As we move into the next section and moving forward and the objectives we have for the talk, I'd like to share with you some of the interventions that we put in place in our cancer center to improve participation. The disclaimer that I will give is that I have made lots of references specifically to cancer patients and cancer clinical trials, but the disclaimer is these barriers actually apply to healthy volunteer studies, other chronic conditions. If you're doing a coronary artery disease, if you're doing hypertension, kidney disease studies, you will absolutely face the same barriers. They may show up in different percentages, they may show up when we talk about what does it look like, it might look different in your clinic or in your population, but they're there. So as we move into looking at interventions and how we develop them, how we identify them, and I will share with you some of the results of what we saw in the upcoming sections, think about the flow applying to the disease that you focus on in your studies because it does translate in spite of my references to cancer studies. On this slide, I have a diagram here because to be quite honest with you, when I started this work about five years ago, and as I've said, I came out of clinical practice, this was not a well thought out professional plan that I was a nurse and then decided I was interested in health disparities and took an academic path that led me to do this work. The interest came out of what I saw and didn't see in practice. As a person of color from Baltimore, as a new nurse on an inpatient unit, questions like, "Why is there an imbalance of the kids that we see?" You don't want to see any of kids there, but the questions absolutely came that I'm working on a 14 bed pediatric oncology unit in East Baltimore, why aren't we seeing so many African-American children, and do we get cancers in fewer numbers? Questions like that. Those questions translated to the work that I did with adult cancer patients. So when this interest started to grow, and in very organically grow for me in looking at this disparity, and I started this role, it can be quite overwhelming as it can be for any one of you when you try to figure out how to improve recruitment and retention on your studies and absolutely, when you try to make sure those recruitments in the patients that you're retaining are diverse, it can be overwhelming to try to figure out how to fix that problem because here's the newsflash, there are lots of people doing this work academically, trying to figure out how to fix it, and it's not been done yet because it is such a broad problem, and it has so many facets to it. What you have in front of you is a diagram that helped me think about the path that people take to get enrolled into our clinical trial. So on the left with the first arrow and the first bar above it that says external effort, it is the path that somebody might take before they decided to even seek care in our cancer center. After that bar on the right side, you have internal effort, and I have three steps there. I have something that identifies our cancer center and then if you're already in our cancer center, that arrow means if you're in the cancer center receiving treatment, do you end up on a clinical trial? What I'll overlay here are those barriers that we talked about; fear and mistrust, fear of medicine or researchers, lack of insurance, health literacy, they're all here and I overlay that so that you can see it along with this path because what it means is that these barriers are all potential barriers all along this path. What is a point of interest in that we have to really be able to understand, is that they look very different depending on where you are in this path. So as an example, fear and mistrust is one. I have it listed here to say fear and mistrust of the institution or medicine or research in general. But to just broadly think about fear and mistrust, what I mean about them looking different depending on where you are in the path, on that left side, that street to center arrow, if in fact fear or mistrust is an issue for you, and you've not decided that you want to even receive care at Johns Hopkins, and the cancer center anywhere here, then your issues around fear and mistrust will look and sound different than somebody who decided they want care here. They're just not sure on that right side if the care they want to get here is on a clinical trial. How I go about trying to address those two very different iterations of fear and mistrust will drive the interventions that we do, what makes up that intervention, and how we deliver it. What I'll do is show you one component of where we focused. I will tell you some effort has to be made in parallel on both sides, that street to center side and the center to enrollment. But you can't fix everything at once, you can't understand all of it at once unless you're looking at it not for whole portfolio of studies in a cancer center or in a department, but a particular, maybe researchers portfolio of studies. So in this green box, this box around the internal effort side, is where most of my effort for the previous several years has been focused. On the next slide, so focus on that internal effort. Again, as a reminder, internal effort for me here means that this is a group of patients that have already decided that they want to receive care here. They aren't Cancer Center patients. But to try to understand what's the difference between those folks that are receiving care here, but not ending up on a clinical trial. So what you have in front of you is stages of clinical trial enrollment. They were stages developed by a colleague, Norma Kanarek. It outlines for us the steps that a person takes between being our patient and being enrolled in a clinical trial. So on the top row in those boxes, we have the stages of clinical trial enrollment from being a new patient, whether or not we had a trial available. Third one is the patient eligible. Fourth is the physician triage. So that really is the physician's decision of whether or not they think the trial is appropriate. Then moving on to did they discuss the trial? Was the patient interested? Did the patient consent to the study? Then ultimately, did they enroll? On the second row in the circles that are below those are all the potential places that someone could fall off of that path. So that means in that first circle that, in fact, we didn't have a trial available for a particular patient. Maybe that was because of their stage of disease or their performance status, meaning, were they healthy enough to endure the treatment on a particular trial? Moving along with those circles, were they not eligible? Did the physician decide and it could be for many reasons that it wasn't an appropriate trial for the patient. Sometimes that is because that particular treatment might not be one they deem as appropriate at this point in that patient's care, they may have decided that the order of how they receive certain treatments should be different. That may be now isn't the time for this particular clinical trial, but they should receive standard of care and then a certain clinical trial or surgery first and then revisit this clinical trial later. Then if a physician thought the trial might be appropriate, but for some other reason decided not to discuss it. If they did discuss it and the patient said, I'm not interested in a treatment on a clinical trial, they could fall out there. Then if a patient expressed interest to the physician during their visit, but then when they heard from the research coordinator [inaudible] some of the details of the study may be the number of visits or side effects that are known, they decided that they did not want to pursue enrollment and they ultimately didn't sign the consent. For the last circle, if we've gotten through the other potential places to fall out, we had a trial. The patient was available. The physician thought it was appropriate in terms of clinical treatment. They discussed it, the patient was interested, the consent is signed and now we're doing some of the screening and we're doing all of the screening that is required. The patient did not meet the eligibility, so they did not enroll for that reason. So to look at this path, it allows a little bit of an ability to try to figure out where we are in terms of our workflow and what we're doing. When Dr. Kanarek developed the stages of clinical trial enrollment, it was in parallel with a retrospective medical record review to find all of these points and figure out who fell out and by race and in percentages or particular cancer types. When I looked at the same stages of enrollment, it made me think of who's doing what at this point. So as an example, top row, third box is patient eligibility. We didn't routinely, as part of standard care, screen patients for our clinical trials. There was one particular group that did, but en mass the others did not. So I knew that we wouldn't generally look very closely at patient eligibility before the physician saw the patient. The physician might introduce a study, so that trial discussion after physician triage would take place. But the real details of what a patient might have to do and really reviewing the consent in very close detail would come from the study coordinator or the research nurse. So that patient interests point could be more significant than she may have been able to glean from a medical record review because I knew where it took place in terms of workflow. So having looked at the path that a participant could take to end up on a trial and the places they could fall out, I'll share with you one project that we did to try to gain some insight into portions of that path. The project that I'll share with you is called Trial Candidates, and it was to answer questions based on what we had about those who do enroll we couldn't answer. So we were interested in finding out who we were talking to about clinical trials and what they were saying to us. To look at those individually, clinical trial candidates, again, with more questions there. When are potential participants deemed candidates for our studies? Who were the study candidates themselves in terms of demographics? Why don't candidates enroll? So if you didn't make it through that path, again here, now with the circles where you could fall out, if you didn't end up on a study, why not? Where did you fall out? So what we found in candidate data, and this is a database that is actually housed in a system that we were already using to keep track of research documents and participants and how they progressed through trials. You may have a similar system or in a smaller research setting, you might be doing this with Excel spreadsheets. But to start this project, we required that we establish a different baseline understanding, and that CRMS noted here is our clinical research management system. When potential trial candidates got entered into that system, could vary from team to team. What we knew for sure is if you consented a participant, they went in. There were other teams who found this system helpful in terms of tracking workflow. So they might enter somebody that they talk to about a clinical trial and try to keep track of when they submitted insurance clearance or how long it might take in the process of that first interaction until someone ultimately consented, so that the research team could have some estimate of the amount of time that might have to be invested into each recruitment or ultimately each consent. So the second one, we maximize functionality that was there. So you can you maximize entries on your spreadsheets or with the system you're already using? Now three years forward, that database has 3,200 patients in it along with demographic information of who they are and the reasons they didn't enroll. What we did to try to make this as simple as possible was tell the research teams that you are required to enter candidate information for any therapeutic trial all candidates need to be entered. That is with any and all demographic information you have, and I'll clarify there that sometimes research teams, a research nurse, or a coordinator might receive a phone call from someone that isn't a patient of ours yet, and they found out about the trial. They may or may not end up coming here to pursue the trial, but if you are talking to that person, you may not be able to get demographic information that would be a weird flow to talk to them and then ask, "Well, can you tell me your race and ethnicity?" Try to collect this information. So as much demographic information as is available if their patients already in the institution, we have that, and what we'd like to know is if they ultimately consented and went on this study and if they didn't, why not? But the baseline definition for candidate was if you talk to somebody for five minutes or more about your therapeutic trial, put them in as a candidate, and let us track why they didn't go on. So some of the reasons that we saw that people went from being candidates and ultimately not enrolling is that they weren't interested. The coordinators and the nurses have a free text space to just tell us quickly a little bit more detail about reasons such as not interested, they come from drop-down menus to say it was too far from home, they were concerned about privacy, they preferred standard of care treatment, or they thought that participation might be too time consuming in number of visits or length of visits. But when you look at this list and you think back to what we just talked about, those barrier names like access, so is too far from home, one that we can attribute to and access issue that has to do with transportation. If you are a potential candidate for study and you have privacy concerns, is that an education gap and awareness gap about how research works and how you're protected that we could address. That you prefer standard of care. Again, is this a reason-based and fear and mistrust or an education gap, and then finally, too time consuming, too many visits. Is that an access issue that we can relate to participant requirements? So on this slide, I'm showing a bar graph of that not interested reason along with two others. Other where research teams can free text details of why a candidate did not enroll and not eligible. In the bars here, the darker red African-Americans in not interested made up 18 percent of those participants that said they weren't interested. All minorities, 22 percent, and females were 55 percent of those who said that they were not interested. The other worth pointing out, and I won't go over the other reason in the middle with those bars because those can vary quite a bit and we'll get back to them, but not eligible, African-Americans were 17 percent of those, 20 percent were all minorities, and 55 percent of those were women. Those not eligibles could be lots of reasons. Where they diagnosed so late that their performance status, their health status overall made them not eligible? Did they have other chronic conditions, comorbid conditions? So looking in a little bit more detail on the right of how the breakdown of some of those free text reasons showed in our database, for not interested, some of those free texts reason showed up as preferred standard of care, they were concerned about randomization that was part of the study, or they were not interested in research in general. Other came with details of financial reasons, logistic constraints that there were too many visits or the distance from home for them to come to those visits. Finally, some of the not eligible reasons in the last box on the right, that comorbid conditions was the basis for their ineligibility, a declining performance status also shown. So when you look at first on the left, the percentages as they show up in the reasons that are given in some free text and drop-down menus and you try to translate those, what you're able to do is potentially answer those reasons given with interventions that might prevent someone from saying no for those reasons. So on the slide, take a look at the first box on the right with the reasons given, the preference for standard of care treatment, concerns about randomization or not being interested in research. We were able to develop, as you can see on the left, an answer to that clinical trial education information, video, and printed material that specifically address those concerns around participation. In response to financial reasons, too many visits, and the distance from home, our intervention doesn't potentially answer all the problems that may be related for someone to finance and logistic constraints. But when we thought about what we could potentially do that could answer some of them that was actually in our control is develop a transportation study. In that study, we paid for because it is not standard for all studies to cover parking and transportation. For those that did not have funding in their budgets to offer that, we offered parking or transportation from the point that a person was a candidate for a study. So that means that their parking or taxi transportation would be offered for them to come to visits required for screening. At that point, that actually means that a person was offered a clinical trial. They may have consented, they may not have consented. They're thinking about it, they make some visits, they want to talk to the research nurse, they want to talk to their doctor a little bit more, they decide to consent and then there are several visits required, may be for tests that need to be done to determine eligibility, several visits that could bring them back to the hospital. In the transportation study, we pay for the parking and the transportation related to those visits. If a person decides after doing that, giving it some thought, or if they actually don't meet eligibility, then there's no harm there, no foul. We've covered the parking, giving you the time you may have needed to be able to consider fully whether or not participation was right for you or find out if you were eligible and removed the financial burden of getting to those visits by having you participate in a study that let us pay for the parking for you to be able to do that. The final bullet is one that we hope to pursue more and is showing up more and more in the literature. Those folks that didn't ultimately go on because of other conditions, other co-morbid conditions, hypertension, diabetes, kidney disease, or that they had a declining performance status, that we want to look more closely at what those reasons are in detail and who those patients are. Is there a certain sub-population that has diabetes or kidney disease and those thresholds for eligibility are weeding them out and making that trial not available to them? For declining performance status, can we have a better partnership with community physicians to encourage earlier referral so that we're not seeing people so late that they're not eligible for studies that we might have available. So on this next slide, I'll highlight here some of that clinical trial education material and tell you a little bit more about how that came about for us and what we've done with it. When we looked at some of those candidate reasons, fear over randomization or preference for standard of care, those do all ring of a knowledge deficit or a lack of awareness about how clinical research works. So what we did was put together a group of community members who may have been cancer patients themselves, not necessarily receiving treatment from us caregivers or loved ones of those that did and they themselves were not cancer patients, former cancer patients from our center to have advisory group together, to talk to them about what either their personal experience was, what their personal thoughts are, reservations about clinical trials, even to the detail of which words are scary. What is it you think you know about clinical trials? But to talk to them from the very beginning in a very collaborative way, tell them that we would like to address, even though we knew from the beginning we wouldn't be presenting information that has never been presented any place else about how clinical trials work or how participants are protected. But could we deliver that information in an innovative way that address those concerns in a way that we've not seen before. What was born out of that effort was a series of three videos: title, power, and choices. In those three videos, we have one piece that is quite education-based in really explaining the phases of research, and randomization, and what it means, and how you might go about as a potential participant deciding if it's right for you. To a second video that highlights a discussion between patients and their family members, their loved ones, about how they actually made the decision. It's a very frank discussion even highlighting a mother and her daughter, who's the patient, an adult patient, but how they didn't agree on what the right decision might be, that the patient wanted to be part of a clinical trial. She saw it as excess to a therapy that might be lifesaving or life-extending for her when her mother wanted those things for her, but was really quite fearful of her receiving treatment in a clinical trial. Finally, the third video in that series is one that highlights researchers, to have them talk about what it means to them to be involved in clinical research and how they go about developing it, and what it means to them to have participants enrolled in those studies. On the lecture page, I'll have links there for you so that you can see those three videos in their entirety. Back to the stages of clinical trial enrollment so we can continue to make that a touch point to see where the candidate data helps us address the stages. We were able to with candidate data, get some insight into whether or not physicians thought trials that we had in our portfolio were appropriate if they discuss them and then track the reasons why patients did not enroll in them.
