In this HIMSS26 recap episode, Tony Schueth is joined by Brian Bamberger, Vanessa Candelora, and Brian Dwyer to unpack what they heard, saw, and debated after a week on the ground in Las Vegas. Rather than focusing on announcements or product launches, the conversation centers on the signals emerging across sessions, client meetings, and hallway conversations and what those signals suggest about where health IT is headed.
In this HIMSS26 recap episode, Tony Schueth is joined by Brian Bamberger, Vanessa Candelora, and Brian Dwyer to unpack what they heard, saw, and debated after a week on the ground in Las Vegas. Rather than focusing on announcements or product launches, the conversation centers on the signals emerging across sessions, client meetings, and hallway conversations and what those signals suggest about where health IT is headed.
The discussion opens with reflections on a keynote from former Tesla president Jon McNeill, which challenged attendees to rethink entrenched healthcare processes. While initial skepticism about an outsider perspective was high, the panel agrees the message resonated. Meaningful progress may require stripping workflows down to their fundamentals and rebuilding them with simplicity in mind. That theme carries throughout the episode, particularly as the group connects it to persistent challenges like prior authorization and administrative burden.
From there, the conversation shifts to the dominant presence of AI at HIMSS26. Unlike prior years, where AI often felt theoretical, the panel notes a clear shift toward practical applications embedded directly into workflows. Examples like prior authorization automation and clinical summarization highlight real efficiency gains, but the group is quick to point out that AI is only as good as the data behind it. Concerns around data quality, bias, and trust are no longer side conversations. They are central to whether AI can scale in meaningful ways. As one theme emerges repeatedly, it is that the industry may have rushed ahead with AI excitement before fully solving for foundational data challenges.
That leads into a deeper discussion on interoperability. The panel describes a noticeable transition from “interoperability as a vision” to “interoperability as infrastructure.” Organizations are no longer asking what connected data exchange could look like. They are now actively building the components required to support it. This includes identity frameworks, consent models, trust networks, and governance structures. While progress is real, the work is also proving to be more complex than anticipated, with many stakeholders still grappling with how these pieces fit together at scale.
The conversation also explores how these shifts are playing out across different stakeholders. From a payer and vendor perspective, Dwyer highlights that many organizations have moved firmly into execution mode, particularly with regulatory deadlines like CMS-0057 on the horizon. However, there is still uncertainty about what comes next, especially when it comes to scaling beyond compliance into true business transformation. For life sciences, Bamberger notes that strategy is largely set, but execution remains uneven. Efforts are increasingly focused on improving data capture within EHRs, enabling more efficient prior authorization, and addressing complex use cases like rare disease diagnosis, where fragmented data can significantly delay care.
Several moments in the discussion bring the conversation back to foundational issues that continue to slow progress. Patient identity, data quality, and structured versus unstructured data all emerge as persistent barriers. The group emphasizes that without resolving these challenges, even the most advanced AI tools will fall short. Initiatives like FHIR accelerators and broader industry collaborations are seen as critical to closing these gaps, but there is still work to be done to move from standards development to consistent, real-world implementation.
The panel also spends time on emerging areas of focus, including price transparency and rural health transformation. Candelora shares observations from her HIMSS presentation, noting growing engagement and more nuanced questions from stakeholders, signaling that the industry is beginning to take these efforts more seriously. Meanwhile, rural health funding is creating both opportunity and urgency, with stakeholders recognizing that interoperability and data sharing will be essential to making those investments impactful within tight timelines.
One of the more unexpected themes to surface is the human side of all this change. Despite the heavy focus on technology, many of the most meaningful conversations at HIMSS centered on workforce impact, trust, and the role of humans in an AI-enabled future. The panel reflects on the need for thoughtful change management, noting that adoption is not just about deploying new tools but building confidence in how they are used. There is a shared recognition that while AI will shift certain types of work, it will also require new roles, new skills, and a more intentional approach to integrating technology into care delivery.
As the episode wraps, each participant highlights a key signal to watch over the next 12 to 18 months. Prior authorization is widely seen as approaching an inflection point, with tangible progress finally within reach, though not fully complete. At the same time, the convergence of interoperability, AI, and policy is identified as a broader, more transformative trend. This trend will shape how data flows, how workflows are designed, and ultimately how care is delivered.
The takeaway is not that the industry has solved its biggest challenges, but that it is entering a new phase. The foundational pieces are being built, expectations are rising, and the focus is shifting from possibility to execution. The next chapter will depend less on vision and more on whether stakeholders can align, operationalize, and follow through on the work already in motion.
0:01
You are listening to the Dish on Health IT, brought to you by Point-of-Care Partners, a leading health IT consultancy.
0:08
Each episode will feature a rotating panel of senior consultants and guests who will talk about trends and innovations and health IT, while also highlighting how organizations can leverage these advances to solve their business problems.
0:21
In this episode of The Dish on Health IT, host Tony Schueth is joined by key subject matter experts from across Point-of-Care Partners to reflect on the major signals coming out of HIMS 26 following a week of conversations and sessions in Las Vegas.
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The discussion explores themes that stood out across the conference, from the evolving role of AI and healthcare to the continued push toward interoperability, infrastructure, prior authorization, automation, and the foundational work needed around identity, trust, and data quality.
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We hope you find this episode.
0:52
If there are topics you'd like us to cover on a future episode, visit our podcast page at www.pocp.com under the Insights section and submit a form with your ideas.
1:02
Hello everyone, and welcome to the Dish on Health IT, where we invite innovators and catalysts from across the healthcare IT ecosystem to break down some of the industry's biggest developments.
1:13
I'm Tony Schueth, CEO of Pointed Care Partners, and I'll be your host for today's episode.
1:18
Today, we're doing something we always enjoy after a big conference season.
1:21
We're unpacking some of the most interesting signals, themes, and conversations after the intense whirlwind of HIMSS26.
1:30
For anyone new to the event, HIMSS is one of the largest health IT conferences in the world.
1:35
It brings together providers, pairs and life sciences companies, technology vendors, government agencies and standards organizations to talk about where the industry is headed.
1:45
Several of our team members were on the ground this year, attending sessions, meeting with clients and partners, and generally trying to absorb as much as possible from the whirlwind that is him's.
1:55
Joining me today are three colleagues who were part of those conversations and each bring different perspectives.
2:02
Let's start by having each of you briefly introduce yourself.
2:05
Brian Bamberger, let's start with you.
2:07
Can you give listeners a quick introduction and the perspective you bring to the conversations like this?
2:14
Sure.
2:14
Thanks, Tony.
2:16
I lead the life sciences practice at Point-of-Care Partners, have been doing so for the last 15 years or so, and have participated in many of the launches the Point-of-Care Partners has supported for life science companies and probably around 400 of them over that time.
2:37
And I'm a lifelong life science commercial service provider and consultant analysis, whatever.
2:48
That's my background and my point of view.
2:53
Fantastic.
2:54
And we love your perspective.
2:55
Vanessa, how about you?
2:57
Great, thanks Tony and happy to be here today.
3:00
So I am a leader within Point-of-Care Partners, payer provider and technology.
3:05
So I focus a lot on working across those different sectors of healthcare, both developing standards through multi-stakeholder collaboratives as well as really supporting our clients to operationalize and make real interoperability, not just standing around talking about it because that's the important part.
3:24
So a lot of my work focuses at the intersection of standards, primarily HL7, FHIR, federal and state policy and real world implementation, especially kind of where things get a little messy in there.
3:38
So excited to be here.
3:40
The HIMSS conference last week was inspiring and eventful.
3:44
And there's a really helpful sort of pressure test on, you know, where things are headed within that space.
3:50
So thank you.
3:53
Awesome.
3:53
And and you're right, it does get messy once in a while.
3:56
Brian Dwyer, why don't you run us out?
3:58
OK, my name is Brian Dwyer.
4:00
I'm the business strategy lead here at Point-of-Care Partners.
4:03
I've been here for four years, but for the 30 years prior to that, I've I've been a a kind of go to market executive and a number of health IT software companies, services companies.
4:18
So that's really the perspective I bring.
4:20
I've spent a lot of time in startup and restart mode.
4:23
And I think that, you know, my perspectives are really primarily around how vendors in this space react to an evolving, evolving marketplace, which, as we all know, Healthcare is continually evolving.
4:40
So, so you 2, remember back in the days where we could go to New Orleans and San Antonio and things like that, where we were small enough that we could go to these smaller markets.
4:51
Now we're just, you know, Las Vegas, Orlando and Chicago.
4:55
So you remember those days.
4:59
All right, let's get started, folks.
5:01
One of the keynotes this year was from John McNeil, the former president of Tesla.
5:05
Some attendees initially rolled their eyes at the idea of another tech executive telling healthcare how to fix itself, but the reaction afterward was surprisingly positive.
5:15
His message was less about fixing healthcare and more about innovation, discipline, things like questioning requirements, eliminating unnecessary steps and simplifying processes.
5:25
I'm curious how these ideas resonate in healthcare.
5:29
Brian, I know you attended this session.
5:31
What are your thoughts?
5:32
Brian Bamberger So I was skeptical.
5:36
I was one of those skeptical people like here comes another, you know, guy from outside the industry.
5:43
I think that frankly, his message about rebuilding processes from from the ground up and stripping away all of the preconceived notions that we might have was a was a valuable 1.
5:57
I mean, it's, it was, it was worth the time to to listen and to maybe take some inspiration from it and maybe pause in the coming weeks to say, hey, should we be looking at this, this problem or that problem a little bit differently?
6:13
Yeah.
6:13
You know, maybe the industry looks at the PA process a little more creatively across the board and and that becomes a a, a, a cornerstone or an lasting impact that that presentation had.
6:27
Vanessa, what do you think?
6:29
Yeah.
6:30
So unfortunately I wasn't able to attend the keynote, but the word on the street from a lot of folks that that joined was really that overlying message.
6:39
Brian, you just described, which was where can we simplify, right?
6:43
Let's simplify all these processes.
6:46
Let's take a hard look at not just innovation for the sake of innovating, but I think that bringing outside perspectives outside of healthcare for those of us that have been in healthcare for 20 plus years.
6:58
And I'm probably the the baby in here, no offense to everyone, but you all.
7:03
I'm pleased to be working with so many of you with so much more experience.
7:06
But in my 20 years of experience, you know, Healthcare is very complex.
7:12
And you know, the financial industry, we draw a lot of comparisons to, you know, from Tesla, right, The car industry.
7:18
I actually used a car analogy in my presentation on patient cost transparency on Tuesday at Hymns, just relating to, you know, when you need a repair.
7:29
What does that process look like?
7:31
And how can we simplify that sort of process in healthcare to reduce stress and make it easier to really empower patients and avoid putting some of our healthcare messiness, which is becoming a theme of this podcast, I think messiness, but putting that on the patient.
7:49
And so I think taking that step back and Brian, what you described is really inspiring.
7:54
I think pairing it with John Halamka and his presentation about what they're doing at Mayo with the data that they've been able to, to pull together and the insights that they were able to get was sort of a practical example, you know, theoretical, take the process apart, match it with a, a, some practical examples, some key learnings that they had on, you know, specific diseases and how to extend life from, from looking at the data that's there without having to do a, a multi year clinical trial to, to, to figure some things out.
8:26
So I think it's going to add a lot to the conversations going forward.
8:31
So I love that you raised that.
8:33
I'll just quickly add Tony, that I had the the pleasure of hearing Mickey Tripathi speak on Mayo actually prior to him.
8:39
So I'll keep it short.
8:41
But some of the work that they're doing is just so powerful with AI and being able to detect diseases early on and prevent it.
8:47
And I'm really hopeful that that sort of methodology of leveraging AI to improve health overall makes it throughout our ecosystem, including for reimbursement, which I think will be key to widespread adoption of it.
9:03
Thanks.
9:03
I'm glad you brought up AI because it wouldn't be HIMSS without a dominant theme.
9:07
And again, this year, AI was everywhere and boozing in in different conversations.
9:12
Let's hear briefly from Larry King, VP of Product Innovation at Sure Scripts about AI.
9:18
One of the key themes that you're seeing from this year's hands and fun to walk around.
9:21
You know, one of the things I always like that is what's the keywords on the booth and we're we're just talking about.
9:25
And each year it's always changed and this year, obviously it's AI.
9:29
So, so anything artificial intelligence and huge priority for us and search groups.
9:33
But as we think about it, it really is in terms of kind of products and solutions that are solving patients and providers needs, Prior authorization automation is the one that we're really investing heavily in.
9:41
The last year, in 2025, we launched 83 medications on our automation process and we're seeing incredibly positive results.
9:49
When a prescription hits that workflow, on average 18 seconds is the approval time to turn around and make sure that it goes through and it's using prior resources to pull all the oddities are and hand it over to our PBM partners.
9:59
And say, mixed with the excitement of the problems we can reasonably solve using AI, there was also a lot of anxiety about workforce implications, training, data quality, privacy, and infrastructure demands.
10:11
Vanessa, from your perspective, working on interoperability standards and interacting with a broad mix of stakeholders, tell us about your observations and conversations related to AI.
10:23
Great.
10:23
Thanks, Tony.
10:24
So, you know, I think that Larry had some really great points, right?
10:28
Leveraging AI, seeing it everywhere, you know, I'd like to say that the tone is starting to shift from AI just being this big buzzword to to demonstrations that are actually embedding it in, in workflow use cases and the importance of, you know, training data quality bias, trust in these models.
10:53
It is something that came up a lot, you know, from from an interoperability lens to your question, you know, we can automate around broken data, right?
11:03
You, you are what you eat is, is a little bit of what we heard at the Monday pre conference for interoperability.
11:11
And HIE from Rachel Dunscombe, this new CEO of HL 7 and, you know, fixing this data quality challenge and really, you know, leaning into interoperability and FHIR being the foundation for AI is something that I really heard throughout the hallways at him last week.
11:30
I did as well.
11:31
Thanks, Vanessa, for that observation.
11:33
Now let's hear from the Brians.
11:35
Dwyer, when did you go next from a market strategy perspective?
11:39
What are you using?
11:41
You know, what are you seeing from health tech vendors and health plans?
11:44
Is AI actually changing go to market strategies or is it still mostly positioning?
11:51
So AI definitely was everywhere.
11:56
It seems that every conference it, it just is more and more AIAIAI and a lot of it it's, it's interesting, you know, very interesting applications, some that are designed to interact directly with patients or physicians.
12:14
Some of them have a clinical focus, some of them have kind of focus on efficiency.
12:20
And then there's the as Vanessa alluded to, the, the kind of AI embedded in workflow that is simplifying processes.
12:29
So it's definitely adding value.
12:32
I know by now most of us have used it directly and it's pretty incredible how it's improving efficiency.
12:39
Certainly in my world in terms of go to market, you know, AI, it becomes, you may not remember this, but years ago, probably decades ago when big screen TV's came out, they all advertised being web enables and web enables.
12:58
And there's a little bit of a feel of that, that every booth, you know, has AI in it.
13:04
I go, as I've joked before at other conferences, I go to order a hamburger and it was an AI augmented hamburger, right?
13:11
Everyone's got that.
13:12
But it's interesting from a go to mark perspective.
13:14
I wonder, and I'm not an expert technically, but I wonder if vendors are going to focus on AI in terms of the information that it delivers to the user about their company.
13:30
Are they going to, is there a way to manage it the same way we do search engine optimization, for example, I, that's kind of where my brain went.
13:39
And if that's the case, it's going to, I think it'll lose some of its its charm, right, because it's being manipulated.
13:48
But that remains to be seen.
13:50
What do you think, Bamberger?
13:52
What do you think it does?
13:53
Life sciences?
13:54
Are they thinking about AI?
13:55
And do you agree with what Dwyer just had to say in terms of health information technology, right?
14:03
I think I, I compare, I look back a year at HIMS 25 where AI was magic and it was going to solve all our problems, right?
14:14
And you know, so a year goes by and I think that there's select tools and select jobs that AI is able to incrementally improve individual activities.
14:28
I might call that practical AI.
14:30
So here's a practical AI tool, right?
14:32
A patient summary for a clinician to review and quickly get through all of the notes that were put in there.
14:39
I saw a, and I think it was one of the CMS presentations.
14:43
They talked about an organization who, to relieve the burden on their physicians, hired PAS to work with their physicians to do the documentation.
14:53
And the physicians complained that there was too much documentation, right?
14:58
That that it it just, they were paid.
15:00
You know, it's almost like they were paid by the word and you ended up with voluminous documentation that they couldn't figure out what to do with.
15:06
So then they had to find a tool or a way to summarize it.
15:09
So that wasn't clearly wasn't the answer that because it didn't have the intended effect.
15:13
But the idea that that this that the industry is going to, you know, finally get after prior authorization in a meaningful way with a practical AI set of tools that will extract patient information and address questions from payers and drive that forward seems like it's within reach.
15:36
More so than it was last year when people said AI is here.
15:39
It's gonna solve all our problems, including PA, because a year later, not a whole lot has happened.
15:45
We're starting to see evidence of it in future versions of EHR software.
15:49
There might actually be a better fit for that because it's, it's more practical.
15:54
It's, it's the specific tool that's needed for a, for a specific thing.
15:59
I, I sort of like an AI to a Swiss army knife with 50 little tools in it.
16:04
And you got to figure out what that, what that one little tool is that you've never seen before and, and you may never use, but you know, understanding that that tool is there and it has a purpose is an advantage.
16:15
Figuring out how to use the tool or which tool you need to use to, to move forward would be fantastic as well.
16:21
But underlying all of that is data and data quality.
16:25
I talked with Ed Yorskin, CTO at NCQA.
16:28
Let's listen briefly to what he had to say.
16:30
One of the key themes that we're seeing is around data quality, especially FHIR data quality where we're seeing a lot of effort to, and this is really part of the CMS Align Networks and of TEFKA of how do you ensure high quality data exchange and interoperability.
16:48
I think this is an indicator of how interoperability is really advancing.
16:54
So as as FHIR is advancing, people are now questioning how do I ensure that I'm receiving high quality FHIR data that I can then utilize in digital measurement or for whatever prior authorization.
17:10
So it's really foundational.
17:14
You're going to see everyone's talking about AI.
17:18
There are a variety of uses of AI that I think are are going to be highlighted.
17:22
Some is taking unstructured data and creating it into structured data.
17:28
That's great.
17:29
I think you're, I've been seeing a lot of AI efforts around data quality, identifying signals where you might have bad quality.
17:42
But I think the use case that I'm really excited about for AI is taking unstructured data and turning, turning it into something structured that can then be leveraged in digital measurement, digital quality measurement or prior authorization or any of the other work flows that are being powered by FHIR.
18:01
So I think we can all agree that healthcare has spent years building interoperability infrastructure, FHIR API standards, and data exchange frameworks, but we're still dealing with inconsistent and incomplete data.
18:14
And of course, the point Ed made about the structured versus unstructured.
18:18
Vanessa, first, do you want to react to what was said in the brief interview we just listened to?
18:23
And then please talk about the importance of the work happening around standards like FHIR and initiatives like the accelerators in making AI viable.
18:34
Sure.
18:35
Yeah, I thought that Ed had great points around the importance of data quality and FHIR data quality, right, as we move to a FHIR and interoperable world and the use of those within prior authorization similar to what our our previous Larry was was saying as as well as digital measurement and how we are moving from digital quality measured, you know moving into digital quality measures and that being a really big focus for much of the industry.
19:04
I think, you know, moving from unstructured to structured data, right, similar to what Brian was just describing with prior authorization as we work towards CMS double O 57 and codifying the prior authorization rules, AI can play a really big role there.
19:20
And just making sure that we are, you know, getting it right.
19:24
You know, a FHIR APIs, they they exist, but getting them to a completeness level to a consistency or compliance with the standards like Da Vinci, as you mentioned, Tony, we're still lagging behind there.
19:37
We've got some, some progress to make, lots of bright spots last week at HIMSSwith so many leaders in our industry really implementing this stuff to an accurate level.
19:50
But I'm hopeful that the accelerators like Da Vinci and the Gravity Project and FAST are really going to drive forward the adoption in a in a collaborative and meaningful way so that we're not just defining the standards, but really.
20:07
Forcing that implementation across stakeholders to enable these tools like the Swiss Army knife AI that Brian was describing to really, you know, get the right tool and have it be meaningful.
20:20
So great, great insights from from Ed and from Larry Dwyer.
20:25
You were there when I did the interview with Ed, you know, do you have any observations?
20:30
So, you know, from the, the context of, of Ed's position at NCQA, you know, they're, we're moving away from a kind of a more manual limited sampling methodology for quality measurement for health plans.
20:48
And what what that means is that health plans are going to be gathering quality data from their entire membership because if they don't, they're immediately becoming lowering their denominator so that they're not going to get us high enough of a score.
21:07
And there's a lot, a lot of money at stake.
21:08
But moreover, there's the actual intent, which is assessing the quality of care.
21:15
If the, if the larger volumes of data are collected and there are not assurances that it's of high quality, we don't achieve the goal.
21:26
So that's, you know, it, it's becoming more and more important if we want to get value out of these measurements and all of the more advanced analytical tools that we're have now and we're developing, it's got to be the highest quality data possible.
21:41
I'm really glad you bring it up because I know we've had some engagements with different, you know, payers and technology companies around that data quality and data quality reporting.
21:50
So thanks for bringing that up.
21:52
So one of the strongest signals coming out of HIMS this year was that interoperability moving beyond the vision phase into what people are calling interoperability infrastructure.
22:03
We're not talking about identity framework, directories, consent management, trust framework and network governance.
22:10
Brian Dwyer, how are stakeholders like payers and health tech companies reacting to this new phase of work?
22:17
So, you know, with pointy care partners, we've been working with payers for many, many years on an interoperability strategy.
22:25
So you know, what will this, what, what will this vision look like when we're all kind of connected and data flows more freely?
22:34
We've definitely moved beyond that.
22:36
We've we've set the strategy and now everybody's in execution mode and particularly around prior auth with the deadline looming, you know, at the beginning of 2027.
22:48
So at least in my experience talking to payers that are all about execution right now.
22:53
But there's also a realization that, OK, once we check that box, what opportunities exist for extending the, you know, leveraging the newfound connections to transform our business.
23:08
But also there's another additional recognition that the things that you mentioned, Tony, endpoint directory consent, cybersecurity are really complex problems and they're, I remember years ago that they had the deer in the headlights when we were just considering CMS 0057.
23:28
I think there's a little bit deer in the headlights now about what's next, right?
23:33
And so that'll be interesting to see they, they need more help with strategy would be my answer.
23:40
Vanessa, what's your perspective on this?
23:43
Yeah, I, I think it's dead on.
23:44
You know, interoperability is really transitioning and, and becoming infrastructure.
23:50
And I, I like that, that motto.
23:53
You know, the, the, the key thing here, I think is trust and, and building trust.
24:00
So, you know, healthcare leaders are really recognizing the data exchange requires trust frameworks.
24:07
You know, building on the API is how we all really use those API.
24:11
So focusing on things like digital identity, authentication and authorization, consent and patient preferences, governance frameworks as we think about TEFKA and how they interact with the national ecosystem while recognizing the state and local HI ES or regional HI ES as well, playing different roles and working together and sort of overarching network trust policies.
24:35
And so, you know, I think of HL7 fast FHIR at scale task force that's doing a lot of really great work there across, you know, many of those areas and, and really emphasizing that that trust layer that's going to be essential as we look to the CMS aligned networks, which are really reshaping how we exchange data at a national landscape and our overall ecosystem.
24:59
Let's pivot to life sciences.
25:01
Brian Bamerger, you spent a lot of time looking at how pharma interacts with Ehrs and digital health platforms.
25:07
1 observation coming out of HIMSSis that the pharma strategy is largely set at this point.
25:14
The focus now is on execution, particularly around improving documentation of patient conditions and supporting automated workflows like prior authorization.
25:23
What did you see this year that reinforced or challenged that view?
25:29
So I think the views have been are being reinforced.
25:33
You know, we I spoke earlier about prior authorization of being able to match up and better match the data that exists in the EHR to what the payers are requiring for that authorization.
25:45
And that's an important reconciliation that I think there's enough momentum behind or at least a starting momentum that we're going to see a lot of improvements in, in that area.
25:57
Another area that we do a lot of work in is rare disease.
26:00
And so improving the quality of data, the documentation at the primary care or initial specialist and then being able to transfer that data to a center of excellence, which there might only be 20 or 30 of in the country and being able to progress that patient, these patients are in a diagnostic odyssey.
26:21
It truly is all over the place.
26:23
And, you know, being able to, to reduce that time to get to that center of excellence, to do the testing earlier on and adding structure to it is, is, are all important phases of this work that hopefully we will continue over the, the course of 2026 and into 2027 to be able to shorten to better the, the lives of those patients.
26:46
The, the time it takes to see a specialist is way too long.
26:52
You know, it could be 369 months to get an appointment with a specialist.
26:57
And if they're going to repeat the testing that was done at earlier stages of the patient's odyssey, the diagnostic process, because they don't have access to the data is going to lead to a follow up visit when they have all those results to be able to move all that information forward and come to a conclusion and a treatment plan for that patient.
27:17
And that's, that's a waste of time.
27:19
It's a waste of resources.
27:21
It's not customer focused.
27:23
It's not the, you know, the, the way that the, the Tesla president said that in his presentation, former president said that he that it should be, you know, how do you take it apart to put it back together again?
27:35
And I think that represents a great opportunity to use these tools, to use the interoperability tools and in very targeted ways with new and different data required for each rare disease.
27:50
You know, there hasn't been a need to do test test X or text Y, test Y because there is no requirement, because there is no solution for it.
27:59
There was nothing you would do with it.
28:01
And we're seeing more and more testing need to go in place to be able to identify those subsets of patients for where there's a real treatment available.
28:11
So those kinds of things that's that's really powerful.
28:14
And those kinds of things don't happen without patient identification and matching.
28:18
It's one of those foundational issues that has broad reaching impacts from clinical workflows to patient support programs and the programs that you're talking about, Brian.
28:28
So how big of a barrier is it for life sciences and digital engagement initiatives?
28:35
So after last year's HIMSSwhen AI was going to solve all our problems, one of those AI tools was ambient listening.
28:44
And what we, what we quickly learned is there's a lot that isn't ambient that gets recorded in a visit.
28:52
So it's not the answer to everything.
28:54
It's would it be a help?
28:55
Absolutely.
28:56
But also having some prompts in place so that it's a guided process for the physician, because the the physician may be making observations visually or or with his hands that don't result in anything ambient that need to be recorded.
29:13
So helping physicians to use these tools more effectively is an area that the life sciences industry might actually be able to help promote and, and, and guide providers through so that their ambient listening or their documentation templates are up to date.
29:34
That testing is done earlier in the process to reveal different patients subgroups as they're moving forward.
29:42
Vanessa, I know that the FHIR and Scale task force is doing a lot of work around these identity and patient matching issues that we're talking about, but also on security and consent or no one could be building the foundation of trust since we don't have Janice the fast program manager with us.
30:00
Could you talk a little about that?
30:03
Sure.
30:03
So, you know, I think patient identity came up a lot because it, it really does under underpin everything that, you know, AI accuracy, patient engagement, being able to get that referral to a specialist, you know, not taking six to nine months to get in there.
30:22
By the time you get through scheduling and everything, which was another key piece that that came up from, from our regulators actually around scheduling, but I digress.
30:32
The, the, the FHIR at scale task force is doing a lot of really great work on identity and, and consent and security and, and really focused on building trust at scale, at network scale and without these sort of shared models with AI on top of it, I think we'll stall.
30:52
So, you know, Fastest is doing a lot of amazing work there and also price transparency and consumer engagement is really important.
31:03
In fact, you had your presentation at HIMS about that.
31:06
So you've been in the forefront of all that and you know what are you seeing?
31:10
Are, is there real momentum?
31:13
You know, it's so great you asked that, Tony, because I actually had the pleasure of doing a HIMSSTV interview as well while on site last week.
31:22
And I was asked that very question, you know, is this thing real?
31:25
Is it gaining momentum?
31:26
What's the, what's the word on the street?
31:28
And so, you know, this year in my presentation, I'd say I've done that.
31:33
This will be my third price and cost transparency presentation at HIMS over the last 5-6 years.
31:41
And this year I had a lot of new faces, probably 200 people in the room and it wasn't a prime time.
31:47
It was during a lunch, people were hungry.
31:50
There are also some really exciting regulatory panels going on at at a similar time.
31:55
And so I, I was pleased with the turn out and the questions we got afterwards that really started to resonate with people.
32:02
Things like, you know, what's, what's the importance of transparency?
32:07
How accurate do we really need to be?
32:09
You know, what's the difference between the online shopping tools where a patient can go see, you know, how much would an MRI be near me at different facilities that are in network versus, you know, I am planning a knee surgery where I'm going to need a device that is nickel free due to an allergy and I have other comorbidities or complications with my heart.
32:31
I'll need some extra testing in advance of the surgery.
32:34
And so how much is this whole, this whole event's going to cost me, right?
32:37
The labs leading up to the surgery, the maybe overnight inpatients stay if there's complications and you know, we'll hold off on the PT afterwards.
32:46
But just thinking about how much that cost, you know, 41% of Americans are actually avoiding care due to fear of costs.
32:56
So whether you're in an area that may be more urban and you have a lot of opportunities to shop around, right?
33:02
That's a clear, clear example of why cost transparency is so important.
33:06
But even in rural settings where you may only have one local facility, you know you're going to get your service there.
33:13
It's very important to empower patients with information so they can effectively plan their finances, their care, everything that they're going to need to make that successful and not have the stress of the unknown going into a large service like that.
33:27
And I think that providers are starting to see that and that's gaining traction.
33:31
They also see that the more they're informed about the cost that their patients will have, they can prescribe, right?
33:38
Whether it be on the life sciences, you know, drug side or or on a regiment for care, something that the patient's actually going to do adhered to, not to mention their own revenue cycle needs of the importance of collecting co-pays and other costs while in the office and payers.
33:55
Absolutely, you're seeing the value of transparency.
33:58
I had the pleasure of presenting with Megan Meyer from Aetna CVS Health company and they talked a lot about how, you know, we know the No Surprises Act is coming and the work of Da Vinci patient cost transparency, supporting that.
34:11
But more importantly, this is just an important thing for them to do for their members to educate them and help them be informed to be better stewards of their healthcare dollar, especially in the the ecosystem that we're in.
34:21
That's needs to be very cost conscious.
34:25
It's interesting that you bring up urban versus rural.
34:28
You know, there has been with the big beautiful bill, there was $50 billion with AB set aside for rural health transformation.
34:36
And I know we've been doing a little bit of work in that that area.
34:40
Brian Dwyer, you know, do you have any sort of thoughts about how rural health transformation is evolving and and, you know, how health IT can sort of help with rural health transformation?
34:52
Yeah, I mean, it was definitely a a theme, particularly with the vendors I spoke with.
35:00
I mean, that maybe that's to be expected whenever the government lays out a big kind of bolus of funding, you know, people are going to be interested in how can we earn a piece of that?
35:13
You know, it's a very complex problem and it, it just made it even more important.
35:23
The concepts around that we've been talking about here around interoperability.
35:28
That really is the, the prerequisite to improving the delivery of care in, in, in rural areas.
35:37
I mean, we've been talking about empowering pharmacists to practice at the top of their license In many States and an increasing number of states, pharmacists are able to offer services beyond, you know, dispensing medications and doing vaccines.
35:58
And in rural health communities, there may not be primary care physicians or there may be a shortage of them.
36:05
And so those many folks are going without, you know, that that's that foundational care that people who live in more populous regions enjoy.
36:16
But there's a requirement there.
36:18
There's a lot of requirements around business model and about, you know, just getting pharmacists and payers aligned.
36:25
But there needs to be a data flow.
36:27
And without that interoperability and again, high quality data, it's just not going to work.
36:33
It's because it's going to be money spent without a positive impact.
36:38
So go ahead, Vanessa, if I could add to that, you know, I think you said some really important things there, Brian and I want to just so on Monday at HIMSSat the pre conference centered around interoperability and HIE, we did hear from a panel including a physician and and NCPDP really talking about the opportunity for communities to engage their local pharmacists.
37:06
And an example was given where in a value based care arrangement, a local provider was struggling to close care gaps, blood pressures, HBA 1C tests.
37:21
And they worked with their local pharmacist to say, hey, if these if this, you know, list of patients comes in, can you grab a blood pressure from them or an HVA 1C.
37:31
And they were able to significantly decrease the gaps in care that they had for those measures, as well as improve their populations health.
37:40
I think this rural health transformation money that is coming, you know, it's, it's five years, use it or lose it.
37:47
That's not a lot of time to spend a whole boatload of money, as you mentioned, Tony.
37:52
And so really making that impactful is, is going to be essential for these communities.
37:57
So figuring out how to get the data flowing with standards, you know, I sat in on on a workshop that Lauren Riplinger from AHIMA was Co leading around social determinants of health data and what some of the barriers were to really improving the ecosystem there, you know, in communities and helping people access the care that they need and addressing that 80% of health that isn't in a care setting, right.
38:29
And you know, the, the big outcome for me, every single table at this workshop had something to say that could be solved with exchanging that data that you're describing, Brian.
38:40
And doing it in a standard way is going to make it, you know, more efficient and more effective because come five years from now, there's, there's going to be an expectation to do more with less.
38:51
And so I think it's important that we we find a way through this, You know, closed loop referrals is a good start.
38:57
Go see the gravity project.
38:59
And we just did a white paper about, about advanced pharmacy practice.
39:04
And what we observed and learned is that payers will pay pharmacists for providing clinical services.
39:11
They are doing it right now.
39:13
It just hasn't scaled.
39:15
And one of the reasons that it hasn't scaled is because there hasn't been a concentration of effort in certain geographic areas.
39:22
And So what we're seeing and where we think there's a lot of promise is from these rural health transformation grants and sort of helping sort of get everybody on the same page and facilitate and encourage that growth and that opportunity.
39:36
We identified 6 use cases in that some some of which you just identified, Vanessa.
39:42
There are some others that are extremely valuable and we think it's a huge opportunity.
39:48
But let's pivot and let's move on.
39:50
Let's talk about the human side of technology.
39:53
One of the more interesting observations from the week had less to do with just technology.
39:58
Despite all of the AI hype and flashy exhibits, many of the most meaningful conversations people reported were deeply personal discussions about the future of work and certainty and purpose.
40:10
How do we as humans beings benefit from this technology?
40:14
How does it impact day-to-day life or workflow?
40:18
In a strange way, the more technology accelerates, the more human these conversations become.
40:24
Did any of you feel that dynamic during this conference?
40:27
Vanessa, let's start with you.
40:29
Yeah, So I think it's an excellent point.
40:32
You know, we should not be talking about AI without talking about the importance of humans and where humans need to be in that ecosystem as we continue to leverage tools for purpose, as Brian Bamberger was mentioning earlier.
40:47
And so, you know, I think it's a healthy fear, right?
40:51
Change is hard and, and, you know, in inspecting what that looks like and really having an impact on the the workforce is essential.
41:01
I had the the privilege of sitting in on a a panel discussion with one of our local in Massachusetts, FQHC's North Shore Community Health, and the leader there talked about leveraging LLM large language models for addressing delays and referrals.
41:24
And it took him about 6 to 8 months to get the workforce buy in on how to use these tools and to use them effectively.
41:34
And I think that that's an important piece to implementing any new technology, especially AI, where we need to build the trust for it so that the human change enabled by that technology is how we should be thinking about this.
41:49
And I think that echoed through the hallways last week.
41:52
Vambergard Dwyer, do you guys have any observations?
41:58
Yeah, I mean, so sorry, Brian.
42:00
Go ahead, Brian.
42:02
Yeah, I mean, rock, paper, scissors.
42:04
Yeah, exactly.
42:06
I I had a lot of conversations at HIMSSand Beyond about this topic.
42:11
You know, clearly people, patients don't want they, they always they want a doctor in the decision making when it comes to their healthcare.
42:22
They don't want, you know, AI just kind of acting on its own.
42:25
There's there's definitely some fear around that and and you can you can understand why.
42:31
I mean, it's kind of a block black box element to it.
42:35
But beyond that, there's a lot of talk about, you know, what's the societal impact going to be, which is perhaps a, you know, conversation for another day.
42:43
But clearly some segment of work is going to be shifted to to AII mean.
42:50
It's just obvious.
42:51
And so then what happens to folks that did that work?
42:55
Economies have been through that before.
42:57
I mean, you know, when when when Henry Ford invented the the, the, what do you call it that?
43:06
Yeah, the the, the thank you.
43:09
The production line.
43:09
I'm sorry, English as my second language today.
43:11
You know, you didn't envision robots, right?
43:15
But now robots build cars.
43:17
Now did that 'cause a you know, a disruption?
43:19
Yeah.
43:20
Did it, You know, did it create a class of people who have no work?
43:25
No, I don't think it did that.
43:26
People shifted.
43:28
But with AI, it's a little bit more, and I think it's gonna create some really interesting conversations about what as a society we do when, when OK, Rock Bamberger from Rock, Paper, scissors, it's your turn.
43:41
So the there's a segment of the population, probably a pretty big segment that would rather make an appointment with a physician or for a procedure via text message, then pressing 3 for this and two for that and one for this and sitting on hold.
44:02
And you know, so that, you know, I think people are getting used to that.
44:07
And that is where the marketplace is accelerating in terms of, you know, agentic workforces, you know, that that can handle mundane tasks more efficiently than a team of people.
44:21
I think in health IT, some of the missing components were in the first versions of price transparency in EHRS, first version of PA, in EHRS, maybe they missed the mark, maybe the marketplace wasn't ready for it.
44:40
I think we're seeing second versions of those tools come out that are better designed, better presented, more refined in terms of the responses that are coming back and a a better opportunity to accelerate healthcare.
44:57
So I think there's some key learnings that hopefully we don't repeat with the next thing that gets automated that we get it right the first time versus having something in there, you know, uptake of real time prescription information in Ehrs in terms of having the technology in place was very dramatic use of that information not so dramatic, you know, and you know, finding the right times in the and bringing people along with that and framing it up with the right conversations and and the right use cases will really be important in the future.
45:32
As we find more things to do in, in terms of helping doctors and clinicians with documentation that needs to be added to the patient record to further identify subgroups of patients that might be appropriate for various treatments, etcetera.
45:48
Well, well said.
45:50
So as we wrap up, I'd like each of you to take a closing question.
45:55
If you had to pick one signal from Hims that the industry should be a paying attention to for the next 12 to 18 months, what would it be?
46:04
Bamberger, you just finished.
46:05
So let's start with you.
46:07
I think the thing I came away with is PA is ready to go.
46:26
And, and I, and I think that it's still going to take more work.
46:32
It's not not saying it's, it's, you know, there's a magic wand or there's magic going to happen.
46:37
It's going to take reconciliation and work on the payer side.
46:40
And on the provider side, the payers to kind of standardize what it is they're looking for and produce criteria.
46:46
And then on the provider side, having the documentation in place to resolve it in a, in a, in a, an expeditious way.
46:55
Vanessa, I don't it sounded like maybe you didn't exactly agree with what Brian was saying.
46:59
I you your radar is dead on, Tony.
47:02
So I love to hear that you think prior authorization is fixed.
47:07
Brian, that's music to my ears.
47:09
I will just share.
47:10
I was in line at A at something at hims and a random person behind me and I sparked up a conversation and Da Vinci came up and she was like, Oh yeah, everybody knows Da Vinci.
47:22
Like it's become a household name, which was very cool to hear.
47:26
I think with the regulation, it's definitely on its way.
47:30
I do agree that on the pharmacy side, right, the NCPDP standards have been around.
47:35
They are, you know, working very well.
47:38
On the medical benefit side, we are on our way absolutely bridging the two together for a seamless experience for providers.
47:50
I think is, is our next generation is where we really need to work.
47:54
And we're starting to see that in some really great pockets like here in Massachusetts, some sort of trailblazing a little bit.
48:00
So there's a lot of exciting stuff to come.
48:03
I think we are fully on the road to fixing it.
48:06
So agree in that sense, Tony, my, my biggest take away here and, and looking ahead 12 to 18 months to answer your question here is, you know, I think interoperability and AI and policy, right, are really converging and coming together at national and local, even rural levels.
48:30
And so seeing all of that together and, and thinking about interoperability as an infrastructure and getting data flowing, figuring out how to get it at a higher quality to really enable workflow and meaningful change for patients is, is sort of the, the overarching theme that I saw at HIMS.
48:51
And is, is what we all need to be marching towards and focused on over the next year to, to five years.
48:58
And I'm going to jump in.
48:59
So I'm the facilitator and I'm supposed to ask you guys questions, but I'm going to jump in and I'm going to say prior auth we've made a significant amount of progress on.
49:08
But we just did some research last fall with in Massachusetts with the Massachusetts Health Data Consortium.
49:15
And what we found is that there are still gaps.
49:18
And So what Ross Martin, who I've been working on with prior auth for two decades now are talking about is sort of the last mile.
49:26
And that's where we are.
49:27
We have to finish what we started and there's still some steps that we need to take to sort of finish this out.
49:33
And we're working with Massachusetts, did Data Health Consortium and other stakeholders to do that.
49:39
And I think we're getting there, but we still haven't quite got there, got completely where we need to go.
49:45
Brian Dwyer, do you have any sort of observations about prior authorization and or you know, what do you think are the next themes for the next 12 to 8 months coming out of HIMS?
49:56
I mean, one thing I left with was a realization that there's a lot of uncertainty around how data will flow like in a macro level.
50:06
Like, you know, progress in healthcare just seems slower than in other industries, I think because incentives are often misaligned between stakeholders.
50:16
And if you look at, you know, the evolution of TEFKA, for example, and then you've got CMS aligned networks and we had HI ES before that there.
50:27
You know, it's unclear as to how you know what that you talk about the last mile, what's what's going to win.
50:34
You know, the EHR vendors, some more than others have a vested interest.
50:41
TEFKA that's certainly the Q hens have an interest.
50:44
It'll be interesting to see how that plays out.
50:48
Yes, it will.
50:49
The, the, the one more thing I observed and it's really kind of on the, the payer side at least is that there still are kind of silos in, in payer organizations that I think are slowing the evolution of techno healthcare, you know, information technology and that require leadership to kind of breakthrough and, and create momentum.
51:14
So I think there's a lot of box checking still going on, but to get to that next level and apply the new found capabilities that that were really stimulated by the government for business transformation, that remains to be seen.
51:29
Also, I agree with you and we are not a box checking consultancy.
51:35
We are all about, you know what, what else can you do?
51:38
What how can you get a strategic advantage, competitive advantage?
51:42
How can you look at these things strategically?
51:45
And I agree with you on that observation.
51:48
So Brian, Vanessa, and Brian, thank you for joining me today and sharing your insights from Hims.
51:53
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52:06
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52:18
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52:24
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