Health Innovators
Health Innovators

Episode 101 · 2 weeks ago

The Data Biome: Difference Between Valuable Data and Noise

ABOUT THIS EPISODE

Data is - and always will be - a chaotic neutral (meaning sometimes, it can be incredibly valuable, and at other times, simply noise).

Understanding which healthcare data collected has value and which is noise? That’s where the real work begins.

On this week’s segment, Jeffrey Carlisle, CEO at Pneuma Systems Corporation; Howard Rosen, CEO and Founder of LifeWIRE; and Brent Wright, Associate Dean for Rural Health Innovation at the University of Louisville, join me for a discussion that centers on the data biome and understanding how data value works in healthcare.

From interoperability of centralized data to who should have ownership over healthcare data, there’s a lot to unpack here - and all of it is valuable. Come and listen to this week’s episode!

Here are the show highlights:

Data: is yours valuable or is it just noise? (0:05)

The power of data in post-market surveillance (6:01)

Interoperability and centralized data: what the future might hold (9:58)

Patient data biome - how far are we from that reality? (17:37)

Who should have ownership of patient data and how it’s integrated (25:55)

The role data plays in a patient’s healthcare (31:55 )

Guest Bios

Jeffrey Carlisle is CEO at Pneuma Systems Corporation. He earned his ScB in Applied Math/Biology from Brown University. 

If you’d like to get in touch with Jeffrey after the show, feel free to reach out to him via LinkedIn at Jeffrey Carlisle or via email at JeffreyCarlisle@me.com.

Howard Rosen is CEO and Founder of LifeWIRE Group. He earned his HBBA in Economics and Marketing and MBA in International Finance/Marketing from York University, Schulich School of business.

If you’d like to get in touch with Howard after the show, feel free to reach out to him via LinkedIn at Howard Rosen or via email at HRosen@LifeWiregroup.com.

Brent Wright is the Associate Dean for Rural Health Innovation at the University of Louisville. He earned his BS in Human Studies from the University of Kentucky and his Masters in Medical Management from the University of Southern California  

If you’d like to get in touch with Brent after the show, feel free to reach out to him via LinkedIn at Brent Wright or via email at R.Wright@louisville.edu.

I you're listening to health, innovators,a podcast and video show about the leaders influencers and earlier doctorswho are shaping the future of health care. I'm your host Doctor Roxey Movie Welcome Back Health Innovators ontoday's episode, you're in for a real treat. We are hosting another executivebriefing with some brilliant leaders and great colleagues and friends, JeffCarlyle, the president of Numa Systems, Corp Howard, Rosen, CEO and founder oflife wire and Writ Wright the Associate Dean for Real Health Innovation at theUniversity of Louville. Welcome back to the show guys so today we're talkingabout data, patient data, medical data, and so I want to just kind of kick offour conversation with. What's the difference between good data versus baddata? Well, in New England, of course, wereferred to a Tater, so is that good, dater or bad daborne ofthe strength? The data doesn't really have any value unless it's beenconverted to information and that conversion requires context. Organization includes you know, sorting andfiltering, and that kind of thing and then analysis so that bad data is stuff that doesn'tever get to actionable informant its noise. Good Day, that is, you know not favorable or unfavorable.It's just real information, that's actionable! So if you have information,it's not actionable, then it's also no wit, but information is actionable,meaning it will change your behavior that that's that's. What I would say isvaluable theater and the difficulty of that is, itdepends on who who is US utilize? The data, because you have different groups,as we talked about earlier in the pre show, is the patient has a certainMount Oda, that's actual valuable for them versus the COLLINTON versus aprovider anywhere in that ecosystem, which complicates the matter. So whatMa bad data use? The context of action for one group may be actually valuableand good for another. Well, that's the kind of white. Whyshould this be as it? Yes? Absolutely exactly, because why should this be easy? Okay? So what is what's happening like? What do we do?Do we have a lot of data out there? Do we have a lot of information what'swhat's happening today and what are we expecting to happen in the future? Ithink we're drowning at data I mean, I think we suffered from data delugesyndrome. I mean it's just that's. Where data causes anxiety, we have somuch of it, but we don't know how to put it together, to bring forthinformation and knowledge to give us concept, and it allow us to act becausethat's the reason we had in Medamin. We want data and we can act on the behalfof the patient. That's what we want to do, but because Datas and disparatesources- and we don't have true Intero to this day- to allow us to bring a lotof information for we just don't have that. So we leads to a lot offrustration. It was real ithel when medical errorshappened and the quote record from an acute care facility is brought to court. You know it can besix feet high, a master amats of a and in many cases they injury, its cause tothe patient could have been solved by a three by five card. It's not the amountthat is our friend the amount. Is Our...

...enemy really really really need to havekind of problem? Oriented Focus and distillation of of data, and we don't that's hard toget so. Is this something that you think machine learning and AI is goingto help fix, because it's going to be able to help us process these giganticdatasets and pull out something that's meaningful. I think it certainly certainly helpedto a certain extent, but there's so many sources of data. You know a simpleone or just patients going on to Dr Google: That's a source of data, asource information that necessarily ar machine learning s not going to helpbecaus they're on be going to their clinician or to the provider with thatdata set an whether it's actual or filtered or anything else. That justadds to the fire hose of additional data that Brent was talking about, and I think we have to be careful aboutthe noise. You know that's generated from all of this. I mean we just wantclarity. If a e and machine learning can give us, clarity can take a lot ofinformation and bring it to that single point of truth that we're seeking, Ithink, that's wonderful, but if it's just going to generate more morebaggage, more noise within the system. It's very frustrated I mean, but Ithink you even you have to back up here, because you start talking about youknow terms such as AI and machine learning. You really got to get thedata right and I still think that we really we struggle in medicine to makesure we get a. You know a diabetic known as a diabetic where you can takea thousand ten thousand, a hundred thousand diabetics where you could putthat into these algorithms and and get true knowledge coming forth. We stillhave dirty data. We still have a lot of dirty data out there and systems thatdon't communicate well with one another. So we're still in many ways where we'retalking about such great tools that were mentioned here, such as a I westill in health care, I think in the trenches just struggle. I think youknow we joke a few of US joke about how sometimes how beautiful paper paper is.You can talk about papers, be an archaic, but sometimes there's just abeauty of paper that you can do with a pin. I mean you can make a mark onpaper you can shut. You can create a quick diagram on paper that you can'tdo that for patience. You know within electronic medical records, so there'sstill there's still a beauty there. You have to balance it, but but really getting it right that that'sthat's where that's! where I'm looking for the two innovators to come forth,how do we really not just data science but but bringing that mercy that datascience and data graphic work together to really help us? His coniton andpatients is saying that they're to new under theSun- and we always you know kind of come back to where we were so maybe thefuture right. The two thousand and thirty day the thousand thirty data isgoing to be picked back to paper and we're going to in two thousand andthirty we're going to say. Remember the good old days when we had paper Howard, but but yet a brents point interms of the data and we're talking about it's also. What is yourcollecting in terms of context like, for example, work that we've done withvariables, and I know this is shocking, but a number of the warbles were notvery accurate. However, many of them were at inaccurate onehundred percent of the time in exactly the same way. So what we were doing isnot measuring the data but measuring the change in the data from thosewearables and that actually became valuable information when we saw thatchange so is not taking the now the main thing, but just look at the changein the Delta actually became a very valuable insight clinicians, who wewere work with, so it is back to your point. It's what is it that data? CanYou? How do you make it information back to Jeff's comment. That's one waywe actually took data that was not necessarily strong as it was but madeit information by just taking the the measuring the change over time. Youknow we touched on a previous call that the FDA, but if you were to...

...understand that the information youcollect in the clinical trial is very, very limited, it's artificiallyconstrained patient population is is very control,but the real power of the day that comes in the post market surveillancewhen you've got patients of all kinds of co, morbidities and differentenvironments, and I mean just on a massive complexity. Yet if you're got good data,then the clarity becomes. I mean it's amazing right so that Ithink ai is more interesting on a societal analysis than on an individualpatient yeah, like I doubt if you've ever seenthe patient, where you said. Oh, my goodness, I could have treatedinpatient so much better if I'd only had a computer helping with the data,it just doesn't happen because that's not the critically limiting factor it's in the aggregate it is, but for anindividual patient, its way, the thoughtful quality of the data yeah, the curation, Satin, absolutely or the incrementalmeasurement over time to have some predictions about what may potentiallyhappen with that patient. I think the I think we've yet to see the potential ofthat type of predictive an analytics on these data sets on thisfor a world evidence that we're talking about. I think t, I think what you said there,I think, and to howards point on Delta. I think that's going to be wonderful tosee as we get people more used to wearing. You know devices thatcollector biometric data. I mean we don't we don't know what it's like tomeasure someone's heart rate over ten years, we're going to know what that'slike in the years and decades ahead to Seeo what what type of subtlevariability that exists. That may show you. You know early hypotension, early,a FIB, you know predictability for a heart attack. I just don't think we'venot had the ability to collect that date and that's you know we coming backto the aim. L POINT: I think that that's what's really exciting. I do have concern on how we've applieddiligence to the data. That's before us now, you know to me: We don't handledata. Well, you know if you move from local to local hospital to hospital.How are we going to be able to gain insight from these large datasets thatwe really need well, and I think in a lot of ways,ovid has made that data even more despair it, because now we've gotvirtual care right. We've got all of these remote patient monitoring allthese wearables all of these different devices and to collect data, that'soutside of the traditional health care ecosystem. So it's even more silentthan ever before, and so I think the the challenges that we've hadpreviously with interoperability in creating some kind of centralized dataset is maybe even exacerbated by. I mean it's good for us to finally beable to collect this data of the person in the home instead of just in thetreatment center. But then it's it creates another problem. I think for usto figure out. How are we gathering and integrating that data? What do you guysthink? What there's that part- and I don't talk to agrigatio all this date,but on the other side, each in individual is different, so Brett,obviously I'm sure you run this all the time. So a heart rate from one patientis different for a heart rate for another as to r the north, as withtheir normans, so guess you're clecking, O agrianes data, but the same time youneed to break it down to to. I think I called precision medicine to the extentthat each person is individual. So again it's understanding theirindividual as a post to saying well, the population does x. So this is asituation. It's breaking it down to much more specific again. This is partof this gross fire. Hose of data is...

...each person's elements. Rare coin bedifferent from the next person we can lower and complicates it if wecan lower the cost of collecting. Some of the data, like you know, Paul Sucksimeter o years ago was you know twenty five hundred dollars and now it'stwenty five and you can do that kind of thing. It's very important. You know somebody comes to the doctorand they have back pain and they go get an x ray and they see a spinal abnormality. It's almostimpossible not to jump to the conclusion that that pain is caused bythat Vermeland. The ever malone that havebeen around for fifteen years be completely unrelated to the to the batpain, but getting baseline data and looking at a changing is Roy, valuable, so Brent earlier you mentioned a termdata bio tell us. What did you create that you come up with that on your own?Where did it come from? What does it mean? Well, you caught me Roxy. I didyou know. I thought I created it right there on comment that Jeff said andthen you caught me just now, because is that you were finishing up that portion.I was googling, so I saw you know, went to Google Real, quick, and I see thatthere's quite a googling on the show. I I love a Syou know. I felt thatquestion was coming, so I wanted to chat because someone else would gogoing to yourself. I check myself so yeah someone's already got this day tobuy on term out there, but you know it's not that hard to data you've got alot of micro bioms, a lot of by ones out there a lot of study, but if youthink it the way, I would conceptualize a data by home. It's look at all theall the data that we would view like Phi, your standard medical record, andthen you look at the biometric data. You look at all the wearables. We havethem and bring that in as another line of data, and then you look at Genomicdata and then you look at consumer data. You know I had a discussion, someonereached out to me about rural health and I'm, like you know really when youstart thinking about people's health, you know it's how you,how you exercise, how many times have I said, Diet and exercise, died andexercise and how many times you patience not listed. Listen to that,but when you really think about it, if you could look, if you had some idealike okay, this is what you're really eating. These are the receipts. Youknow, I see that you have like less than one percent of your monthlyreceipts in fruits and vestiblulete and fresh fruits and vegetables not can,and then, if you think, about getting down to that consumer data and aligningthat to give you context of everything that's going on, including socialdetermines of health. Where I'm hearing a lot of people ask for socialdeterminate data, you put that all together, then you start getting this.I would I really like the term data buy em, while others can lay claim to it. Ithink we can use it here or approach it and because that's what we're chasingyou know we want that comprehensive view of patients, so we can treat thembecause you can, you can tell me you have two diabetics. I can have diabeticIMPATI and Rom one and two, but they're going to be different, based on all ofthat contextual data around them. To my doctor asked me how many beers aday do you drink and I said well to they said really how many beers a weekdo you buy? That is the apite between the consumption and the acquisition.That's right, but but at us it's an ax, a great example to back to Roxy, whenyour comments was in terms of the data and the context of the data. It's alsowith all these things. How is the data requested or asked of the individualsat patient generated? Is it where well related? Where is it come from? Becausethe context what's being asked just to your point jeff is it may be twodifferent answers, so it's again...

...awareness of that becomes what Y, not Ijust another factor, but that becomes a factor in it all and will determine whether it is gooddata or bad data and which is actual or not yeah, and that passive data that cannotlie versus you know the qualitative datawhere it could be that we're lying or we just remember it very differentlythan the receipt show. I remember not long ago that I went toa new doctor and they wanted me to fill out a paper record, which was just verydifficult for me, cause a lot of stress. In fact, for me to fill out of paperrecord and they said you have any surgeries orillnesses to report. I send now a couple and, and by the time I finishedfilling at the form I said, can I have another sheet of paper. Please had forgotten rights. Is You just can'tremember and when we create medical records for people I've done on previous occasions, it actually takes months months to getthe record to be complete because there's just so much family history. Somany other related histories that you cannot. You cannot remember on the fly,so it takes multiple iterations and literally months, which you can'tcompress into hours. They can't it can't be done. We got to take calendartime to do it, so I think a perpetual camutes owned record that can always beaudited and correct it, but never recreate you never try to remember yourappedeutes, always there. You can look at it and correct it, but that's really critical for medicalrecord accuracy. If you look at a medical record for a hospital livespatient, it will be filled with uncorrectable errors. Some of them don't cause harm, but itis a ridiculous number of errors of omission and commission in any hospitalhospital is Pincion, reverend, always yeah. So so, when we talk about this idea ofBrent that I'm going to just give you credit for that, you came up with thepatient biome pasion data byom. You know, I mean itsounds like a dream come true. So how far are we really from that reality? Isthere and are there any players in the market place that are either moving theneedle or best suited to help us get closer to that full holisticaggregation of data yeah? I think that you know the the term that comes to mind is PHR. Itseems like there's an interest around phars I mean there's. Some failuresnoted failures out there early on, but if you think about how apple came backwith the tablet, I mean the people were saying. Tablet was no more and thenhere you come with the tablet and people like the IPAD. I think I don't know if I can give specificcompanies. I know people are working on it and it I want to be correct, but Idon't know that anyone's out there doing it great or it's going to get it.You know there's some big companies, they all want to do health data. Ithink the real question is: How do we get patients involved? You know howI've always believed that patients are are sometimes the last people thoughtabout in health care, and we talk about how important it is to move data. Whydoesn't the patient get some credit you know for data used to? We would bringglass bottles back to the grocery store and get credit for them. We get like adeposit on. You know why don't patients get some type of R uneaten for a grainto be? You know very liberal in sharing their data, whether that's for researchor other other causes, and I think that patience for a lot of years as long asI've been practicing and I've been...

...practicing twenty years now, it's hardhard to believe. I'm saying that, but even in the early days when I thought auniversal record was coming like within five years that patient still at thattime, they thought that that medicine had everything they thought that healthcare has everything they're like you, just have it in a computer. You justhave it there, there's this belief among patients that we have all theirdata perfectly much like a credit report. Like an experience, Trans UnionEquifax. I think we're going to have to look at that model. Personally, I don'tbelieve in Inter op anymore. I don't think we're going to getinteroperability. I think interoperability is, could have comethrough some other mechanism and that mechanism is going to look like thecredit reporting bureaus, because actually there their philosophy iscorrect. I think I think interrupt ability cancome by having the focus of the information, the ownershipof it with the patient, so you're going toyou're not trying to get a lot of different caregivers to seamlessly exchange information. Whatyou're doing instead is really allowing a patient- and I don't say this lightlyExcu. I know the patient needs help in doing it, that patient can't managetheir own medical record any more than you can manage your own taxes right. Soit's too too complex, not that it's complex, but it's more complex andspecialized and any patient will want to do. But if you have that assistancethat paid for monetized kind of assistance to help organize your recordand it's easily transferable to your next caregiver, whoever it isand wherever it is that that gives you the kind of interoperability as long asthere's an agreed point structure and today's structures, the conduit of CareRecord and ast n thirty one and all that stuff- that's not really, itdoesn't really do the job it too complex. Yet it's too simple there's, Ithink a better structure, but the more important thing isn't. The structure ofthe data as much as it is the ownership of it and the ownership will drive to ourobably to your point. Cheff it all the patients own their data assistant, thenitself will be forced to go. Oh, we want this day that we're going to haveto actually create this universal interoperability, so it becomes ademand. Push if you want to be in business, you have to find raveactually be able to read that data. Hey It's Dr Roxy, here with a quickbreak from the conversation. Are you trying to figure out what moves youneed to make to survive and thrive in the new Co vid economy? I want everyhealth innovator to find their most viable and profitable pivot strategy,which is why I created the Co. Vid proof, your business pivot, kid. Thepivot kit is a step by step framework that helps you find your best pivotstrategies. It walks you through six categories. You need to examine for athree hundred and sixty degree view of your business. I call them the sixcritical pivot lenses, as you make your way through this comprehensive kit.You'll be armed with the tools, tips and strategies you need to make sureyou can pivot with speed without missing out on critical details andopportunities, learn more at legacy: Hyphen Daco Back Kit. I want to go back to something that yousaid Brent about the credit bureau. I talk a little bit more about that inthat comparison that you're making okay. So I think it's reallyinteresting. If you look at so you look at banks and- and you look at sharinginformation about what say- loans to Trans Union Experience Equifax, youupload that information. They do that for free. They do that and why do theydo that? Why do they push that information to those bureaus is becausethat they know that they have safer...

...lending universally throughout the financialsystem, because that is shared through those three bureaus. Those are the mainones. So why not in health care? Why don't we have that sharing, becauseit's better if we share the information about patience and about knowledgeabout research, the demand for clinical trials, as I understood it, I'm not aprimary researcher, but those that I know who do do research and promoteclinical trials shake their heads. I mean even at larger universities, it'sjust expensive to enroll it's expensive, to conduct it's very challenging or foruniversities. Just think what we have now: The data collection tools at ourdisposal, whether it's a biometric device or our phone and what you knowif patients on their data and said, look, you got to imagine getting a textmessage that you qualify for this study. You know you can roll in the study fora hundred dollars. Would you release your mate? Would you release yourhealth care information from this APP? You know. Click release your healthcare information, all of the sudden boom you're in rod boom your enrobeboom you're groat. We got a we, the information is there and we're I'mhealth care has an Amnesia when it comes to patient data, because at everypoint of carriage you redo that work all the time, so annoying t one and we're still filling out thepaper chart. Every time you don't want to cause harm with the data, and one ofthe things that causes harm is the request for re entry of data, which is just anopportunity for a transcription error. You never want to re enter data. Youwant to confirm it edit. It check it off, sign it initial it whatever youwant to do to review it, but you really should never allow data to be re entered. The other data point is that you shouldavoid excess specificity right. We went from a billing system, I cd nine codesto ID ten, and there was never really, even as very as to how that could helpan it. Just it forced people to go tocomputerized billing, so it helped that industry, but no one else, because they,the artificial specificity, actually caused heart. He he just can't arguewith that. He could now it's like a Mike, well yeah, it's it's and that'spart of the problem is it's this forced innovation. We got to show we'reinnovated, we're making changes, but sometimes to to get deft point. Ifthere's no basis for that except change for the sake of change, you can createmore harm or more confusion or again, particularly to transfer informationbetween the two systems. It's hard to see the good just change for second changes thatnecessarily a good change. Ye can imagine. If someone decided wewere going to have a hundred commandments instead of ten well- and you know you guys touched on-you know the patient being the person that owns the data and then being theones that are kind of determining how it gets integrated and who it getsintegrated with, and you know kind of like the tax prep, and you know whatcomes to mind is really almost that role being of the caregiver. Now, maybethere's not always an official caregiver involved, but you know a lotof times we're talking about really sick people that aren't going tonecessarily be that text p person, but a lot of times the caregiver, just inthe whole effort of being an advocate for their loved ones, ends up becomingkind of that text. Tax, prep person that has to that needs to beresponsible for aggregating all of that...

...data and in determining who gets it andthat becomes tricky because we went through that with my in laws as they'regetting older. Is You become that advocate? But you know what what prephave I had? What education have? I had you know to become that, or my wife andI become that advocate- were art put in that position and so you're making itso s a lot of these decisions be made. Yes, there is a patient ownership andit comes down to okay. Well, what do you know about what should betransferred or what what elements of this are value are not valuable. So Ihave told people that by education of an NBA- and I said, M L stands formedical. Just because of all these things I had to do and forced to be in. No, I don't thinkit's a credited anywhere, but I kept on trying, but but we're forced to and aswe get you know more of these sandwich generations and we're you know caringfor parents is that example that we're becoming those caregivers. We don'thave the education, but all we do. Is You go online? What we did talk to afew people now is all we can do so again, because it goes back to thecontext, God os data, what's the proper context and what's the valuable contextthat we have, that can actually make those decisions thinks it's certainly not a black andthe white scenario yeah. I think you've got aggregating and then you've gotnavigating. You know where the caregiver comes in and then I thinkyou've got decision support and I think that's where economy comes in, becausein health care we still have to abide about patient autonomy and I think, aspeople have more tools at their disposal, I think if we can show themhow their day they can give them greater opportunity around theknowledge of what's going on with them around the potential consequences oftheir disease or the outcomes or the treatment algorithms. I think that thatpeople can make use of those, but the they're going to have to have the userexperience correct and again they will not work well, if you don't have a gooddata going into them, and I think, rather than a help, health care systemsbe worried about that. I think they're going to have to use those withpatience, because I think this whole thing around data and data blocking and and not sharing data. I think healthcare system see that is the ultimate advantage, but that old that's going togo away when it goes away, I'm not sure, but it is going to go away as patientshave more control over their data, and I think you're going to find thatpatients still need their local healthcare systems as much as theyalways have and trying to come go get past. That fear is going to be, I think,a big leap for data integration rent over a baby step where today, if you go to quest or lap cork, you knowyou'll get your blood analysis and all the outlyingvalues will be highlighted in red and that's very, very helpful right. It'sextremely helpful as it is what I you also had a color coding or someother indication of how it shifted, even if it's in in in limits withinlimits or out how it shifted over time rite you got. The patient became thenormal value set and you're looking at exceptions. So you you can look at younow clinical exceptions, obviously for all mammals or whatever you are tolook at. But in addition, getting the benefit of trend for thatin individual patient yeah, I think I think those tools aregoing to be great in getting people accustomed. I think, if you look atsome basic biometrics like walking like step counters things like that, just I think it really is. I mean Ithink, that's where I think this is where the counter intuited play comesin for success and help to renovation. I think you've got to have the scienceand I think you had to have the artist come together, because people are goingto engage as they have a very rich infographic experience. If you show memy data and it excels spreadsheet, that's boring. If you show me, you knowmy data with color and in maybe bubble...

...charts or something that really give memore of a more of an insight and more of an engagement with my health to Datam a vocation wrinkled in and then maybe you know, look you. You knowyou're doing great, oh by the way humaner sent you a note, anthem justsent you a note and said you're doing so great that they're going to you knowyou're going to get this, I mean maybe you're going to get a water bottle oror a baseball cap, or maybe you're, going to get five dollars off yourpremium or something I mean we all there's different tools out there, butI think people I think to your point earlier Jeff, you talkedabout the money, how you install systems based on the money, and I thinkthat's where health care systems are. We talk about treating patients and thevirtue of treating patients, but to the end of the day you usually are leadingbased on the economics and then the humanistic aspect of the patient careand the position care and the provider care are sometimes secondary. Based onhow quickly you can get the economic installation in so I think we have to. I think we haveto bridge that and think about more how we engage to get better outcomes, so who's responsible for educatingconsumers about the role that data plays in their health care in theirfamily and the the rights that they have to ownershipand even potential compensation. Well, I think and add an element tothat, and not that in even answered your question, which is a veryimportant question, is the day we've been talking about the most parts whoare leaning bit more to Biologics, but you also have the mental health side ofthings until the SD age as well. When you look at data relating to financialrecords to buying habits to where you driving, like all sorts of things, thattie into the mental health side, which is a whole other sat of data which isConsimili more complex but deals in the men to health side, as so to yourquestion Roxy, how do you educate somebody when I would argue in grantand hopefully C N, tell me I'm wrong? We really don't have a handle on allthat, yet we just realizing you have all these data points, but now, ifthere's necessary, real handle on the effect all these people, all thesethings have even on the on the health care system, let alone the individualfor making those decisions m well, and you think about the amountof data just consumer data that we provide to- let's say facebook orInstagram, or even just google, based upon our google search right or agoogle maps or apple maps right, there's just so much data that theseother entities are collecting. That can be that can be used against us in harmfulways, whether we realize it or not, and we have a very different conversationabout keeping that information, private or disclosing that information allowingthese tools to have full access to it versus our healthcare data that you know in some ways is even morecritical for it to be managed. Well, I think, O the patient privacy stuff is, I think, according to most patients, alittle bit overblown because there are very few medical anomalies that you have thataren't obvious to people. Anyway, I mean there, I guess there are somepeople are walking out seemingly healthy, but you know secretly morbidlyobese or schemingly healthy, but with the broken leg, but a lot of it is notsecret right O, I pretty obvious, they may not know exactly what you have, butthey know a here if you're, sick or not, but it's I said Matun privacy iscertainly an impediment to innovation in in health care management.

I think in your question, rocks thatyou ask you know who educates consumers and I think you know calling them usingthe term. Consumers is very important here because, as I've gone along in my career, I I'veopened up my view of health care and I've come to the realization. Now thathealth care is everyone's responsibility, whether you have ahealth illness, health care is still going to affect you in some form offashion, and I would anyone who can tell me how it's not. I would love toknow because, whether that's in your, whether that's in your investment intown, whether it's in your taxes, whether it's in your family, I meanyou're, going to be affected by health care and how health care is utilized inhow people treat their health and we've got a we've, got a long way to go. Ifyou think about where we are right now, we yes, we do and then it can have andhow people are looking at health and health care and science and the lack of scientific literacy thatwe're seeing around how we're just dealing with one issue. And it's notlike we, it's not like. We, we cured cancer and obesity and Carny baskerdisease, and all of that and now we're just. We have covin on our plate, we'vesort of forgotten about all of the chronic diseases, as we deal with withthis most most immediate threat that we're seeingthrough Ovid. So I think everyone has. It has an obligation in educatingconsumers, and I would like to see more. You know whether it's retail space orwhether it's a large online retailer or an in store retailer to do you know towork innovatively to think about how they can interact with patients health,because, again, you know, go back to diet and exercise. You know, I think weneed to rethink those. I think just you know, maybe a hackathon on those wouldbe really good. How can we rethink how to inform people on what they're doingI'm going to call out all the billionaires out there Jeff bezos thetrillionaire out there trolling there before Ovid? I don't even know what youcall it now after Ovid. You know that needs to grab a hold ofthis mission and invest some dollars in this, because I agree with you. I thinkthat every person in the world can benefit from this type of education andgreater literacy. So we talked a lot of. We talked abouta lot of different layers around data and patient data, as we think about thepurpose of this show in the audience of the you know our listeners, Ip andviewership. How does this conversation that we've had today affect thoseinnovators that are in the market place today that are bringing innovations tomarket or maybe even those people who you know, are playing some role ininnovation ecosystem? I think everything every device orevery invention has got some element of information to it, not perhaps noteverything, but in the most part it does, and you just have to be thinkingabout your invention in the context of a much much bigger ecosystem. You knowit's no longer, okay to think about segregated Bada A so. I think that'sthe big thing you could get away with it. You know ten years ago, but today you've got to figure out how you play.You know in the Internet of things and Internet of medical information, so I think that's the bigger thingthink more broadly about where the information's coming from. Where doesit have to go, and how do you fit into a holistic picture? Hi think the use within the ECO systemis really important because I said there as we talked about earlier,there's many many elements in that ecosystem and different data points mea different value along the ways it's Gonta be really aware of all that andthe fact it's going to be used and if it's collecting it's going to bepotentially used and could be misusedd...

...not necessary intentionally, but justmisuse got to be aware to make sure it is it's contextualized and processed ina manner that is usable and understood along along the way. You know I I've come to this andlooking at data and what it means, and I think it all boils down to prediction.I think at every data point you know insight knowledge. However, you want toframe that. I think ultimately, people who are really playing the big datagame are looking towards prediction: everything to do. How do that topredict your next site? Your next Click, your next movement, you know, and inmedicine, it's your next heart attack or your next visit, or I think thatreally thinking about how you use data for predicted capabilities, because Ithink that that is one of the the core areas, I think that's. The reason Ibelieve it to be important is because I think the the quest for predictiondrives value, incredible value yeah, so I've you know,have a different guest on the show all the time and there's a couple that cometo my when I h describe that Brent, so one of them in particular, is doingsome predicted prediction are around bone density and of the propensity tofall and so kind of looking at early interventions of people. You know thecost to the health care system ace, they follow a cost to that family andthat quality of life, and so that's that would be just one really. You know,example that comes to mind really quickly of how this is. You know databeing used in a real positive way in a real, valuable way, not just for thesake of data in that type of prediction, or you think about heart attacks right.You know all of the different indicators that could potentiallypredict where, when someone's going to have aheart attack versus heartburn- and you know what are some interventions thatcould be at least presented having that greater awareness yeah the I'm about to engage in some clinicalstudies for a new confusion pump and this world today is very, very, verydifferent than it was ten years ago. So the FDA is looking for US ability,studies but they're still thinking about a clipboard and somebody watchingyou know a dozen nurses use their product, but what we're building in are very sophisticated counters of behaviorto find out. You know how many mill a second delay is that between this actand that act and look at the big data aspects of it to find out where ourpeople possibly confused. You know where are they hunting around? Where dothey make a mistake? Or you know? Where did you let them make a mistake? Soit's a very different world in terms of information management that it was eveneven ten years ago I got yeah that goes to the point. It'sjust there's so much data a lot. We don't even know what kind of data thatwe really have like. We know sort of specific points of data. You know justan example, as we lit at as a communication platform and Amente data,we realized again in the end to hell side is not just the date time stamp ofwhen someone responded to a message, but with you know, measuring how quicksomeone does respond to a message when it's email text or whatever the casemay be, and that to the change in the speed of which they change here ittakes them longer and longer and longer again, we've realized that becomes anindication of a change of behavior and work in the condition with that changeis, but that was a data point that resulted as a because of collectingdata points. So I said so within all that day there there's new data pointsof collection to explore that we invaluable for you. The management and DecisionSupport, so many closing words as we wrap uphere. We got to wrap up this conversation around data data.

Well, the Big Tame is, you know: patient centered data, that'sso much more holistic than we have ever imagined a short time ago, and it's allthe stuff that brand talked about and in the biome and it it's becoming easier and easier to doit. So I'm actually hopeful that that kind of of data will will be available because the speed with which we can dothings now all the financial transactions is ancient Tenet and it'sreally no technical reason why we can't be doing the same thing in in healthcare in milly, come as we're looking at thepatient and data is in. We talk, let earlier look at the patient as aconsumer. So, in terms of is a perspective, I think that helpsunderstanding the date and the value of the data and the need for the data atthe patient side onward. But I think until you C NEveryone Back Connie, you hear it more and more, but in until the entireepicist em recognizes it you're going to still going to have some of Ye stopgaps once it's all recognized, then okay, at least moving towards solution to managing. All this, I think, is as this new patientconsumer moves forward in health care and moves forward within the entireecosystem, whether it's health care or commerce. I think that what we reallysee need to happen is ubiquity. We really want this data ubiquity aroundaround individual, so we can get the we can get the best from our life. Nothing.I think that sounds so much cloche, but that's really, I mean a lot of healthcare is often time. Seen is just being a moment of trial a moment of sicknessOreole, but I think that we're going to have to change the paradin around howwe do health and health data to make sure we are adapting every day to ourbest wellness and and that that's going to be an exciting time and that's wheresome great tools are going to be able to be used and implemented. But UVULA.For me, t t that's where we want to drive around data and that's wherewe're going to see some exciting things advanced. So I'm going to leave us a closest outon this word that I think every innovator out there should go and poacha data scientist from a consumer goods, company, propter and Gamble Watch out for yourdata scientists right. These are the folks that have been dealing withconsumer data and understand how to leverage it in and out and- and wecould use some of those folks in health care and having you know as we as asinnovators, whether we are corporate innovator or we're a startup oracademic innovator. You know thinking about our team and the teams that werebuilding and planning how that data scientist and when they fit into thatrole. Just like you would having a CEO, apresident, a business development person, a marketing person, thinkingabout the role that data science plays on really really early on in thatbusiness model. Well, thanks guys, thanks again forjoining me as another great episode on the health innovator show reallyappreciate your wisdom to day. Thank you roxy. Thank you so much for listening. I knowyou're busy working to bring your life changing innovation to market, and Ivalue your time and attention to get the latest episodes on your mobiledevice automatically subscribe to the show on your favorite podcast AP, likeApple Podcast, spotify and stitcher. Thank you for listening, and Iappreciate every one who shares the show with friends and colleagues, seeyou on the next episode of Health Innovator, a.

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