Unlocking Healthcare Data: A Conversation with Dr. Tim O’Connell

Episode Overview

Episode Topic:  In this insightful episode of “The Skeleton Crew,” the discussion revolves around the transformative power of emtelligent software in the field of radiology and healthcare informatics. Host Jen Callahan engages in an illuminating conversation with Dr. Tim O’Connell, the CEO of emtelligent and a practicing radiologist. Dr. O’Connell also shares more about his journey from a diverse background in engineering and neuroscience to founding emtelligent and becoming a radiologist. This episode offers a deep dive into the critical role of informatics and how it can revolutionize healthcare.

Lessons You’ll Learn: The discussion delves deep into the functionalities of emtelligent’s software, designed to process unstructured medical language and convert it into structured data. Dr. O’Connell also provided valuable insights for individuals aspiring to become radiologic technologists. By granting access to invaluable patient information and streamlining tasks like summarizing patient histories, emtelligent’s software contributes to enhancing the quality of healthcare delivery and mitigating burnout among healthcare professionals.

About Our Guests: The guest of honor in this episode is Dr. Tim O’Connell, the CEO of emtelligent and a practicing radiologist. Dr. O’Connell brings a unique perspective to the table, drawing from his background in engineering and neuroscience. He shares his passion for revolutionizing healthcare through informatics, emphasizing the need for software that can decipher complex medical documents accurately. Host Jen Callahan navigates the conversation expertly, unraveling the intricate world of radiology and healthcare technology.

Topics Covered: Dr. O’Connell provides insights into the inception of emtelligent and its mission to enhance healthcare through innovative software. The episode explores the capabilities of emtelligent’s software, which can process unstructured medical language and transform it into structured data. This technology’s potential applications extend beyond radiology, benefiting government agencies, health insurance companies, biotech firms, and even patients. Moreover, Dr. O’Connell discussed the pivotal role of radiologic technologist programs in preparing future professionals.

Our Guest: Dr. Tim O’Connell, CEO of emtelligent and Trauma Radiologist

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Episode Transcript

Tim O’Connell: [00:00:00]

When you talk about burnout, one of the big factors is people not feeling proud of the work they do or them feeling they don’t have enough time to do the work in the manner that they want to do it, to do a good job, and giving people access to information and helping them know their patients better. I think any radiologist would say, Yeah, I feel like I can do higher quality reports when I know my patients better and that will help contribute to job satisfaction. There’s a whole bunch of ways which I think we can help caregivers do their jobs better and more efficiently and help reduce burnout.

Jen Callahan: [00:00:33]

Welcome to the Skeleton Crew. I’m your host, Jen Callahan, a technologist with ten-plus years experience. In each episode, we will explore the fast-paced, ever-changing suburbs. Completely crazy field of radiology. We will speak to technologists from all different modalities about their careers and education. The educators and leaders who are shaping the field today and the business executives whose innovations are paving the future of radiology.

Jen Callahan: [00:01:03]

This episode is brought to you by X-ray technician Schools.com. If you’re considering a career in X-ray, visit X-ray technician Schools.com. To explore schools and to get honest information on career paths, salaries, and degree options. Hey, everybody. Welcome back to another episode of The Skeleton Crew. For those of you that are out there in the world of radiology today, I have the privilege of speaking with Dr. Tim O’Connell. He is the CEO of a company called emtelligent. And then he is also too the vice chair for the Department of Radiology doing clinical informatics. And he also, too, is a practicing radiologist as he works in the Department of Radiology. Tim, thanks so much for being with us here today. Really appreciate it.

Tim O’Connell: [00:01:50]

Thanks, Jen. It’s a pleasure to be here.

Jen Callahan: [00:01:52]

Awesome. So let’s just get started. Can you just give me a little bit of background of yourself and how you went from doing one thing, being a radiologist, and now starting a company of emtelligent, and then we’ll have you dive into that after there?

Tim O’Connell: [00:02:05]

Sounds great. Thanks, Jen. So, yeah, I’ve got a little bit of a mixed background. I went to school, didn’t know what to study, did a degree in neuroscience, and was paying my way through university, selling computers and fixing computers and doing networking and didn’t know what to do and was done my degree. So I did a master’s degree in engineering and then I worked for a couple of big companies doing telecommunications and network engineering. And then I decided to change course and went back to medical school and ended up becoming a radiologist. And now I’m happily practicing radiology. And I also do a fair bit of informatics work at the hospitals and institutions that I work with for radiology. Then along this path in radiology, I met some great guys and we started emtelligent to solve some of the problems we see in health care today.

Jen Callahan: [00:02:49]

So before we dive into emtelligent, I wanted to ask you, you yourself as a practicing radiologist, is there a certain modality that you specialize in?

Tim O’Connell: [00:02:56]

Not by modality. My subspecialty. So I have a combined fellowship in emergency and trauma radiology and in imaging informatics from Brigham and Women’s. But my practices has changed over the years. And so I do a lot of general radiology and a fair bit of oncology work today.

Jen Callahan: [00:03:12]

All right. So what is Imaging Informatics?

Tim O’Connell: [00:03:15]

Imaging Informatics is in radiology. We’ve got an all-digital workflow essentially nowadays, and there’s a lot of plumbing and other bits that need to be in place for our radiology departments to work. And so imaging informatics is making sure that the information is flowing from system to system, and it’s working and it is meeting the needs of the radiologists workflow and the technologist workflow and that reports are getting distributed to the right people at the right time. So you can think about it as everything from PACs to RIS to speech recognition technologies to other adjuvant technologies like what we do at emtelligent.

Jen Callahan: [00:03:47]

Okay, So that’s making sure that they’re all working together and flowing properly so that you can do your job, the technologists can do their job, and that the people who are there to have their studies, that their doctors are receiving the information.

Tim O’Connell: [00:04:00]

Absolutely. And that the appropriate electronic checks and balances are in place so that we’ve got QA systems and this sort of thing to make sure that things aren’t slipping through cracks. A mentor of mine once told me that Imaging Informatics is ensuring the quality, safety, and efficiency of the radiology department. It is a nice way to describe it.

Jen Callahan: [00:04:16]

So then moving into what we’re here to discuss today, your company, emtelligent, that includes informatics, obviously. Give us the base of how you started and where you currently are with that.

Tim O’Connell: [00:04:28]

Yeah, absolutely. So during my fellowship, I met a team from Boston Children’s and they make an open-source medical natural language processing platform. And it’s a great software and it’s open source and it’s free and was in practice. And the use case I was trying to solve Jen is I was working at that time as a mostly emergency and trauma radiologist. And in a busy shift, I might have to read 50 CT scans and 100 X-rays. And I just wanted to get a summary of the patient histories. I’d open a case and they might have 50 priors. And I just wanted to be like, Oh my gosh, who is this patient? Like, why is part of their valve intersected? What is this thing in their liver to know? Is this a known condition or is this something that I’m going to have to give a differential for? So I used some software, some of this open source medical NLP software. I created an app for my colleagues to use that was the intention and processed a couple of years with the radiology reports and that we could have a button in packs to pull up this automated patient summary because that would help us know our patients better, help deliver more specific reports, help reduce the number of unneeded follow-ups for recommendations for things that are already known. But the issue was, is that NLP software was just a bit too immature. It would understanding language is difficult and it would say patients had diseases when they were in fact they didn’t have them. Or when the disease belonged to a family member. It couldn’t understand that sort of thing. The whole idea was correct. Like doctors need to know their patients better, but that technology was sort of the wrong one at the wrong time. So around that time, I met our chief technology officer at emtelligent, a wonderful gentleman named Dr. Anoop Sarkar, who’s a lifelong researcher and academic in the field of natural language processing and computer science, and with a couple other guys, we ended up starting an emtelligent.

Jen Callahan: [00:06:08]

So you took the NLP base of what you started using and you developed it even further.

Tim O’Connell: [00:06:13]

Yeah, absolutely. So like we didn’t use that software. We wrote all our software from scratch, but we realize the need was to have a medical natural language processing platform. In other words, computer software that could understand human medical language.

Jen Callahan: [00:06:27]

Right. Sounds like so out there, but it makes total sense, especially like you said, sitting there looking at a patient who has had at least ten images or imaging studies prior to that. And you’re just trying to figure out what’s going on with this patient. But I don’t have the time to sit there and look through the reports from all the different studies that they’ve had done prior.

Tim O’Connell: [00:06:45]

Exactly. My use case was I needed to know, oh, they had a liver cyst diagnosed in 1996. They had a bowel resection in 2005. They had an adrenal adenoma that was picked up in 2004. Like this stuff is known. So I can be like as I go through the images, I can be like, check, check. This all makes sense. This is congruent, okay? This sort of thing, right? Then read the pros of my colleagues’ reports from former studies and you only have a limited amount of time. You need things that tools that can help you in your job.

Jen Callahan: [00:07:12]

So would that be hooked up to the PACs where the images are or would it be used for I guess it would be risked like, for instance, like the health system that I work where they use Epic for their system? Would it be hooked up to both of those or would it be hooked up to one or the other? Yeah.

Tim O’Connell: [00:07:28]

So one of the things in informatics is that different systems are the system of record for that department’s document. So for example, the risk is usually the system of record like that. The risk is the truth and it will send a copy of documents to of radiology reports to the EHR. The EHR is not necessarily the system of quote-unquote truth for radiology reports, but nowadays we’re seeing a lot of these lines blurred and EHRs themselves are acting as the risks and this sort of thing. So yeah, when we go into an institution at emtelligent, one of the ways we integrate is connecting to the EHR platform to process the unstructured text of medical documents that are in there, be they radiology reports or pathology reports or discharge summaries, soap notes, whatever it is.

Jen Callahan: [00:08:09]

So the EHR, just for someone who might be listening and doesn’t exactly know what that acronym stands for, that would be like the charting system.

Tim O’Connell: [00:08:17]

Well, yeah, in this setting, using the term EHR and EMR for Electronic Medical Records, sort of just to mean thing. So the EMR is like a or is like a huge database that contains all the patient documents. That’s the easiest way to think about it. Okay.

Jen Callahan: [00:08:30]

So all right. And then the imaging system interacts with the EMR or the EHR. Then as yourself, as the radiologist, you’re sitting there, you have your emtelligent hooked up to the EHR and you know, you have this one study, so you’ll just go over to emtelligent and type in patient’s name and clicking off on certain data that you’re looking for in the patient’s chart.

Tim O’Connell: [00:08:52]

Well, what we do now at emtelligent is a little bit different than the original concept that I came up with years ago. The original concept that I came up with years ago was a fairly narrow use case. It was let’s read radiology reports and provide a patient history for radiologists. The idea was correct years ago, but the foundational technology wasn’t as mature as I needed it to be. And that foundational technology was software that can read and understand medical documents. And so that’s what we’ve done at emtelligent. We don’t necessarily make applications for people to use. We’re really focused on the extremely difficult task of software that can understand medical reports and medical documents. And then we work with other partners to develop apps. On top of that. It makes a lot of sense. If you’re a company that makes apps, you’re dealing with customers and customer issues and writing sort of front-end software and making it beautiful and usable. It may not be your subspecialty to make software that can understand human English or human language. And so that’s our specialty is that ability to have software that understands when someone says he had his gallbladder out in 2016 and he’s had diabetes, he’s a longtime user of metformin, right? So we can understand all of those drug names and diseases and procedures and know whether they present or absent or this sort of thing. So we do all what’s called data structuring. We take unstructured medical language and turn it into structured data so people can use it in their apps because we enable other people’s use cases. So there’s literally like hundreds of use cases, if not more in medicine that people can use us for.

Jen Callahan: [00:10:21]

So then besides doctors using it, or who else would have either access to it or would even be interested.

Tim O’Connell: [00:10:27]

So many people in the healthcare ecosystem who need access to structured data from medical documents because those medical documents are created by clinicians like nurses and doctors and pharmacists, and they contain the source of truth about a patient’s health. And so if you’re a government, you may want to use our software to understand epidemiology, right? Like you can imagine how useful it would be to have a real-time epidemiology reporting system to go in City X where there’s a million people. There were a thousand doctor visits today, primary care physicians where cough was the presenting complaint. That means, gosh, there might be a respiratory illness on the go. Do we need to take action about this? So you can think about it? Governments could use it. Payers can certainly use it, right? Right now they’re Fed claims data, but they want more and more information to know their patients better, to appropriately assess risk.

Jen Callahan: [00:11:16]

So would that be really more like insurance companies that you’re talking about?

Tim O’Connell: [00:11:19]

Yeah, when I say payers, I mean health insurance companies. Okay. You can think about people in biotech and pharma. Drug discovery depends on being able to know who’s got what disease and what are their side effects and what’s going on there. So we work with companies in the pharma space. There’s many, many different users who can use our store. It’s not just for doctors. If you call up a hospital and said, Hey, how many of your patients had B-cell lymphoma last month, they’d probably go, Oh, it’s in the charts. I mean, we could do a chart review and look it up, but that would be humans looking at charts, trying to sort this out, right? They wouldn’t necessarily know that specific information, whereas our software can just read those charts and store it in a database and it takes might take a few seconds to read the charts. And then we analysts at a hospital or health care system can then start running analytics on it and know sort of everything that happened to all other patients.

Jen Callahan: [00:12:06]

I think your website termed it as finding the needle in the haystack.

Tim O’Connell: [00:12:09]

Yeah, we got a lot. There’s a lot of needles and a lot of haystacks. In health care?

Jen Callahan: [00:12:12]

Yeah, definitely. How about patients with patients be able to utilize something like this?

Tim O’Connell: [00:12:17]

I’m a huge proponent of patients having access to their health records. One thing that would be useful for patients is sometimes there can be errors in health records like a doctor May speech recognition system may miss something That said the patient didn’t have a disease and it ended up in the report and saying they did or something like that. So there are certainly applications for patients to help them with that or to do translation. When a patient says, Oh, I’ve got a slap tear in my shoulder, what is a slap tear? What does that mean? It sounds bad. Is it bad? So you can also use software like ours, which sort of understands a record to then hook it up to things like medical knowledge databases so patients can get a more of a plain language understanding of their document.

Jen Callahan: [00:12:54]

So how about the technologists in the field? Is this something that X-ray tags or MRI tags or CT tags, even outside of that, like maybe almost like nurses, would nurses be able to use something like this? Absolutely.

Tim O’Connell: [00:13:05]

There’s a lot of use cases. You can imagine nurses coming on shift and they don’t know a patient and they want to get an automated patient summary of I’m now responsible for Mrs. Wong in room three. I need to know about Mrs. Wong and what’s in her more than just what’s in her problem list. Right? Like this was going to help me know the patient better and provide treatment that’s. And provide care for that patient that’s better for them. One use case, we have sort of a sample app to show this is for radiologic technologists working in MRI. Patients often can fill out a form and forget that they have metal in their body or they had a certain type of procedure and then they show up for an MRI and they remember something like, Oh, I got metal in my eye working in a machine shop 30 years ago. And that would they couldn’t have the MRI. So it can be a wasted time slot. So one sort of sample app helps the technologists search through the patient’s chart for things like that. Prior procedures or medical devices or things like metal in the orbit, that sort of stuff.

Jen Callahan: [00:14:00]

That’s really interesting. I mean, all this cool stuff that’s going on out there with all that, like so many different technologies. In the past few weeks, I’ve been speaking to companies that have really come a long way in using artificial intelligence in terms of helping to make impressions like the summaries of radiology reports or some and aiding in finding something that might have been missed by the naked eye. It’s so great that different softwares like this are being developed. Just help the human mind. Not that it’s trying to take over for you, but just aiding you in doing your job better almost.

Tim O’Connell: [00:14:34]

Absolutely. And you know what? I think in health care, we’ve got sort of this problem where if you’re not a doctor, you know, you’re being told again and again like this is your role, stay in your lane, this sort of thing. And there’s real barriers to care when that happens. Right. Like you, I’m sure as technologists and nurses often feel like, oh, I’m not allowed to think about that or I’m not allowed to do that because that’s not part of my job. But software like ours can help people in every role in health care get to know their patients better. And I’m really keen on that because I think even just like some tiny piece of information that you may not think is important or may be very important to delivering care for the patient. So giving people access to those needles in haystacks is really important.

Jen Callahan: [00:15:12]

So using that interfacing with an EMR, is it also to pulling from not just reports but say guess like signed reports would are also to pull information say from like a patient’s stay and there was just a progress report that was put in by say like a doctor or a nurse during the day.

Tim O’Connell: [00:15:31]

Absolutely. So I’m a radiologist. You’re a radiologic technologist, a radiologist show. But we deal with all different types of medical reports at intelligence. So the majority of the reports that we process are, in fact, not radiology reports.

Jen Callahan: [00:15:44]

So how long have you been working on this and how long has it been out in the market that telepro?

Tim O’Connell: [00:15:49]

So we started emtelligent back in like we incorporated the company in 2016 and I’ve been working on it since then. I think we sort of first went live around 2019 at a customer site and really we’ve just started our commercialization efforts this year. We felt that the accuracy of the engine and that our feature list was rich enough to go to market and also sort of chief quality Officer. So I’m the one who I have to be pretty happy with things to be able to go, Yeah, I think this is I would be happy if my colleagues use this.

Jen Callahan: [00:16:19]

Is there a certain market right now that you’re targeting more?

Tim O’Connell: [00:16:23]

We’re focused. The three markets that were there’s a lot of markets. As I mentioned, there’s like pharma, there’s government, there’s payers, there’s health tech, there’s hospitals and health systems. And I think we’re as we’re we’re being able to tackle more and more of these markets. So payers is very important for us. There are people who have to deal with really large volumes of documents and they really need good software. But we’re also certainly focused on health technology. If you have medical software today that deals with patient records, right? If you add NLP and that sort of report intelligence to it, you can probably make your software better or have more features or retain more customers, or get new business. There’s a lot of different verticals we’re focused on. Right!

Jen Callahan: [00:17:03]

Now as the feedback from who you’ve already integrated with, has it been good feedback?

Tim O’Connell: [00:17:09]

Yeah, you know, there’s so the breadth and in-depth of how language is used in medicine is so broad and so deep. There’s not a site that we go to that we don’t get valuable feedback from. But it’s great to see customers in production using features like our ability to detect follow-ups recommended by radiologists to help make sure that patients don’t miss those follow-up exams. To me, every time that happens, that’s like such an enormous win for patient care. That makes me very happy.

Jen Callahan: [00:17:36]

So looking more towards integrating with health systems first or like doctor’s offices themselves.

Tim O’Connell: [00:17:43]

Usually the use case. Every doctor’s office. It’s not the sort of software that would go and sell to an individual doctor’s office, but it’s certainly the type of software we would go and work with an EHR, EMR vendor who might be in tens of thousands of doctor’s offices. And so we’ve done some of that work and done pilots and trials in real-world utility in primary care physicians offices and gotten great feedback and they’re quite happy with it. So yeah, we’ve got a lot of different commercialization efforts like that on the go right now.

Jen Callahan: [00:18:13]

So Tim, going back to how I had mentioned that in the past month or so that I’ve been speaking to different artificial intelligence companies that have been producing technology and software to assist in the healthcare flow and mainly to assist in the radiologists themselves with reading images, picking up on subtleties or simply helping in the text area of finishing out a report. It seems like this type of technology that you’ve developed would almost go along the lines with that to help with radiologist burnout, where you know, you’re not, like we said, like you’re not searching through all these different charts to find the information, to be able to look at these images. Have you had feedback from people that have been using this software at this point about that?

Tim O’Connell: [00:18:56]

Not specific feedback about that, but that is certainly a goal of our software. And some of the use cases which we’re working with with people on is to help physicians get at the information they need faster, more efficiently, more accurately, and help them do a better quality job. When you talk about burnout. One of the big factors is people not feeling proud of the work they do or them feeling they don’t have enough time to do the work in the manner that they want to do it, to do a good job, and giving people access to information and helping them know their patients better. Those are all ways that will help. I think any radiologist would say, Yeah, I feel like I can do higher quality reports when I know my patients better and that will help contribute to job satisfaction. And also just there’s a whole bunch of tools that we don’t even have today that can enable providing feedback on the quality of radiologist reports. So, you know, when you’re doing a good job or there’s areas for improvement, being able just to search the patient chart properly and you with context-sensitive search, does the patient have they had appendicitis? Right? Not just rule out appendicitis or that sort of thing. So there’s a whole bunch of ways which I think we can help caregivers do their jobs better and more efficiently and help reduce burnout.

Jen Callahan: [00:20:04]

So I’m going to turn the table now and I’m going to put you in the hot seat. Not that you haven’t given us enough information already, but just always like to have my guests that are on to talk a little bit about the radiology world and how you feel about it and where you’re at in it. So you are still practicing as a radiologist, even though you are the CEO of emtelligent. And you were telling me that you work about two days a week. Are you working eight-hour shifts, 12-hour shifts or it just depends.

Tim O’Connell: [00:20:29]

Yeah, it does just depend. It depends on the hospital. I’m working at most of the hospitals. I work at work at eight-hour shifts. And so it’s you come in and you know what your work assignment is and you do your work and you’re able to go home. I try not to do calls, but I do a little bit of calls occasionally.

Jen Callahan: [00:20:44]

So you’ve been radiologists since 2013, but then you were saying how your undergrad with neuroscience that played into radiology at all?

Tim O’Connell: [00:20:54]

Well, sadly, no, I don’t think so. I think neuroscience is really fascinating. I think a lot of people tend to think of neuroscience and, oh, wow, you must be studying the brain and you must be like, interested in neuroradiology and neuroscience as an academic discipline, I found was a lot more about learning how nerve cells work and doing things like plugging electrodes into leeches and things like this. So it was a bit abstracted from actual how the brain works and human health care and things like that. It was a great intro and you have to take your cell biology and organic chemistry and all this kind of stuff. So it certainly was good preparation for applying to medical school.

Jen Callahan: [00:21:26]

So where do you see yourself and emtelligent maybe in the next few years, are you going to continue pushing forward with the current software that you have, or do you have things grinding gears already about where the path of where you might like to lead?

Tim O’Connell: [00:21:40]

So absolutely, yeah. I think there’s just tremendous advancements being made in our field right now, particularly in areas like generative AI, and every year there’s major leaps being made forward and our software is using a lot of those technologies and we’re every time we do a software release, we’re making major leaps forward. So I think the future will hold for us at emtelligent, probably enhancements in making it easier to use our software or making our software more accurate, improving speed of throughput, things like that. So I think there’s going to be a lot of incremental improvements over the next several years and hopefully, we’ll see the software being used for more and more use cases. One of the really fun parts of my job is talking to people who are like, Oh, we’d love to use your software for this. And I’d be like, didn’t even think of that as a use case. So that’s super cool.

Speaker3: [00:22:23]

Do you have to go through?

Jen Callahan: [00:22:24]

Any type of approval process for your software? Because it is dealing with health informatics and health care and patient care?

Tim O’Connell: [00:22:30]

Yeah. So the opinions we’ve gotten from councils in the US and Canada have been that our software is not considered a medical device. Certainly be possible for, let’s say we partnered with a technology company that was going to implement our software. It would be possible for someone to implement it in a way that became a medical device. If you were using our software to predict future outcomes or something like that, that would be possible. But it doing an app as a platform on medical records is not the opinion from council is that it’s not a medical device.

Jen Callahan: [00:23:01]

Okay. Definitely a great tool for anyone in healthcare to have.

Tim O’Connell: [00:23:05]

Yeah, we want to be the enablers of 1,000 different apps and a thousand different use cases for people. And we want to stay focused on just doing the hard work of understanding human language.

Jen Callahan: [00:23:16]

Yeah, because medical terms are for sure. Oh, yeah, confusing.

Tim O’Connell: [00:23:21]

Yeah. We say I think there’s the saying that medical school is a four-year terminology course and I think it’s right. Medical English is not standard English. If you used our software on a legal document or on a product review, you would get all sorts of strange stuff out.

Jen Callahan: [00:23:34]

Do you think that was purely based because medical language is based of like Latin almost?

Tim O’Connell: [00:23:39]

We use all this crazy medical terminology that seems very difficult to an outside eye so that we can be really, really specific about it. Like when I say, Oh, there’s a fracture of the lamina of t four to a spine surgeon and they know exactly what I’m saying and exact body part is affected. But, to a person who’s never heard those words before, they may find that very confusing. That’s why we use so much terminology so that we can really when I say something and the other person understands it, hopefully, they’ve understood 100% of what I have to say. Miles Davis had a great quote. He said, If you understood everything I said, you’d be me. And I think that strikes at the heart of how difficult communication is and how difficult language is. And that’s why we use our specialized medical vocabularies.

Jen Callahan: [00:24:19]

All right. Well, on that note, then, we’re going to end here with Dr. Tim O’Connell. Thanks so much for the enlightening conversation, Tim. I really appreciate it. And I hope to see emtelligent utilized in my future of my career because I think it’s an excellent tool for anyone to be able to use.

Tim O’Connell: [00:24:35]

Awesome. Thank you so much, Jen. It’s been a real pleasure.

Jen Callahan: [00:24:37] Yeah. All right, everybody, thanks so much for being with us. And Dr. Tim O’Connell, make sure that you check out the Skeleton Crew on YouTube, Apple Podcasts, and then Spotify as well. Okay, everybody. We’ll see you soon.

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