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Herbal Remedies

Natural Herbal Remedies

Alternative Medicine Questionnaire

Dana E Rollison PhD MyMoffitt Portal Giving Data Back to Participants

Good afternoon.I'm sheri schully from the epidemiology and genomics research program here at nci.I would like to thank you for participating in our first webinar in transforming epidemiology through advanced methods, or team webinar series.Today, we have the pleasure of having Dana rollison describe the mymoffitt portal, how patients receive health information, and how it engages patients in epidemiology research through the electronic patient questionnaire, or the epq. Rollison is vice president, chief health information officer and associate member in the department of cancer epidemiology at moffitt cancer center.

In this position, she provides executive vision and strategic leadership to develop leadingedge information resources using moffitt's enterprisewide data warehouse, the health and research informatics platform.She also oversees departments responsible for acquiring, curating, and provisioning data in support of research, operational efficiency, and clinical guidelines development.Today's webinar will focus on moffitt's electronic patient questionnaire, which is used to capture patient reported data and incorporate into electronic health record and research databases.At the end of Rollison's presentation, we will open up the lines for questions.At that time, if you would like to ask a question, please press.

Star 1 and state your name and affiliation before asking your question.The operator will unmute lines on a onebyone basis as callers are queued up.All other lines will remain muted to ensure that there are no disturbances.With that, i'd like to turn it over to Rollison for the presentation.Thank you sheri.It's my pleasure to be speaking as part of the team seminar series.And i look forward to a dialogue after the slide presentation.So, as you alluded to, we're going to be talking about.

Moffitt's electronic patient questionnaire, or what we refer to as the epq.And you'll see that this epq is involved in capturing data for both research and clinical purposes.So, i'm just going to begin by giving a background and rationale as to why we created the epq in the first place, the design of the epq, and the approach that we're utilizing to actually implement the epq.We'll do a little bit of a deep dive into the content of the epq, how we're operationalizing it at moffitt, and how the.

Completion statistics paint the picture of uptake across the clinics.And then we'll go into how we're using epq data for research, particularly for epidemiologic studies and the future plans for the epq.So, to begin with the background and rationale.You need to understand a little bit about the moffitt clinics.We have a diseasecentric approach, so we have clinical programs that are focused on patients with a particular type of cancer.So, for example, the thoracic program focuses on lung cancers, cutaneous, etc., and within these programs we have a multidisciplinary team.

So they include the oncologist, the surgeons, the radiation oncologist, the pathologist, etc.And so it's around this diseasecentric model that the epq was designed.In part because each of the clinics, and historically speaking, had their own clinical intake form that was given to patients.And these questions varied across the clinic, such that you couldn't collapse data across cancer types.They were also patientfriendly but not necessarily researchfriendly.And finally, they were paper based.So while they were accessible in the electronic medical record, or emr, by viewing it through pdf, you couldn't query.

On the data or extract it for analysis.So based on this landscape, we employed a strategy to collect patientreported data electronically in a standardized way across multiple clinics, so that we could use those data for both clinical care as well as research.So the design of the epq is that all questions must have clinical relevance.And this is because we're asking all patients to complete the epq, regardless of whether they consent to a research study.So their new patients are asked to complete this form via the patient portal.

All questions must have clinical relevance.When there were gold standard questions available, like smoking let's say, we used the gold standard questions from the literature so that they could be used in research.And because these data are being collected for clinical purposes, it's pushed to the emr in what we call the md summary report.So this is something that the clinician can view in the emr, but also we have information from the epq flowing into our data warehouse so that we can access it for research.And i mentioned we have multiple diseasebased clinics, so we.

Have a core set of questions that every patient receives that are relevant to all cancer patients.And then we provide the opportunity to each diseasespecific clinic to design their own supplements.And that would include questions that are specific to patients with that type of cancer.In terms of content, we've broken it down here into what's involved in those core modules versus the diseasespecific supplements.So you can see in the core, we have many questions or subject domains related to what you would typically see in a patient clinical intake form.

So demographics, your personal history of cancer, and your personal medical history, as well as review of systems and current symptoms.But then we also have a variety of epidemiologic risk factors that can not only be related to treatments and treatment efficacy but also to risk of second cancers.So, included in those risk factor modules we have women's reproductive history, we have sunlight exposure, tobacco use, physical activity, diet.We also have an extensive quality of life section, which is modeled after the ss12.And, of course, we have family history of cancer.

So all of these data are collected across all of the new patients.In the diseasespecific supplements you can see the ones that are live listed here.And we continue to expand upon them.But there are diseasespecific questions.So, for example, in a thoracic supplement there are extensive questions on environmental tobacco smoke exposure, asbestos exposure, things related to lung cancer.In the cutaneous module, you can imagine there are specifics on sunlight exposure, mold removal, and those types of questions.And then we have qualityoflifespecific questions that are specific to the cancer type.

So, for example, prostate cancer, treatments that the quality of life issues that are driven by the treatment for prostate cancer, are included in those diseasespecific supplements.The questionnaire is quite long, as a result.And what you're seeing here are the numbers of questions that a patient may be asked to answer depending on their skip patterns.So, for example, if a patient says they have ever smoked 100 cigarettes in their lifetime, they're of course presented with the followup questions related to smoking in terms of how many years, number of packs, etc., whereas if they've never smoked.

They skip out of those questions.So you can see the ranges for the minimum number to the maximum number of questions a male or female patient could be presented with, across the different versions.So npqv2 is the version that we had implemented prior to 2012 epqv3 is the one that's currently in place and has been since january of 2012.And then you can see the various diseasespecific modules that add questions to the core.Pccv3, that first one, is a very abbreviated, as you can see by the question counts version of the epq that was rolled out.

Specifically to patients consenting for our total cancer care cohort study at institutions outside of moffitt.So it was a very limited number of data points.But for most of the patients being treated at moffitt, you can see that there are quite a number of questions that they're answering.And it typically takes patients anywhere between 45 minutes to an hour to complete the questionnaire.So how do we actually operationalize this at moffitt well, a patient makes an appointment at moffitt, and this could be in the screening center or in.

Any of our outpatient clinics.They receive instructions via email to log in to the patient portal and to complete their new patient questionnaire.If they have not completed the questionnaire at home via the patient portal when they come into the clinic, they're asked to complete it on a tablet right there in the clinic, and then the data flow into the emr in the form of an md summary report that i described earlier, as well as discrete responses to each question flowing into our data warehouse for access by researchers.

So i'm just going to give you a few screenshots to show you the patient portal and what this looks like in action.So here's the moffitt patient portal.And you can see down here is the login to the patient portal.And here they have the ability to log in as an existing patient or to create a new account.It's very userfriendly.And once you're in the portal, you can do a variety of things as a patient.You can view your clinical results in terms of laboratory tests that were conducted within moffitt, you can look at a.

Summary of your medical record, including a summary of your disease, your stage of disease, and your treatment.And then you can also manage your appointments.And this is what's particularly useful for patients to track, when they're coming in, to which clinic, and what they need to do to prepare for those appointments.And you can see under what to expect that the link to the questionnaire is there.So patients would double click on that and then they would be prompted to fill out the epq.And you can see in the email that goes out to them with the.

Instructions, it mentions the epq, that you must complete it online, and if you complete it online you can arrive 30 minutes prior to your appointment.If you've not completed it online, they ask you to arrive 90 minutes to your appointment.Again that reflects the amount of time it takes to actually complete the questionnaire.So in terms of the usage or utilization of the questionnaire, you can see that at 100 percent of patients actually as of now, request an account for the patient portal.Now this is surprising, given that we do have a large.

Percentage of seniors in our patients, so people who you think maybe might not be uptodate on all of the technology.But it's really showing through the uptake statistics that people are preferring to manage their appointments through the portal, even if they've got the assistance of maybe a family member to access the internet.So we see a great uptake in the patient portal itself.And it's also reflected in the total logins per month.So you can see that not only are patients registering for the portal accounts, but they're actually logging back in.

Periodically to again manage their appointments and look at their records.So what does the md summary report look like we looked at the portal, we saw how patients can enter and input their data, and then how does it look in the emr and here's a screenshot of the patient questionnaire for it looks like gyn patients.And you can see how the individual questions are summarized in a format that's fairly friendly to the provider.So it goes into all of the different personal histories, social history.It aligns with the modules of the questionnaire.

And we can look at the second page of this.This is where you have unint.Systems, the psychosocial and quality of life.So again this is a pdf file that's accessible to all of the providers within the context of the emr.And just to give you a feel for if you were to deploy this questionnaire, genovo ph., in one of your institutions, the variety of team members that are required to do this.And so this slide's fairly busy, it's not meant to go through each detail per se but to give you a feel for the various steps.

In the process and the teams involved.So, for example, once we went live, every disease program wanted their own spoke, we needed a prioritization process to determine which program got a spoke next.So that's one level of just basic governance that has to be in place.If the individual programs have an existing questionnaire, or even maybe an existing database, there's a data review and profiling step to understand, well, what types of data do you want to capture and if another program is already capturing those data, how are they asking the patients about that, because.

We want to utilize the same questions as much as possible to enable the combination of data across the programs.And then there's the content design, in terms of how you ask the question but also where you integrate those questions into the core.So with the smoking example, if you're going to ask about how deeply did you inhale and other aspects of smoking behavior in the thoracic supplement that you don't ask in the core, you want to make sure that those questions are integrated into the order of questions within the core, so it's not this.

Standalone supplement that is awkward for the patients to complete.So there is actually a design component in the ordering of questions.And then the md summary report has to be designed so that the physicians can easily use it.What information is critical for them how would they like it displayed and then of course we have various it teams reviewing the coding to bring the data into the emr as well as through to the data warehouse.So it's a fairly complex process, but in order for both the clinicians and the researchers to leverage the.

Data, this is the type of effort that's required.So what do the completion statistics look like we already talked about the fact that most people log in for a moffitt portal account.But then whether or not they actually answer the questionnaire is the set of statistics here.And in order to understand that, we have to look at scheduling types to look at our denominator.And it's interesting, our epidemiologists at moffitt who are frequent users of the epq data want to understand well, what percentage of patients complete the questionnaire, and.

I'm interested in maybe lung cancer patients.Well, the first question you have to ask is how many of those patients actually were invited to take the questionnaire.And since the questionnaire is triggered by our scheduling system, it's those patients who have a new patient appointment type that are actually asked to complete the questionnaire.So some of the challenges with using the data is educating the faculty as to how these systems are deployed administratively so that they can better understand the denominators in some of these completion rates.

So here you can see for january 2012 to date we have various numbers of patients who had new patient appointment types according to our scheduling system, who were then asked to complete the survey, and you can see the different types here.So epq would be the core, and that would be given to all patients unless they were coming into the cutaneous gu or thoracic program, in which case they were invited to complete those specific questionnaires.And so here you can see of those who had mt appointments and were.

Invited to participate in the epq the percentages that actually did so here.So we're running an overall rate of about 65 percent, although it does vary from clinic to clinic.You can see that we have 25,000 of these epqs completed, so that's a substantial number for those of us who want to use them for research.We also have an additional 22,000 records from the previous version, npv2, and several of those questions are common between v3 and v2.So in fact your sample size could be closer to 40,000,.

Depending on which questions you're interested in.If we look at the data another way, by primary site, you can see also that the completion rates for epq are quite high, ranging from a little under 60 percent for the head and neck clinic to 80 percent for the breast clinic.And the factors that go into this are varied.So, for example, head and neck, one of the challenges has been just their geographic location within the cancer center they have poor connectivity compared to the other clinics and have.

Been frustrated with using the tablets within clinics.So we've worked on improving their connectivity to increase the completion rates.Other times, it's just enforcing the schedulers or the people registering the patients to actually prompt the patients to complete it.So again, tackling the implementation side, it's a variety of it as well as governance approaches to improving the completion rates.But they're fairly high and averaging about 70 percent.So finally we come to accessing epq data for research.And you can imagine a variety of questions could be asked.

The way we access the data is through our data warehouse, so i mentioned that the discrete responses come through the software, in which the patient's completing the questionnaire, and link into our data warehouse.Our data warehouse contains information from a variety of source systems, including our cancer registry, our bio banking system that has information on tumor tissues and blood samples collected as part of our total cancer care protocol, as well as much information from our electronic health record.So all of the epq data are actually linked to the data in.

These other systems, which of course provides added value.And in order for faculty or staff to obtain counts of patients who have different demographic or clinical care adristics ph.And for whom the epq data are available, they can actually query the data warehouse directly.And here i have a screenshot of the bi tool that's sitting on top of our data warehouse, which we call transmed ph., that is the company that produces this particular software.But you're looking at the cohort explorer feature of the software that allows faculty to go into the system, look through a.

Variety of folders listed by subject area and actually find counts of patients who fit certain criteria.So in this screenshot, i actually highlighted the question what is your relationship to the patient , because it brings up another aspect of the epq that i think is important for research.Most of the time the patient completes the questionnaire him or herself.But we do prompt the patient to answer that question, are you the patient or is someone else completing this questionnaire for the patient and if they indicate that they are not the patient, then.

They're asked well, what relationship do you have to the patient and you can see the distribution of responses here.So among those questionnaires that were completed by someone other than the patient, most of them were the patient's spouse or patient's child and then occasionally a friend or parent.So this is important of course for research because some of the selfreported data you may want to parse out by whether the patient selfreported it or a surrogate to the patients reported it on the patient's behalf.And, of course, this information is available just like any other.

Question would be available through the warehouse.So if you actually want a dataset, you need to go through the department that we've created to provide data.And that's called the department of information and shared services.What you saw with the screenshot of the data warehouse is all deidentified information.And that's how we're able to provide broad access to investigators who want to obtain counts of patients for grants.But once they're ready to actually obtain patientlevel data to import into their statistical software package of choice, they have to go through a department that is.

Certified to understand when it's appropriate to release data or not, based on regulatory approvals.And so we've established that department here at moffitt.So for actual examples, and i've framed it in terms of epidemiologic study design, given today's audience, clearly the first application would be in crosssectional studies.So because we have a lot of baseline data on all of these new patients, we can use the patient's selfreported data in epq to crossvalidate with some of the emr data that we're collecting.So, for example, comorbidities or even performance status.

And here i have an example of a research question.We're interested in understanding whether patientreported health status on the epq correlates with physiciandocumented performance status in the emr.And we've recently deployed a discrete ecog ph.Or cornosky ph.Performance field within the emr that's a required field.So we're interested to see how well that correlates with what the patient's telling us on the epq.And so both of these sets of data are available in the hri, our data warehouse.And so here's the screen shot for what's the general health.

Question as an example looks like.So we have the ss12 version one included into epq v3.And this particular question is one of those questions in the ss12, asks in general how would you say your health is.And this is a distribution of responses for that particular question.What i've done here is simply summarized it in a pie chart so you can see there's a pretty good distribution of answers to this particular question.And this is based on data from a little less than 48,000 patients.Now in parallel within the data warehouse,.

We also have emr data.And so what you're seeing here is a screenshot of the distribution of responses to the cornosky performance status field coming directly from the physician notes.And so you can see the various values for cornosky performance status.And this is the distribution in pie chart form.So again you can see a pretty good distribution here.And this is based on a little less, ',000 patients, only because this field happened to go live in the emr about 6 months after the epq v3 was rolled out.

So you can still see that among ',000 patients, you have quite a number of observations to look at the correlation between patient selfreported health and their performance status in the emr.I should have prefaced this by saying that many of these examples have not actually been fully analyzed and published yet because again we're accumulating data it's only been since 2012, so these are analyses that are underway but aren't quite ready for prime time in terms of results.I did want to show you though examples of what we're doing.

With the data just so that you could get a feel for the value of collecting this type of information.So this is another research question where we asked what is the agreement between patient selfreported history of a particular comorbidity, in this case multiple sclerosis, on the epq versus our icd9 diagnosis codes from our emr and billing system so this is important not just for research but also a variety of administrative applications of using comorbidities and needing to understand what is the completeness of our coding of comorbidities, what is the completeness of the epq data,.

So we can compare these to again within the context of the data warehouse.And this is just a screenshot of how it can be queried on icd9 codes to find ms.And then this is the question from the epq when it asks about your personal medical history and those that indicated they had ms.And within the user interface for the data warehouse you can actually look at intersections of patient populations.And here are the results.And again i did this within a couple minutes last week to get.

These data, so the accessibility is phenomenal.But it does require a deeper dive.So, for example, in this venn diagram, we have 62 patients who reported ms on the epq and for whom an icd9 diagnosis code also indicated ms.So it's a safe bet that those 62 actually had ms.Now the other ones who either selfreported and weren't coded for it or who were coded for it and didn't selfreport, that would require a little bit more analysis to understand what's going on there, for example, the billing codes go back further.

Than the epq data were collected, so of course you'd want to filter on patients for whom data from both sources were available to look at agreement.But again this was conceptual so that you can see the power of using selfreported data in conjunction with data from the emr billing to verify some of these clinical data.So that's an example of crosssectional studies.And you could also envision case control or casecase studies.I mentioned we have a large screening population, so you could actually essentially match controls from the screening.

Population on things like age and sex, and then look at the prevalence of particular risk factors according to the epq among those screening patients and cancer patients, or just look across cancer types and sort of a casecase design and see what are the prevalence of various risk factors across cancer types, to see or to derive hypotheses around novel risk factors.This is a big data approach.So clearly it wouldn't be a welldesigned case control study with a unint.Hypothesis, but since you have all of the data.

On various risk factors and particularly cancers that may be rare or that no one studied before, looking at the relative prevalence of these across thousands of cancer patients is an interesting way to generate hypotheses that one can then follow up on.And so finally we have cohort studies.And this is i think what we're most excited about and probably what we haven't quite realized the potential of fully yet, just because we haven't had a whole lot of followup time elapse since we've rolled out the epq.But clearly looking at baseline factors that are captured on the.

Epq, in association with disease outcomes and survival, including factors that could affect the treatment effectiveness as well as quality of life.And so one example of this would be we have the complete ipac, physical activity module, so one could look at the role of physical activity in both treatment efficacy as well as quality of life.And we have investigators within our health outcomes and behavior group who are interested in doing that.The next series of slides are some data we've presented at the frontiers meeting this past fall that's fairly provocative, and.

It's asking the question is selfreported uv radiation exposure at baseline associated with overall survival and again it's invoking the vitamin d hypothesis.But we thought let's just see what we have with epq data since there are so many patients.And this is fairly again straightforward to do within the context of the data warehouse.We were leveraging, here's one example, have you used a sun bed, sun lamp, or tanning bed more than 10 times in your life and so we're querying on patients who've completed that question.And then further looking at lung cancer patients, this is data.

Coming from the cancer registry, and then seeing who are alive or have died since the completion of the epq.So right here all in the context of one data warehouse we have exposure, we have disease, and we have survival.And so when we pulled these data for analysis you can see here we felt, okay, we have good sample size, so again this is a nice way of the investigators being able to assess feasibility of a particular study.These are the filters used, you can see here from the previous.

Slide the bread crumb is what we call it, we filter for some whether they answered the question and then whether they had lung cancer, and then this is the number who are alive versus have died.And so there was an adequate sample size to look at this.And you can see this is actually the kaplanmeier curve showing overall survival among lung cancer patients as a function of whether they reported sun bed use at baseline or not.And so we observed a difference here when we actually conducted.

A cox proportional hazards ph.Model adjusting for age of diagnosis.We saw significantly inverse associations for sun bed use at baseline in overall survival for lung cancer overall and particularly for those who were distant stage of diagnosis.So we thought this was interesting.Lung did seem to be the most strong association observed.We looked at other cancer sites as well.So this would be not a definitive study per se but certainly something that perhaps could require a followup study, where you're collecting data specifically around the vitamin d hypothesis.

But again, this is leveraging big data to look at these hypothesis generating type questions.So that's the end of the accessing epq data for research topic.And i just wanted to end on what our future plans are with this slide.We would like to create derived variables, so all of those screenshots i showed you were specific to individual questions.But of course there's added value in coming up with the summary scores that those questions can create.So, for example, the physical activity module or the ipac as.

Well as ss12, things like pack years that are derived from, of course, total number of years smoked and cigarettes per day.If we could create those derived variables within the warehouse, i think it would provide an easier usability for the faculty.We're working on the next version of the epq, which is going to include a comprehensive medication history.The idea there is that people can access their medicine cabinets from their homes, look at all of their medications, enter them at their own pace, and that this will not only.

Improve the reporting of medication history, but also have it prepopulate that particular module as the ehr, so it cuts down on the provider's time of entering these data all over again.So they can just look at the screen and say, okay, great, mr.Jones you reported you're taking x, y, and z, is this correct and then simply validate it with the patients.We're going to continue to build out diseasespecific spokes.And you saw we had quite a few up and running, but we'd like to add more, such as unint., living hematology, etc.

And then finally, and this is i think, it's a big goal but it's a critical one, and that is to incorporate followup questionnaires into the clinical setting.We actually deployed a followup epq to try to track some changes in some health behaviors over time among cancer patients, but we didn't have very good response rates, if you will, to that questionnaire because it wasn't tied to patients coming back to an appointment at the clinic.So if we can integrate those followup questionnaires into the followup appointments, like we did with the new patient.

Appointments, i think it will improve the participation or completion rates as well as add clinical utility to the information that we're collecting.And so that rounds out our future plans, and i'd just like to end on acknowledgements.It's my pleasure to speak on this topic to such a wide audience, but really this is the work of so many people around the institution, including Tom sellers ph., who's our center director and this was partly his vision was the epq, and Paul jacobson ph.Chairs our steering committee.

We have several faculty who provide input on an ongoing basis to the contents.Of course all the clinical programs are involved in the creation and usage of these data within the emr.And there are several it departments as well as datarelated departments that have been involved in various aspects of implementation.So with that i will end and look forward to the question portion of our webinar.Great.Thank you so much Rollison.I think this was an excellent start to our discussion of platforms that can help advance cancer epidemiology research.

So at this time, we're going to open it up for questions.As a reminder, please press star one to be placed in the queue to ask your question live.When it's your turn to ask a question, you'll be prompted by the operator so you'll know that you're on.Please introduce yourself before asking the question because we don't necessarily know who's asking the question.And we ask that you limit yourself to only one question and then get back in the line, back in the queue.So at this time, press star one if you have a question and i'll.

Actually start out by asking a question while we get some people in line.So dana, can you tell me if there's a data cleaning step between the patient entry and the data warehouse or do you leave that up to the end researchers to do the data cleaning well, there's some data checks, data quality checks, built into the software that the patient's entering data into already.So, for example, all of the skip patterns are built into the system such that they couldn't answer a question that wasn't consistent with the skip pattern.

We also have ranges programmed in there so if they were to enter an age, obviously we have an upper limit to the number that they can enter.So we try to employ as many data quality strategies at the front end.But in terms of creating dry fields or other data cleaning activities, that's really left up to the investigator, just because of the sheer volume of data that we're capturing.It's just not costeffective to do that at the warehouse level.That's really where the individual investigator steps in once they receive their data set.

Okay, great.And i don't know if the operator has anyone on the line but we have.We do.Okay.Go ahead and please introduce yourself.Pause caller your line is open.Pause please introduce yourself and ask your question.Pause again, caller your line is now open.Pause maybe we should move onto the next person.Caller are you there pause i thought i heard someone say hello.I'm so sorry, there's some glitch with my phone.Dana i just want to say thank you so much.My name is unint.From unint.

That was really wonderful.And i'm really interested to know whether or not access to the data is open to everyone who might be interested or only just for staff and faculty at moffitt.Well, i think it's available for people who want to collaborate with investigators at moffitt.So typically our model with all of the data really that we're capturing as part of the total cancer care initiative has been if there's an outside investigator who has a particular research interest, that question of interest that can be answered by our data, we try to maybe pair them up with.

A faculty member who has a similar interest or a complementary interest and who could be a collaborator, or a coinvestigator if you will, to champion that protocol through our own regulatory processes and governance processes here at moffitt.So i guess the answer is yes, if you can find a collaborator at moffitt.More broadly speaking, we are part of an information exchange with ohio state and the vision there is that data, some of the epq data will be available through that information exchange as well.And that's kind of far in the future though.

Thank you.Thank you.Our next question yes, we'll take our next question.Hi, yes, this is gina way ph.I'm with my colleagues here at nhlbi epi branch ph.The question, and i'm sorry we joined like maybe five minutes late, so i don't know if you've already answered this, two questions related to consent and irb.So are the participants consented at the beginning to allow the data to be used for research, and also sort of what kind of irb restrictions are there, or do you have to supply.

Etc., when you want to use the data for research purposes thank you.Sure.Great question.I touched on it a little bit in the beginning.I'm happy to review it, because it is sort of a unique, i guess, application.Because the epq is their clinical intake form, so just as you would go to a 's office and be handed a form, which is really i mentioned in the sort of the background slide where we were before the epq.Patients would come into the clinics and be asked to complete.

A paperbased form that was scanned as a pdf image into the chart and wasn't very useful for obviously querying the data.So we made that electronic, so it's their patient intake form.Because it is a patient intake form for new patients that populates the electronic medical record, we don't need consent to gather that information.And all of the questions in the epq can be tied to clinical relevance, either something pertinent to their current disease or information we're collecting that could affect their treatment effectiveness andor their risk of secondary.

Malignancies, so that we could counsel them on risk reduction behaviors.And so all of those data are collected primarily for clinical purposes.Just like you could use emr data in a research study with a waiver of informed consent, you can use the epq data in research studies with a waiver of informed consent as approved by the irb.So any time an investigator wants to use epq data or any other data from the medical record for research, they would write a protocol and submit it to the irb and apply for.

A waiver of informed consent.So that is the way in which one can access the epq data for research.Thank you.Pause okay, do we have our next question there are no additional questions from the phone line at this time.We actually have one online from danielle carack ph.Are there treatment utilization practices, physical activity, or foreign travel which may be indicative of infectious agent related cancer questions that you can sort of get at through the epq yeah, it's a great question, and the answer is yes.

So i can hit physical activity, we have the complete ipac.I'm sorry i lost my question here.We have the complete ipac modules built in, so the light, moderate, vigorous physical activity questions are all in the epq.Foreign travel, we don't ask specifically about foreign travel, but we do ask about infections that might be related to cancer.So we ask about hepatitis, hiv aids, hpv, and so we have a variety of questions in there about infections.In terms of treatment utilization practices, not sure exactly what you're thinking of in terms of that, but we ask.

About, for example, screening, past history screening.We ask for those patients who have had cancer in the past, what treatment they received, just broadly speaking in terms of chemo, radiation, surgery, hormonal therapy, not the specific agents, but just thinking those would be generally the treatment related questions that are in the epq.Okay, and we have another question online from alfa battelle ph.What proportion of the patients completed the epq at home versus on a tablet at the clinic do you know that that varies quite a bit from program to program.

Again because the schedulers are the ones that remind patients to complete it at home, and then if they come in without it completed at home, it's the registration people within the clinic that remind them to do it in the clinic.So it varies by clinic, but i could go out on a limb and say approximately 20 percent of those that complete it do so in the clinic with a vast majority, 80 percent completing it online.And our goal is to really have most patients do it online just.

Because it doesn't impact clinic flow as much if they do it ahead of time.That makes sense.Are there any more callers in the queue, because i see some people are typing questions online there is another caller in the queue.Okay.This is paul sorely ph.From an nhlbi as well.What is the software system for your electronic medical record, and do you have any difficulty pulling research data and linking it to your questionnaire for use okay, our emr is cerner ph.The software that we capture epq data.

Through is called visit manager.There have been various challenges getting data in and out of cerner.Cerner in the past has only accepted discrete data for problems, allergies, medications, and immunizations, which historically weren't areas that we captured on the epq, and that's why we resorted to incorporating really a pdf format of the md summary report.But we're actually working closely with cerner, as well as visit managers working with cerner, to be able to prepopulate discrete fields within that medication history module that i mentioned.And social history would be sort of the next module, so that.

Information on marital status and smoking could prepopulate the discrete fields within the emr.So that's something that's evolving.In terms of getting data out of cerner, that is also somewhat of a challenge, but we have a fairly sophisticated data warehousing team, so in the example where it showed cornosky performance status or even the icu unint.Diagnosis codes that are coming to the billing system via cerner, we have basically code, etl code written to access data from those backend tables and bring it into our data warehouse.So the linkage with epq data is happening at the level of the.

Data warehouse, not cerner per se.It's at the data warehouse level where we're linking the mrns and information from cerner to epq as a cancer registry to bio banking, etc.Pause okay, we have another question from online from joanna leena ph.The appointment scheduling module is a great way to bring patients to the epq.How often does the average patient access the epq and are there other modules that patients have requested specifically how often do they access the epq do they do it once or do they come back.

Well, they can only do it once.So it's only open to that new patient appointment type.Once they complete it, the information is loaded into the emr and then in the data warehouse and then that link in the portal disappears.So they're not able to access it again.And mainly that's because we don't currently have a way of integrating their followup information into the emr so that it would be clinically useful.But that's something we're definitely looking to do in the future.In terms of whether patients have requested modules.

No, they haven't.We've done some focus groups on patients, as well as we have a patient and family advisory council, so any time we're proposing major changes to the epq, we consult the advisory council and get the viewpoint of patients.The feedback we've gotten is that the diet portion of the questionnaire is quite expensive.It takes a lot of time and patients don't really like filling it out.So in the next version of epq i think we're reducing the number of diet questions.So we do like to get patient feedback, but we haven't had any.

Individual patients you know call the cancer center and request that we add a particular module.Okay, are there any other questions in the phone line queue there is.We'll take our next question.This is jane harmon ph., also from the nhlbi epi group.The slide that you showed, the example you showed for multiple sclerosis diagnoses with i believe it was 400 some persons who had ipd code on their cmr, but they didn't selfreport it.Do you have ruleout codes appearing in the emr, as sometimes happens in the claims forms.

And has this been a problem and do you think that's a large part of this group of 400 because we're a cancer hospital, they wouldn't do a work up to rule out ms per se.Those are just, they're really more the document comorbidities that could impact the cancer treatments.So i don't think that that's a likely of a problem at moffitt as it might be for another hospital that's treating a variety of conditions.But specifically to that slide, the reason, and again i just ran that venn diagram within a couple of minutes as sort of a.

Proof of concept of how you can use data from multiple sources to try to validate some of the selfreport, but i would suspect the billing data goes back to 1998, but the epq is really launched depending on the version going back to maybe 2010 or a little bit before that, so you would expect a fairly large number of patients to have a billing code for ms that wouldn't even have epq data.So that's why i was mentioning if you're really going after the answer to that question with methodologic rigor, you would.

First filter on those patients who were seen at the center in the timeframe that the epq is actually live and then look at the overlap.But to your point, there are always a variety of coding issues to consider when you're interpreting the results and that's quite a valid point.Okay, we have another question that came in online about any challenges or resistance to getting patients to buy in or comply with the epq, at least in these early stages of implementation.Yes, i would say the patients felt that it did take.

Quite a while to complete it.And in the early years of the epq what was particularly frustrating to patients, and i don't blame them, is that they would come to the clinic and then sometimes be asked to complete a paper form in addition to the epq they had completed online.And the reason for that was the uptake of the md summary report was not 100 percent right when we started.So in other words, the physicians weren't used to accessing the data in the context of the md summary.

Report and wanted to stick with the paper forms that they had in the clinic.So that was frustrating to the patients because they felt like they were being asked, and they were, being asked to provide information twice.But again as we've worked with the clinicians directly to make these md summary reports more useful to them, they've bought in basically to eliminating the paper forms that were in their clinics, and therefore now the patients have a better experience just completing the information once.And i think they enjoyed doing it ahead of time at home where.

They can look at their medicine cabinet or they can call up a family member if they don't remember who had what type of cancer in their family.So in the end, i think we are getting patient buyin, it's just you have to have the physician buyin in order to get the patient buyin, so that their experience is as positive as they can be.I think we have time for one last question.Is there one on the phones if not there's one more online.There are currently no questions from the phone lines.

So i guess the question on the internet is through the portal what kind of information do patients get back from being on the portal and do they get like risk factor information or stuff like that currently right now they are getting back their lab results, so any time they have lab work done at moffitt, the results of the lab work will be posted to their portal account within a few days.We also provide them with treatment summaries.So if they have a particular type of cancer, the information.

On the type of cancer they have, the stage, the diagnosis, as well as a summary of the various treatments they receive for that cancer are also coming to the patient, and that way they can print that out and give it to their other providers in the community.We would like to provide risk factor information back to them with you know suggestions for improving their behaviors and reducing their risk of other cancers, etc., but right now we don't have that deployed through the portal, it's more of a.

Discussion that the providers have with the patients in the clinic.But ultimately that would be you know a great thing to give back to the patient as well.Okay, great.Well, i'd like to thank everyone for joining us today and specifically i'd like to thank Rollison for participating in today's webinar.Your feedback is very important to us, so you'll be getting a link to a very, very short survey that we ask you to complete after this webinar.And we hope that everyone marks their calendars for october 29th.

Southern Diet Linked to Heart Disease More evidence that fried food raises heart attack risk

People who eat lots of fried food and sugary drinks have a 56 percent higher risk of heart disease compared to those who eat healthier, according to us researchers.The findings in circulation, a journal of the american heart association, were based on a sixyear study of more than 17,000 people in the united states.Researchers found that people who regularly ate what was described as a southern style diet fried foods, eggs, processed meats like bacon and ham, and sugary drinks faced the highest risk of a heart attack or heartrelated death during the next six years.

regardless of your gender, race, or where you live, if you frequently eat a southernstyle diet you should be aware of your risk of heart disease and try to make some gradual changes to your diet, said lead researcher james shikany, a nutritional epidemiologist at the university of alabama at birmingham's division of preventive medicine.Try cutting down the number of times you eat fried foods or processed meats from every day to three days a week as a start, and try substituting baked or grilled chicken or vegetablebased foods.The study included both white and africanamerican men and women aged 45 or older, who did not.

Have heart disease when they began the study.Participants enrolled from 2003 to 2007.They were first screened by telephone, then given an inhome physical exam, then they answered a food frequency questionnaire.Every six months, the participants were interviewed via telephone about their general health status and hospitalizations for nearly six years, said the study.Participants fell into five different eating groups, including the southern style eaters those who favored convenience foods like pasta, mexican food, chinese food, mixed dishes and pizza the plantbased pattern which was mostly vegetables and fruits the sweets.

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