links that have been posted in the Q&A to show you which whether it's secure access a secure access environment for the researcher to do the analysis themselves or exclusively an analyst at the data center who does the analysis for you it will depend on the data center how that mechanism of getting the access to the data and how they prepare the data set for you yeah so just wanted to clarify that because there were a few questions about that yeah I think Sophie that's great there's a question on the kinds of data that could potentially be obtained from participant medical records just important to note that the available records at provincial data centers are oftentimes not like electronic medical record data people should be aware of that they're typically abstract or what we generally call administrative data which is that they're typically procured through although not exclusively sort of funding mechanisms so where the province funds a drug plan then a receipt of which of which drugs are funded for which individuals go into our pausatory or their abstract level data from discharges from hospitals those are typically available across provinces have a look at the hdrn site where you can see across jurisdictions what data sets are available like of course they're all in regular use so you can see examples of published work from those data sets quite easily and then each provincial data center on their website would also have helpful helpful resources around various data dictionaries and what information can be accessed Jennifer I might just jump in on some of the the questions in the chat so um I I want to address the question about the length of time and and just as I said in the in the answer in the q&a part of hdrn's canada's reason for being is to streamline and harmonize both data access processes across our our member organizations but also to harmonize data itself so so these these two areas we appreciate the the comment about the length of time but both these areas are are ones where there is active you know thought work engagement with sites on on how to continuously improve so I just want to reassure folks that that this is something that we are aware of and that we are working on in terms of the questions around accessing data so we there there are very good resources on our website about the requirements across the different sites but generally most sites have secure access environments and many of them are remote access if if sites do not have remote access at the moment they are working on getting remote access so basically all of our sites are moving towards remote access into secure environments and you know they're in recognition of you know the need for capacity building around advanced methods and federated analysis hdrn canada has planned with in collaboration with others a federated analysis learning series so I put that also in the chat it's on our website it's a great opportunity to learn from folks who are more expert in this area but also there's a desire to hear from people about you know where the sort of interests and needs are and and sort of maintain this learning series going forward so it'll be very much an engaging sort of learning series that will lead to more opportunities going forward so those are just some things I wanted to highlight great um andre I see we've got another couple minutes and there's one last question so perhaps you or one of the panelists can address the question from Jennifer Lawson and then I can can wrap things up yeah I'll comment briefly and if someone else wants to that's great I think what's been gained in terms of all this work um uh procedurally I think basically just the muscle memory of doing it it was like our gantuan feet and uh we proved principle that it is possible and there are many small steps and hurdles to to reach that and we were able to achieve it and we continue to be able to achieve it for me that's it maybe others have a comment concluding remarks from any of the panelists and uh there was also the last question squeaked in about um whether the Pang Canadian Genome Library will be part of of the linkage I'm not aware so we may have to follow up Andrew all right great well I see the I see some some nice general comments coming in and congratulating everyone so maybe this is a a good time to end and and congratulate everyone on a great webinar and this has been a tremendous feat for the CLSA and and all the collaborators who we've been working with on so thank you again for to all of you who presented or were behind the scenes helping answer questions we really appreciate your participation in these webinars they're they're greatly valued by the our researchers and participants