Facilitating Shared Decision Making through HCP+DTC Synchronization

Hello, everyone. My name is Mike Paladino. I lead the clinical solutions at OptimizeRx. And today, I wanna talk about, shared decision making and how as pharmaceutical professionals, we can assist with this in educating both clinicians and patients. I have a very, brief skeleton agenda today. First, I will talk about what shared decision making is, and then I'll show a a live example and a case study of how as marketers and professionals in this space, we can use technology to improve shared decision making. Some disclaimers here. I'm not being paid for this presentation. Much of this is my own opinion and from my own experience. I spent nine years in in clinical practice as a pharmacist at large health systems in Philadelphia. I then went to the pharmaceutical industry for seven plus years in medical affairs roles, and I've been at OptimizerX for a little over two years now, really understanding patient and HCP journeys and educating those folks, via one of our channels, or working with clients or agencies and educating in that manner. So, this presentation is educational in purpose and is not me selling any particular OptimizeRx product. So, what is shared decision making? It's a very simple term. It is exactly how it sounds. The AHRQ, the agency for health and research quality, really coined this term some twenty years ago. That agency has been around for thirty years. That agency was developed to really improve the safety in in the way medicine is practiced in the United States. And, if you go to their website, you will see a number of amazing tools and resources and research based on a number of things. But shared decision making is a strong part of of really how they educate and the research that they do there. And what shared decision making is is really this collaborative conversation between clinician and patient or consumer or the family member to make sure that the right type of therapy or maybe no therapy at all is a really strong conversation piece. And when that occurs, we know that patients are more satisfied. When patients are more satisfied, we see better clinical outcomes. And that's essentially, the basis of shared decision making. I urge you to go to this website to look at some of these resources and tools. I use them when I was in practice. A lot of a lot of health system still use them to this day. A real simple example of of shared decision making before I get into a more complicated one is I'm a parent. I have an eight and eleven year old. This resonates with a lot of folks in the crowd. My children used to get a lot of earaches as as younger children, sometimes strep throat, and we've all had the experiences of augmenting way really nasty tasting suspension given to your children. Right? They don't feel good. They have a fever. Now you're giving this them this medicine. They're spitting it across the room. Everybody's upset. Bad experience. The patient is not getting better. So now when my youngest child has strep or an ear infection and requires an antibiotic, and the pediatrician recommends an antibiotic, as a consumer, as an educated consumer, I can say, hey. Listen. She will not take this Augmentin. She will spit it across the room. Please prescribe the bubble gum tasting amoxicillin. Right? We leave. We're happy. My daughter's on the right medicine. She's on a medicine that tastes good. She takes the medicine, and everyone is happy, and then she feels better, right, which is the most important thing. So I think really simple stories like that of having some level of knowledge and having that conversation with the clinician is, is a great example of what shared decision making is. And and for those of us, that are health care practitioners or really consumers of this environment, that's that's the holy grail. That's what we want. Here is an example of a checklist, that I developed, and we will kind of apply this checklist to the the case study that I'm gonna show you today and is really using data and technology to define the journey of both patient and ECP. This data could be claims. It could be labs. It could be historical medication. Right? And then we're we're deploying technology to find the right time and the right type of message to educate these particular audiences. Study. So here's our case study. This is what good looks like. This is what shared decision making should look like. And I'll I'll kinda give you this approach, and then we will reverse engineer on how we use data and technology to get to this particular case study. Okay? So this is a a diabetic management. This gentleman on the left is Matt. You see this very short timeline, this month timeline I have on the screen, and then we also have doctor Smith. So what we'll do here is we'll walk through what Matt looks like. Alright? Matt is forty two. He has type two diabetes. He has hypertension, peripheral arterial disease. He's on a number of medicines, metformin for diabetes, lisinopril, solastosol for his PAD. On the side, he likes to binge watch Netflix. He's a computer engineer. Matt is obviously pretty tech savvy, so he is in front of the computer a lot. And that's Matt. Now let's meet doctor Smith. She manages a midsize suburban PCP office. She has a care team. She has two nurse practitioners. She has one PA. She has several nurses working at her office. The practice has been around for quite some time. She knows the diabetes space pretty well. She's actually a speaker for a number of, SGLT two brands. So, when it comes to diabetes and this type of management, she's pretty well educated. On the side, she's a DIYer, and she likes to use her social media to learn more DIY tricks of the trade. So that is just an an understanding of who these folks are individually, maybe what they like to do, as a as a consumer. And now we talk about Matt's journey. So it's roughly mid January, and Matt has noticed some more hyperglycemic episodes. Right? He's had metformin on board for quite some time. About six months ago, there was an increase in dose, but there was maybe one episode, and now they become more frequent. Right? So in mid January, Matt has another episode. What Matt does now is he proactively reaches out to doctor Smith's office. Right? So he's not just sitting there waiting for something to happen. He is taking action in his care. Matt then goes to doctor Smith, at least three to four weeks later. A BMI is recorded. Matt's BMI is over forty, so he would be defined as an obese patient. His a one c is taken. His a one c is elevated, so that kinda tells us that there's been quite some time that Matt has not been controlled. Alright? Matt and doctor Smith now have an interaction. They have a conversation that, hey. What is currently available for you and what you're currently using, is not working. Right? It's not optimal care. So then there's becomes this conversation between, hey. There's these GLP one injectables. Okay. And then there's these SGLT twos that that doctor Smith is is really used to prescribing. Alright? The end of the day, Matt leaves on GLP one injectable. Alright? And so this type of conversation, this level of conversation, and the timing in which this occurs is really important, and this is exactly how we wanna see the health care environment play out. Alright? So this is, again, kind of like the gold standard of how we want shared decision making to occur. So as professionals in pharma, right, experienced folks with either clinical background or marketing background, media, consumer background, how do we use technology and data to get to Matt and to have Matt have that conversation with doctor Smith? Alright? So how are we aligning the DTC and HCP journey? I I explained this in a a really simple three step process. In the weeds, it may not be simple, but the methodology is very simple. On the left, we see audience definition. So we wanna define the patient, always starting with the patient, and we wanna define the prescriber or the HCP. We then wanna be able to use that definition and learn from all of our historical data that many of us in this room have access to, and build an engine to really predict when that patient is ready for care. And then the right, I guess it would be the most simple and and media related concept is once we have these audiences, we're now educating them, and we just have to decide what channel works best. Alright? I mentioned Netflix for Matt. I mentioned social media for doctor Smith. And so we're simply choosing which, channels to educate these audiences in. Data becomes knowledge. Like I mentioned, we all have access to data here. This is not new, but it's just numbers if we don't understand how to use it. So when I define Matt with data, I can say, well, he has a diagnosis code, this ICD ten code for type two diabetes. He had a lab order, hemoglobin a one c. Right? The CPT code. I have this information. I also have medication history and fill rate as well as the milligram strength to maybe that particular medication. So we can understand dose escalation. If we understand dose escalation and we kinda combine that with doctor visits and lab orders and diagnosis codes, we can kinda get this understanding that Matt may not be managed properly on his current therapy. We then layer in what doctor Smith may look like from a data perspective. Right? What is doctor Smith's specialty? I mentioned she's a PCP, a family doctor. We understand that doctor Smith prescribes a lot of HCLT twos, so we can understand the HCP's prescribing patterns. When we understand all of this data, we can then train a model to predict when somebody like Matt is eligible for care and also understand who Matt is going to go see for care. And here are the dynamic audiences that can be produced on a weekly cadence. We see a number of images like Matt. We also see doctor Smith, and we see some other folks that are part of her care team. Right? A lot of health care, particularly in primary care and family doctors, you will be seeing physician's assistants, nurse practitioners. These folks all control care. They're very important to educate above just the MD. Alright? So when we do both of this perfectly, we can then understand when Matt is gonna see doctor Smith, and let's educate both Matt and doctor Smith at the right time. On the right, you see a number of channels. Again, maybe streaming on Netflix is the place to educate Matt. So we're only educating Matt during that time frame so So that when he goes to doctor Smith and she say is, like, logging into her electronic health record, we have this perfect timing to educate her as well. So that when we combine both of these, we have this very nice synergistic outcome and hopefully a nice shared decision making conversation. So here is kind of the road map in which we use to find data, develop an AI model, predict dynamic audiences, then educating at the right time in the right channel. So now we talk about this time frame too. This was a tight time frame, and we wanna tailor the channel appropriately. I kinda use that term Netflix a lot and and doctor Smith using social media. We also think about what type of messaging resonates. So Matt left on an injectable GLP one. Well, maybe Matt was concerned about giving himself injections. Right? So Matt's media plan should potentially involve education on how you would sub q inject yourself, and it could be web based. Again, so when he's on the Internet all day, he's serving up this he's served up this information. He may also think that, this is an injectable. It must be really expensive, and it potentially is. But Matt has a commercial payer, and there could be an opportunity to educate Matt on access and how he could actually get drug at a low cost. Alright? So now we have doctor Smith. How does how how is she best educated? Alright. She's a different type of consumer here. Right? She's a she's a physician, so she has an understanding of this disease state. So maybe for her, the ADA guidelines should be an opportunity of education. GLP ones have a lot of great information in the ADA guidelines, particularly with obesity and diabetes. So maybe she needs to be be brought up to date on GLP ones in the guidelines. Similarly, she may think, oh, you know what? I've been prescribing us GLT twos forever. They're affordable. My patients can get them, and she doesn't know the formulary coverage of GLP ones. Again, another opportunity to educate on access. So when we can align both of these education points, these conversations become really valuable. Alright? Then lastly, doctor Smith is had has made the diagnosis with with Matt and is about to send him home on GLP ones. She's in her electronic health record prescribing drug because that's where doctors spend all of their day, and she gets notified of a co pay benefit for this drug that she can actually print out and give to Matt. So this is really a full circle here of this timeline of how we identify patient and provider, the quick time frame in which we wanna educate these folks, and then the type of education that we give them. And lastly, here is our key takeaway slide. We all know shared decision making improves patient care and satisfaction. And in this life science industry that we live in, we do have the responsibility to find the right patient, the right HCP, the right time, and the right resource and channel to improve shared decision making. That concludes the presentation. If anybody has any questions, please email me. I would be happy to have a conversation, at some later time. Thank you very much.