HIStalk Interviews Steve Cagle, CEO, Clearwater

Steve Cagle, MBA is CEO of Clearwater of Nashville, TN.

Tell me about yourself and the company.

I’m the CEO of Clearwater Security and Compliance. We are a national, healthcare-focused cybersecurity compliance and privacy services and software company. We work with healthcare organizations – hospitals, health systems, physician practice management groups, and digital health companies. Really any type of organization that serves healthcare. I’ve been CEO for five years. I have a 20-year background in healthcare.

How do you distinguish between security and compliance?

Compliance and security are very much intertwined, especially in healthcare. Certain regulations, including HIPAA, require organizations to meet certain specifications and standards in order to adhere to those regulations. Some of those of course involve security and privacy. We have other standards and frameworks that we use in those domains to build and execute programs that protect the organization — its data, its patient data, or third-party data — to ensure that it is kept private and secure.

There is some overlap. In healthcare today, compliance is extremely important. But from a security and privacy perspective, we need to go beyond what we see in some of those regulations, and most importantly, build programs that are ensuring that we are taking the appropriate actions that are relevant for the specific organization based on its size and complexity and its contractual agreements with third parties based on other requirements it may have from insurance providers and so on. Most importantly, based on its level of risk and its risk tolerance.

We see organizations getting better at at understanding risk, although not always going as far as they should — understanding risk, evaluating that risk, and then making decisions that are risk-based to secure and protect private information and to protect their organization’s operations from a cyber incident or other type of security incident.

Is ransomware still the predominant risk for providers?

It certainly is a top concern. We see in the headlines repeated ransomware attacks against healthcare. According to the FBI, healthcare is the most targeted industry out of all critical infrastructure industries for ransomware attacks. This year alone, there have been at least 19 attacks on hospitals versus 25 ransomware attacks in all of last year. 

Ransomware is extremely disruptive and dangerous when it comes to healthcare. Organizations aren’t able to deliver services at the same level of quality. It may be that backup systems are ensuring that patient care is of high quality, but we know there’s an impact when you can’t get test results, you have to reschedule procedures, or you have to wait longer to get care..

A good amount of data has come out recently that unfortunately shows that outcomes were impacted and the mortality rate increased following a ransomware attack. Even hospitals that are adjacent to a hospital that was affected by an attack have had overflow, increased wait times, and increased morbidity. There’s real data out there that shows that it is not only an extreme business risk, but also a patient safety risk. It’s a business risk because revenue is impacted. For smaller organizations, a ransomware attack can cause the loss of up to 30% of their total revenue. So from both a patient safety perspective and a business perspective, ransomware is a top concern.

Is email the primary vector of ransomware attacks?

I would clarify that a bit and say that people are the top vector. That could be email business compromise or other types of social engineering attacks. A lot of those attacks are coming through text messaging. Also phone calls, where the person on the other end purports to be somebody that they are not to try to get someone to give them information to further infiltrate the organization. Phishing and other types of social engineering are top concerns.

We have to continue to make sure that people are aware of all those tactics and techniques. We also want to have other types of security controls that limit the impact of a breach. If somebody were to be able to get those credentials, what can they do with them? Do we have controls in place, such as multi-factor authentication? Do we have controls in place that limit the amount of access that individual can get to? We want to have environments that provide for a zero trust approach, that they have to have repeated authentication to access certain applications even if they are able to get into through to a certain point. There has been a lot of focus on that area.

That’s not the only vector. We’ve seen a lot of attacks, especially over the past couple of months, involving zero-day vulnerabilities or other vulnerabilities that have been exploited by bad actors. We have also seen that with third-party breaches, such as the recent MOVEit vulnerability. That has been a huge source of breaches for the healthcare industry over the past couple of months.

Will AI be better for hackers to launch cyberattacks, or will be be of greater benefit for defending organizations from them?

The AI wars have really begun. Artificial intelligence is not necessarily a new thing when it comes to security tools and techniques. There have been advances in applications being able to use those in a security operations center to assist an analyst in diagnosing or responding to a attack, certainly in identifying some sort of incident or potential incident that should be investigated.

But it’s being now used by bad actors to do all sorts of things, such as crafting more convincing email messages to learn about an organization’s defenses and to adjust the way that it is executing those attacks. From a social engineering perspective, it also allows creating deep fakes using video, photographs, and voice to trick people into giving credentials. The ability to detect an attack is getting better, but being able to execute those attacks is also getting more sophisticated. There will be continued advances and an ongoing battle in the world of AI and security.

How well do health systems evaluate the risks that are introduced by their business associates and vendors?

A lot of organizations are aware of the risk. There is more risk in third parties since we are using more third-party applications in healthcare, especially with digital transformation. We’re moving more to the cloud in healthcare. We are sharing information with more third parties, and it’s not just third parties — it’s fourth parties, fifth parties. It’s the whole supply chain. Understanding risk begins with understanding where your data is and where it’s going. Who are your business associates contracting with and how good are their security programs? How good are they assessing risk?

Healthcare is getting better, but the risk and the sophistication are growing  also. We are probably not catching up as fast as we want to consistently across the industry. Many organizations are assessing by sending out a spreadsheet or a questionnaire. Are they asking the right questions? Are they asking those questions at the right level of depth or depth when they are assessing the impact that particular business associate could have? How frequently are they doing it? What are they doing with those responses and how are they tracking?

That’s hard for a lot of organizations. They don’t have the time, resources, or money to do all those things. Some of the clients we’ve worked with get better at by helping to build better programs that optimize the resources. That’s a lot of what risk management is about, especially in healthcare, where there aren’t endless budgets. How do you become more effective at deploying those resources in a way that give you the most bang for your buck? There’s definitely opportunity there and those challenges can be improved or solved by being a bit more optimal in how you assess risk.

Do you see the Federal Trade Commission becoming more aggressive in the non-HIPAA security and privacy aspects of healthcare given its recent activities in consumer privacy and application practices?

Absolutely. The FTC has recently come down with settlements or resolution agreements with healthcare companies that have shared sensitive personal information in violation of FTC regulations. They have also been focused on the health breach notification requirement. They have been very clear that they are looking closely at health apps that might not fall under HIPAA regulations, but certainly could fall potentially under multiple FTC and other privacy regulations. Several fines have been executed this year. They have also asked for comments on updating some of the rules that are in place already.

Recently there was the joint notice that was sent out to about 130 hospitals between the HHS Office for Civil Rights and FTC, warning those hospitals and also telehealth providers about privacy and security risks from online tracking technologies. Office for Civil Rights had also issued guidance in December. There’s a lot of attention on on how information is being shared through the pixel and other tracking technologies with organizations like Google, Facebook, and other advertisers and marketers, how that information is being used internally and to ensure that it isn’t being used in an inappropriate way. I think we are likely to see additional action taking place from FTC and potentially from OCR as well. 

What are the challenges for health systems in recruiting or retaining cybersecurity expertise?

It’s definitely a challenge, and has been for a long time. There are only so many people qualified for these roles, and healthcare has been challenged with having the resources and the dollars available to be competitive in many cases. Some organizations are in areas where there just isn’t that talent available at all to begin with.

Healthcare is also unusual in terms of the environment that we are working with from a security perspective. It requires a good understanding of a clinical environment and the technologies, compliance, regulations, and the business of healthcare. It is different when you’re working with patients. A lot of unusual attributes go into making somebody successful in that role. That’s probably why we are seeing a lot of healthcare organizations outsource services that don’t make sense to do directly. 

We hope to see more support from the federal government in providing some of the resources that are needed to train professionals in cybersecurity. There have certainly been some talk about that in the national cybersecurity strategy and some of the legislation that was recently proposed, specifically for rural hospitals. But it’s a huge challenge, and the need for security professionals is only growing. We will continue to see some gaps over the next decade, even as we hopefully begin to bring more talent into cybersecurity.

What will be important in the company’s strategy over the next few years?

Our vision has been to be a market leader in healthcare, cybersecurity, and compliance. For us to continue to do that, going back to the talent question, we have to have the best possible people. We also have to have a good understanding of what the needs are for our clients going into the future. Being a partner and continuing to innovate. 

We always want to be thinking ahead about what our clients are going to need going forward. We spend a lot of time there, developing people, retaining people, and giving back to the industry. We hope that through our work, we can continue to provide insight, information, and sense of community that can help healthcare to work together to solve its cybersecurity challenges.

HIStalk Interviews Ron Remy, CEO, Mobile Heartbeat

Ron Remy, MBA is CEO of Mobile Heartbeat of Waltham, MA.

Tell me about yourself and the company.

Mobile Heartbeat is in the clinical communication and collaboration space, which is being renamed as care team collaboration as the market is changing. We’ve been in the business since 2011 with our existing product line. I’ve been the CEO since 2013 and been involved since 2011. We were acquired by a public company back in 2016 and have been a part of them for almost seven years now. We are fully deployed in the market with over 260,000 monthly users, predominantly clinicians in acute care facilities. We have been on premise and are in the process of coming out with our first cloud-based platform.

I have a background in electrical engineering, which is surprisingly pretty useful in the software space, and a minor in computer science, which back in the day was an interesting field that was relatively new.

How did the business change with the pandemic?

It was fascinating, particularly in the first six months. Clients that were fully deployed were really grateful that they had deployed communication capabilities in their facilities. Clients that had partially deployed were calling us and asking us to speed up the process of getting them fully deployed, which was challenging because getting on site in some of these facilities for our staff was not an easy task pre-vaccination. Those that were in the process of evaluating new technology acquisitions — not just us, but anything that was new technology — those opportunities just ground to a halt because there was so much they had to do. 

Our existing clients were extremely happy, and we made sure that we were there to support them to keep things running. It was a core to them being able to treat patients effectively. For those that were partially deployed, we sped up the deployments. They saw the value from the places that they had rolled out smartphones and our software, and they wanted it everywhere. Those that hadn’t made a decision to deploy this new technology just stopped. They couldn’t take on any new projects. That lasted until a year or 18 months ago and was a pretty consistent trend.

It works like this in our experience. A health system decides to deploy smartphones to its staff. They do analysis to determine how many smartphones to buy, how many units they have, and how many folks they want to give access to this technology. They put the phones in place and then look at one of the communication companies, Mobile Heartbeat being one of those, as a vendor of choice. They deploy, because the first tool that they need is a communication tool. That’s obvious. Immediately after the tool is deployed, they start seeing some pretty good return on their investment. Then they look at other capabilities that they can put on their smartphones to enhance the clinician experience, improve patient care, or decrease errors.

It’s fascinating how our clients have integrated different pieces of technology onto these smartphones, using Mobile Heartbeat software to glue them all together. That trend is accelerating, and we have clients that are making these integrations on their own. We don’t even know that they’ve integrated other products into our own because they have become so good at it. I’m excited about the trend of the in industry going forward because clients see this as a future-proof path to providing better care and providing a better experience for their clinicians. That’s what we set out to do back in 2011, and we are seeing that come to fruition. The pandemic accelerated how clients pushed their smartphones to their highest capability.

We saw during the pandemic that clinicians and then patients were untethered from traditional locations. How has that changed your strategy?

It changes it in one big aspect for us, which is that we’ve supported the telecare side of telehealth predominantly. For remote nursing or central monitoring, we’ve become the endpoint for those folks that are doing the remote monitoring to message and communicate with the actual point-of-care caregivers. 

Take a central monitoring scenario. You have a technician, nurse, or other clinician who is monitoring a number of patients. Suddenly, they notice something about a patient. They have to immediately get that information to the caregiver who is most likely to provide care for that specific patient. They need to communicate quickly and efficiently, and they can’t be searching around for the right person. 

In that scenario, the technology that Mobile Heartbeat produces has become a critical component of those systems. That has been the biggest change. The pandemic has sped up those telemonitoring scenarios. I believe that virtual nursing will be the next big trend, providing nursing care without being in the room all the time, but still with a presence in the room. 

What have you learned from analyzing how caregivers use messaging and mobile devices?

The first thing that you learn early on in deploying smartphones and communication capability is that you need to think of it as an enterprise product. Not just from a product standpoint, but from a value standpoint for an acute care hospital or system. Metcalfe’s Law was proposed in the early 1980s by Bob Metcalfe, one of the co-founders of 3Com. His law states that the value of your communication network is equal to the square of the number of endpoints on that network. It dates back to the days of fax machines being replaced by a 3Com network. The value of your network grows exponentially as more people can use it to communicate with one another.

A healthcare system’s investment in communication technology becomes exponentially more valuable, and your ROI increases, as you put more people on the network to communicate with one another. You‘ll see challenges if you only do one unit versus the entire hospital so that the whole hospital can communicate with one another. That’s the biggest lesson that we got from the earliest days of Mobile Heartbeat. We are seeing this come back 10 years later as we talk about new technologies going out into the hands of clinicians, making sure that that network grows and includes the entire continuum of care.

It’s not just those inside the hospital. Now it is the at-home capability of a physician who may be a referring physician and isn’t part of the hospital system. How do we bring them into the communication network? You’re going to make a big investment, so you want to make sure that the ROI is as high as possible for your system. You have to pick carefully which projects to fund, the ones that have real value to your patients and your staff.

When do collaborating caregivers prefer a synchronous voice call versus asynchronous texting?

That differentiation started immediately with our first customers. Our analytics tell us who is who is texting who, who is calling who. We can see it over time. Put an asynchronous communication system in place in a hospital, with smartphones and Mobile Heartbeat software, and the communication paths won’t be what you expect at all if you’ve enabled other parts of your facility. Those paths will be much broader than you expected. It’s not just physician to physician or nurse to nurse. There’s a lot more people involved, such as pharmacy, respiratory, and PT, that are key parts of the care of a patient.

The second thing you start seeing is that the trend to move to asynchronous happens immediately. People realize the value of sending you a message to read when you have time versus a phone call that interrupts whatever you’re doing. The value of asynchronous communication is immediately recognized, but it has a fascinating secondary effect, which is that once people are comfortable asynchronous communication — a phone call, a synchronous outreach via phone call — the recipient knows that that is valuable. They know that that’s important, because otherwise it would have been a text. The likelihood of the recipient picking up the call and actually starting a conversation is much higher because there’s a confidence level that you’re only calling me if you need me right now. 

That has an improvement on your overall communications capacity and the way people use the different tools and the best path. Asynchronous if you don’t meet need me immediately, synchronous if you need me immediately. Your chances of the communication being correct and actually occurring is much higher. I found that fascinating early on, watching the phone calls drop and the text messages grow. Then going back six months later and interviewing the clinicians, who say, those phone calls are still critical to us. When something is really needed, someone hops on the phone and I always answer, where before I would let things go to voicemail. That’s a fascinating change in human behavior based on new technology.

Are messages escalated or alerted if they aren’t delivered or answered?

The alerting capability is pretty much in place today. What will be fascinating in the future is the ability of AI tools to make sure that these orders workflows are done, they’re done in the right order, and that people are reminded if they’ve not completed.

The digital playbook for a stroke stroke patient is different from hospital to hospital. If everyone is in a channel that has access to the digital playbook, it will be followed. You’re making sure that everyone takes care of their steps in the playbook, and you’re using some assistive AI technology to predict what the next step should be. That’s a big plus and that is a big win for the patient, the hospital, and the healthcare system. It’s a really good use of new artificial intelligence technology. I think we will see that coming relatively soon. 

Alerting when things don’t happen properly, if messages don’t get sent, is already pretty much there. It’s the keeping track of what should be done in a playbook manner for each patient and for each condition that will be the future.

Are health systems doing anything to integrate messaging with the EHR?

Almost everyone stores the actual messages, archiving them or keeping them in a offsite facility. They choose how to long to hold this. But very few want this to be a part of the medical record, for good reason. In many cases, these are conversations happening between clinicians. It’s like a hallway conversation. Would you really want every hallway conversation written into the medical record?

There are places where you need to be written in, and other places where you need it to be accessed down the road, but you’re going to clutter up a medical record with an awful lot of chatter around a patient if you wrote every conversation into the record. That being said, you may want to access it at a future date, so you need it to be archived, but you don’t want to bring back hundreds of pages of conversation in the medical record around the patient. You’re asking people to search through a lot of data for limited value.

Phone use went from calls to texts and then to two-way video like FaceTime. Are you seeing health system demand for that video capability?

There is demand, and we are moving down that path. The big use case is, “I need to show you something, but you’re not with me at the moment.” That’s the use case of video. You and I are working together. We have a patient or something of interest in common. We are in different facilities across town, you need to show me something, and I can’t be there standing next to you.

The video will give that opportunity. You have a smartphone in your hands that has camera capability. I can receive it. I can look at something with you on using the voice side of it. I can illustrate what I am seeing, ask for an opinion, or let someone know of something that will interest them that they should be aware of.

The challenge is that video is bandwidth heavy, and wireless requirements in healthcare systems are growing exponentially. If you’re going to add a lot of video onto your network,you’ll have to do some physical infrastructure planning to support it.

You have an unusual perspective in being a vendor that is owned by hospital operator HCA. How is the business environment changing for digital health companies?

I’m fortunate, and our team here is fortunate, to see how our parent company operates and how they make decisions around not only acquiring technology, but also business decisions around staffing and growing the business into different areas. 

One trend that doesn’t seem to be going away, both in our world but also in that of our customers, is the pressure on staffing and cost. Staffing costs are going up, and you have a couple of choices to try to address that. One is to hire more staff, which is difficult because the people just aren’t there. If you look at the number of nurses entering and leaving the profession, you have a potential 10 to 20% staffing gap in five years in just that individual role alone. Roll that across your whole system and that’s a pretty big gap. 

You can’t hire your way out of the problem, so what can you do? You can decrease the quality of patient care by assigning more patients to each caregiver, but that’s not a very good thing when the quality of care begins to slip. Now you look at other ways of mitigating this issue, and technology plays a role. It’s not a panacea. It won’t solve every problem. But it certainly serves a role, along with making operational changes. 

If you can reduce operational challenges using technology — make the clinician available to the patient more frequently or cut down their non-productive time so that they are practicing medicine instead of standing in front of a workstation on wheels – you have a chance of solving this problem. We are  looking at the operational side of the clinician’s world and how our communication capabilities can improve it. How can we make them more efficient? How can we increase their job satisfaction? How can we increase their time spent with patients and decrease the time they spend on administrative tasks?

Everything we are working on is aimed at that. It’s a problem we see both in our parent company and across the industry. That problem of staff cost and shortages is just not going away.

HIStalk Interviews Bart Howe, CEO, HealthMark Group

Bart Howe, MBA is CEO of HealthMark Group of Dallas, TX. He is also president of the Association of Health Information Outsourcing Services (AHIOS).

Tell me about yourself and the company.

I’m a problem solver. I like to work on big projects. I started in finance and quickly determined that my entrepreneurial bug was a little too strong to stay put there, so I started a solar energy technology company and worked in molecular diagnostics before getting into my career in health information management.

I’m the CEO of HealthMark Group, which is a digital health information management solution provider that is most known for our work in the secure and digital exchange of medical records. Oftentimes that’s referred to as release-of-information. That function is perceived at times by the rest of the healthcare industry as a bit archaic, but it can, and has, benefited greatly from the evolution of technology and the way that we maintain records and transmit records. HealthMark is committed to changing that dynamic by providing technology that drives digital self-service and immediate access to patient health information.

I’m an unapologetic patient advocate, so I’m always trying to think from the patient’s perspective. I am a consumer of healthcare, as are all of the end users of the clients that we serve. I always try to have my patient perspective hat on when we’re looking at how we can do things different and better at HealthMark.

I am also, as of a few months ago, president of the national industry association that represents release-of-information vendors. It’s called AHIOS, the Association of Health Information Outsourcing Services. In that, I take a pretty active role in speaking with regulators and legislators around the evolution of the health information management industry from a regulatory perspective. There are tons of opportunities to work with ONC, OCR, and even FTC as we see them starting to regulate more in this space, to make sure that we are creating the right pathways and incentives for organizations, providers, and digital health app developers to engage more in the interoperability solutions of the future. I’m a believer, and I think that opportunities are on the horizon that people don’t even realize exist yet in terms of what can happen when information flows more freely.

How has technology changed the release-of-information process over the past five years?

It continues to change regularly, so it has changed quite a bit in the past five years. I’m sure the next five will as well. What drove me to the space was the rapid change in the way that health information is managed and being transmitted.

I had a personal challenge in one of my prior roles. I was at a molecular diagnostics company, and we were pushing the bounds of scientific discovery in some of the tools that we were using to do oncology diagnostics and provide therapeutic guidance. One of the challenges was getting access to the longitudinal patient information to demonstrate that our diagnostic tool was actually generating better outcomes for patients, and therefore should justify better reimbursement. I saw a need for a better solution for accessing and transmitting health records. When I came across HealthMark, it struck a nerve as an opportunity to jump into an industry that is changing quite a bit and that has a lot of opportunities for improvement.

But to answer your question more acutely, the way that it has changed over the past five years is that everything is going faster. Medical records requests take all sorts of shapes and sizes and they come from all sorts of different parties, such as patients, other physician practices, attorneys, and insurance companies. But expectations for turnaround time for delivery of those records have increased dramatically. They will continue to increase until we can truly hit that target that I’m shooting for with our organization, which is immediate. We want to be able to provide immediate access to that medical information for a variety of different purposes while maintaining the security and privacy of that information.

As EMRs have proliferated throughout the healthcare ecosystem, a lot of that information is now stored digitally instead of on paper, where it was copied or scanned and delivered via snail mail. Today, we try to digitize as much of that delivery as possible. You would be surprised how much of that information is still being requested via a snail mail pathway, but in every chance that we get, we’re pushing requesters towards receiving and ingesting that information in a digital form.

The molecular diagnostics example is a near real-time, business-to-business transaction. How you see the line drawn between release-of-information versus interoperability?

That line is blurring entirely, and that is a good thing. From my perspective, the release of information function, again, has historically been perceived as relatively archaic and lagging behind much of the rest of the industry in terms of moving towards interoperability. I would challenge you to look at HealthMark a little bit differently. We are definitely embracing interoperability as a tool to be able to help deliver digital self-service and immediate access to those records.

To your point, we deliver records for both B2B purposes as well as B2C purposes or B-2-patient purposes. It covers all aspects of what we do. I’m incredibly excited about the trajectory of the industry from an interoperability perspective, and I really want HealthMark to be a leader on the forefront of that push.

On the patient side, how has the Cures Act change how patients request and receive access to their medical records?

I don’t think we’ve seen yet the inflection point of adoption that I hope that we will see at some point, in terms of the adoption of FHIR endpoints and the delivery of information through API methods that will enable a digital healthcare app ecosystem that doesn’t yet exist. We certainly have elements of it and we’re starting to see more of it, but we haven’t hit the inflection point yet.

Do hospitals see release-of-information as a necessarily evil or as an opportunity and a touch point for patient engagement?

If they are not looking at it as an opportunity or as a necessary touch point for patient engagement, then they are looking at it the wrong way. It is absolutely one of the areas that can cause the most abrasion between patient and provider if they aren’t given timely access to their information. They certainly need to think about that as a core competency of either their organization or of a partner that they’re working with to help facilitate that information flow as easily and seamlessly as possible. Maybe it used to be viewed as a necessary evil, but certainly it is an opportunity today.

Much of the information requests that the release-of-information association or partners fulfill are still continuity-of-care requests, so a lot of that information used to treat patients is still flowing through those means. It is critical to the patient as well that they get access to that information for those purposes.

You offer services related to the Family and Medical Leave Act. What kind of information requests are involved?

It’s not just FMLA. There are disability requests and requests for other information that require the physician or physician practice to complete information related to that patient’s care or related to that patient’s treatment regimen. It’s not something that you can pull directly out of a discrete data field. It often takes physician know-how of the situation, or specifically what the request is about, to complete that information. We work on behalf of our healthcare provider partners to alleviate some of that administrative burden.

Ultimately, HealthMark is trying to alleviate, across the ecosystem of our clients, the administrative burdens that we see in our US healthcare ecosystem, which is two to three times the administrative burden that we see in other developed nations. We think there are opportunities to streamline a lot of that information flow, and FMLA paperwork is one of them.

There are requests for that paperwork on a regular basis, ranging from simple requests related to a pregnancy or a surgery all the way up to things that are much more complex. Provider practices are required to fulfill that information request on behalf of their patients because it’s necessary, often for the patient to get a paycheck, so it’s critical to that patient experience.

Everything that we work on ultimately drives back to that patient experience. We are completing that paperwork on in conjunction with the provider partners that we work with to make sure that information doesn’t get stuck with the front desk staff or stuck with an MA and ultimately fall to the bottom of the priority list because it doesn’t involve treating a patient right there in front of you. These things are still critically important to the patient. We are helping make sure that we can streamline the flow of that information.

It’s vexing as a patient to go to your regular medical practice that uses an EHR and having a clipboard full of empty forms immediately shoved at you every time, especially when you know that everything you are being asked to write is already on the computer screen five feet from the clipboard. Why does that happen?

Honestly, I ask myself why that is still so often the case. Filling out paper on a clipboard should be a thing of the past. There is virtually no other situation where we complete information on a clipboard. We provide a digital patient intake solution to help streamline the flow of that information. In this case, not out of the EMR or the practice management system, but into it. We are providing a digital experience for patients to be able to bring healthcare into the modern world, into the 21st century of technology adoption.

I understand why there is a laggard nature to the healthcare industry in terms of a adopting technology. It’s a heavily regulated environment where it is difficult to make changes overnight. That has created a situation where healthcare providers are slower to adopt technology than in other industries, but I think we see that changing as well. Certainly with the pandemic, we saw a rapid overnight need to adopt technology for solutions for things that didn’t exist previously. Telemedicine skyrocketed during that period, as did things like digital patient intake, pre-registration forms, and remote check-in opportunities. We are coming along and we are making progress, but it still baffles me when I walk into a healthcare facility and I’m handed the clipboard and a pen.

Where do you see the company in three or four years?

We are going to continue to lean into the interoperability landscape. I know that is a buzzword that has been around for decades, but I hope that we are reaching the inflection point for both technical and regulatory pathways to make true interoperability a reality. There is a ton of potential in things like the Cures Act and TEFCA. As we lean into that, it will open up downstream use cases for organizations like us, where we are a trusted partner of the healthcare providers that we work with and a steward of that most precious protected healthcare information that they hold on behalf of their patients.

As we sit in that position and start to facilitate better, cheaper, faster information flow, that opens up a ton of opportunities downstream for things like analytics and focusing on the potential for using things like AI to provide relevant insights from that data back to the provider and back to driving better treatment outcomes for the patient.

This is stuff that I care deeply about, and as I mentioned at the beginning, I am an unapologetic patient advocate who tries to think about things from the patient perspective and how to make their experience better. A better experience for them is a better outcome for our clients.

HIStalk Interviews Chakri Toleti, CEO, Care.ai

Chakri Toleti is founder and CEO of Care.ai of Orlando, FL.

Tell me about yourself and the company.

This is my fourth gig in the healthcare space. My brother Raj and I have done business together, and this is my own project. I started the business three and a half years ago to bring ambient intelligence to healthcare.

I don’t have a pure technology background or healthcare background. I worked for Disney Ideas, then went to film school. That has nothing to do with any of this stuff, but I always was intrigued with other industries and how they adopt technology to bring process automation and efficiencies to deliver consistent, better solutions. That is my background and my passion.

Looking at healthcare, many processes can be efficiently automated to impact the care delivery process itself. I looked at ambient intelligence and felt that there is a significant gap in healthcare. I saw the transformation that was happening even in your home, like a smart home, the ability to get control of what’s going on in real time. That was the genesis of Care ai.

How will your business change as new types of health-related sensors are developed?

The technology has evolved dramatically. We can deploy high compute engines like GPUs in a smaller form factor with less power consumption. We have several provisional patents in terms of how to scale and do edge computing in a much more efficient way in the healthcare setting. We can roll out across tens of thousands of rooms without bringing the network down. We are really good at being able to get the appropriate data, clean data, to run these AI models on the edge.

If you want to draw parallels, look at Nuance’s 10- or 15-year-old technology with Dragon. When you have enterprises like Google, Microsoft, and Amazon spending billions of dollars on NLP-based workflows, that has become commoditized dramatically. Amazing large language models are being deployed in enterprise settings to be able to deliver the same kind of results, and much better results, for a fraction of the cost. That’s the transformation that is happening.

What we’ve built is bringing these operational clinical workflows together, building a scalable command center, and shifting the paradigm of what clinical data capture or operational data capture will look like in healthcare.

A lot of the old-school monitoring in the ICU went beyond sensor-based instrument alarms and instead involved an experienced clinician asking questions or observing the patient. Can value be added by analyzing audio and visual information?

That’s exactly what we do. Imagine a Tesla car sitting in a room. That’s what we’ve built — inferencing, audio-visual, three-dimensional volumetric data to give you a lot more information of what’s going on, how many people are in the room, how long did they stay there, did the patient eat food, how long have they been sleeping in the same position. All the environmental data, coupled with the data capture of every action that’s happening, is the fundamental difference that we are enabling to truly build a smart patient room.

I wake up every day from the dream that I’m going to kill the EMR. EMRs are the most antiquated way of data capture. They are required, but were built for a specific purpose 10, 15, or 20 years ago with an archaic way of data capture. It would be unthinkable if workers in an Amazon warehouse had to stop and input information about everything that they are doing. Yet we take the most talented and expensive resources in healthcare and make them do data entry in a crappy interface with all these clicks, forms, and flows in a complex form of data capture. All it is doing is generating a bill.

Obviously the clinical data is important, but we all know that every unit in every health system has skewed dark data. If you look at the respiratory rate, it is magically the same, 14 or something, in every unit. It’s like muscle memory. It gets worsen as you go through the ecosystem. Post-acute reimbursement is completely based on data capture. They have something called ADLs, activities of daily living. They have to capture all of that, and it’s a manual process.

Some hospitals have created command centers and are interested in remote patient monitoring. What will the hospital of the future look like given the opportunity to separate the services from the hardware capabilities of the room or having people enter the room regularly?

An accelerator for us is that the staffing shortage and the staffing crisis is elevating the need for solutions like these that can give the bedside care teams the scale that they need. Also, they have to think outside the box. The EMR cannot be the universe of every way of capturing information. Every health system recognizes that, and that’s why we are getting traction.

Also, the technology has become democratized, in that the cost to deploy these solutions is fractional. If you go to most of these organizations, they are still moving computers-on-wheels from older companies from one room to another, paying $10,000 or $30,000 per cart. For a fraction of that cost, we can wire up a true smart patient room that gives you real-time visibility into operational and clinical workflows with the ability to analyze audio, video, three-dimensional volumetric data visualization and capture of that information with super high accuracy.

How will AI change the way we think about healthcare software and how technology is developed or deployed?

It will be a once in a generation change in terms of how you look at delivering care. There are two sides to it. One is innovation, drug discovery and all the other aspects of AI. But when it comes to the four walls of operations of a hospital or post-acute facility itself, real-time AI will fundamentally change how we monitor and how we deliver care in an efficient way and at higher standards of quality. If you look at generative AI and all the innovation that is happening at an accelerated rate, healthcare will have a huge impact on that.

When we talk about AI in a healthcare setting, people talk about taking a few algorithms and applying them to the dataset that we have. That is good, and you need it. But a lot of the data is dark data. It’s skewed. How did we capture that information? Is it accurate? You have to go back and look at how you bring true, clean data into the system. 

Imagine a self-driving car. They send out these cars, capture real-time information about the roads, then teach the neural nets to look for the most efficient way of driving. More and more you will see those kind of implementations and adoption of AI into healthcare in a different way. It could be a radiology or a CT scan that’s happening in real time. The ability for it to recalibrate itself using AI to get more accurate scans will also be a part of the entire ecosystem. Rather than just, hey, I’ve scanned, so let’s apply AI to identify abnormalities. There are different aspects of AI that have not fully been leveraged in healthcare settings.

How should a mid-sized healthcare technology company look at incorporating large language models that are changing so quickly?

We should be looking at a problem and then seeing if applying AI to that problem will solve it. Does it even require AI? Once you have identified a problem like nursing shortages — we have a virtual nursing infrastructure — but then how do you look at AI being more integrated into the platform? Understanding the workflows within healthcare and using the frameworks with the right set of data to impact that workflow. That work will be a key way for these organizations to succeed. 

Cerner or Epic were designed before a lot of these innovations happened. For example, for controlled substances, two people have to sign off in the room, logged into the EHR on the same computer. That was designed like 10 years ago. There’s no way for one person to be virtually beaming in and one person in the room. EMRs don’t have the ability to do it. They would have to re-architect everything in the new way of doing things. That would be a big lift for them. 

Newer companies have an advantage to look at a clean slate and say, what’s the most effective way in today’s technology landscape to implement the most effective solution for that problem? If they truly understand what real-time AI can do, then the sky’s the limit to transform healthcare.

You started the company right before the pandemic began. What is different now about starting, running, and selling a digital health company?

I would strike out the last one. If someone is building something with the objective of selling it, then that’s the wrong way of going about it. You have to solve a problem, and whatever the outcome is, it will be good, whether you sell the company or stay with it. 

The landscape has dramatically changed. For us, we had an advantage in that we started the business when the pandemic hit, which propelled and accelerated our growth. I don’t think I could repeat the same kind of growth again in my career. We were at that inflection point.

Also, health systems have changed their thought process. The pandemic exposed the weaknesses that are inherent in the care delivery system and processes. That is in the forefront of the leaders in these health systems for them to solve. They are much more open to new, innovative companies, so it’s a great time to bring innovative technologies to these institutions that are more open to newer ideas and newer companies to innovate for them. They know that the status quo has a lot of weaknesses that are built into their systems today. It’s a great time if you have the right solution to help them be more efficient and deliver the same or higher standards of care.

What will be key to the company’s strategy in the next three or four years?

It will be extremely important to understand the impact of AI and how it will change the client’s businesses. If companies don’t look at new ways to solve problems, be nimble about it, and adapt aggressively, it will be tough in a dynamic environment. The technology landscape is changing at a much faster pace than we’ve ever seen in our careers. They have to be at the same speed as what the technology is changing. ChatGPT 3.5 versus ChatGPT 4 or Bard are coming up at lightning speed, and startups and new companies that are trying to go to market need to have the same agility.

HIStalk Interviews Patrice Wolfe, CEO, AGS Health

Patrice Wolfe, MBA is CEO of AGS Health of Washington, DC.

Tell me about yourself and the company.

I am a industry veteran. I’ve been in the healthcare space, particularly the healthcare technology space, for over 35 years, and have worked both on the provider and the payer side. I think I’ve seen every possible permutation of the challenges that we face in this industry in one form or another. I’ve been with AGS for almost four years. I’m so grateful to be in the revenue cycle space because we are at the core of the challenges that health systems are facing. 

AGS is a global provider of revenue cycle products and services, mostly to large health systems, but also we work with a lot of big physician practices and other players in the market.

What is the financial situation of health systems?

It is dire for a lot of health systems. A few dynamics have converged simultaneously. The rise in inflation impacts the cost of goods that hospitals and providers use and the wages they pay. Inflation is impacting margins across the board. Then you add to that the dynamics around clinical staffing and administrative staffing, where we’ve seen huge turnover across the health system space. They are left with fewer people to do the jobs that need to be done. Then when they try to fill these positions, particularly the clinical ones, they can’t find people, so they are using temp staff at triple the cost. You have huge cost pressures from that. 

On top of that, there’s the drop in investment income that some health systems have seen based on the markets. 

The news came out last week that the federal government will be rescinding a lot of the additional Medicaid coverage and other types of protections that were put in place during COVID, so a lot of health systems will be left with even more indigent care. 

The financial pressures are coming from every single angle for providers. We hear it from our customers. We see the anxiety that they have around, how am I going to cut costs? How am I going to increase revenue given all of these headwinds that I’m facing?

How will technology such as robotic process automation, natural language processing, and generative AI contribute to revenue cycle management?

Some of them are a little more near term than others. RPA has probably been around the longest. There are a lot of good use cases for using automation. I see across our customer base plenty of use cases where they’ve brought in automation to do some rote manual activities. We do quite a bit of RPA to drive out some of the  low-value tasks that you don’t need a human to do, so that the humans can focus on the more complex work. The low-hanging fruit has already been plucked in many cases, but there is an endless supply of additional use cases. It’s dependent on the health system’s ability to harness the data from their EHR and other types of systems and have the ability to attach the RPA to whatever the process is that they are focusing on. It’s a lot harder in practice than it sounds when you are planning it out.

There are some fantastic use cases in the HIM or coding area with the greater sophistication that is available in machine learning and natural language processing. You can see 10, 20, even 30% improvement in coding efficiency. With that comes increased revenue, because if you are getting your coding correct, that can then drive more accurate representation of things like case mix index, which then drive higher revenue. 

These types of tools are still in earlier stages of maturity. But with what we are doing in computer-assisted coding, we have some clear examples where customers are generating additional revenue from implementing these types of tools.

A lot of it comes back to data. You have to be able to extract from your EHR all the right information to take advantage of these tools. That is a critical success factor.

We have been playing around with not just ChatGPT, but some of the other OpenAI tools. We’ve implemented a couple of use cases for our internal use. Voice to text is important in the work that we do because we are often calling payers on behalf of our customers. Sometimes we’re on hold for 40 minutes or an hour, and the conversations that are taking place to follow up on claims can be lengthy and complicated. We’ve been able to use some of the OpenAI tools to turn those lengthy voice discussions into text so that we can do better quality assurance on our own folks as they are in these calls. We’ve implemented a few other use cases. There’s a lot of promise here, but I roll my eyes a little bit at some of the statements that are being made about how it’s going to revolutionize healthcare in the near term. I think it’s more of a long-term play.

Assuming that all the important chart information is in digital form, wouldn’t generative AI be ideal for coding and abstracting, perhaps replacing humans in the same way that speech recognition has done? 

Given how long I’ve been in this industry, I have a hard time saying that I think things will be completely eliminated. I can’t believe that we are still using humans to post payments, which should have gone away 15 years ago. 

The promise is there that these tools will be able to take over a good chunk of that work. But we have seen too often that a human is required to do some of the more nuanced review. It may be that AI can eventually code a chart, but the human is most likely going to need to continue to do some of that auditing. There’s a lot of hype around things like autonomous coding in certain discrete specialties like radiology, where the clinical nomenclature is  limited. But at this point, only a subset of those charts are able to make it through the autonomous process. You have to have humans on the back end to take what falls out and to do that auditing. We have the promise to be able to automate far more of this work than we have to date, but as a grizzled industry veteran, I don’t think we will get to that 100% automation level.

Everybody is unhappy with the prior authorization process. Can it be automated or eliminated?

That is probably the single most expensive activity that takes place in the revenue cycle. I’ve seen estimates of $80 for each prior authorization if you add the cost of the payer and provider to adjudicate. That’s a huge pain point, and there will be a lot going on in the industry to address this. My understanding is that Epic has been working on this for a couple of years now and has some payer partners that they are doing some development work with. The EHR is part of the solution, but I don’t think it is going to be able to completely solve that problem. 

Without a doubt, some of these front-end activities are  getting more complex. We hear from our customers that the barrier to prior authorization has only gotten worse since the pandemic. Some of that may be a reflection of staffing and other problems on the payer side. They are having the same kinds of issues providers are with the great resignation and other types of administrative challenges. We are seeing the prior auth space get worse, so any kind of automation that can be done in this area is of enormous importance to providers and to payers. 

It’s a huge pain point to physicians. We are doing patient access work, including prior auth, with one of our customers. Their physicians are unhappy when they get involved in these peer-to-peer conversations with payers, or when they have to re-review the documentation that was submitted. We are doing a lot to try to minimize how much the physician actually has to get involved in these types of interactions, because it takes them away from their core mission, which is to care for patients.

It’s probably not the best example of healthcare consumerism, but how is patient payment processing developing?

This is an area where every single person has a personal opinion. Earlier in my career, when I was running a patient payments business, any time I talked to anyone, they had a story about trying to pay for something or trying to understand what they were supposed to pay for. This is a visceral topic for a lot of people. 

There has been a lot of progress made, particularly around the patient front door type of growth. I see progress in patient registration and all the things that we try to push to the front of the revenue cycle that can and should get done before the patient shows up. Some of the mobile-based and text-based tools that are out there are pretty good. As always, getting them correctly integrated with the EHR is often a problem for these providers.

So many people are comfortable with mobile-based payment activity that it makes me happy when I go to a doctor’s office personally and have to do a mobile-based registration process. There has been good progress made in this area, and while I don’t think we are done yet, we want to meet people where they want to be, and most people want to do mobile-based banking and other kinds of financial activity. I feel fairly hopeful about that.

How have operational and market conditions influenced the appetite for innovation in health systems?

That’s such an important question. In the course of my conversations with our customers, I see two camps. One is that I see the organizations that are using this as an opportunity to double down on innovation, but I would say innovation with clear ROI expectations. What we are trying to do a better job of at AGS is quantifying the revenue impact we are having for our customers. Our space historically has patted itself on the back in terms of its ability to reduce customer expenses, which is a great thing, but that’s not enough right now. In this environment, it’s about how you will positively impact a health system’s revenue. Organizations that are  a little more risk-taking and forward thinking are willing to double down on innovation, but they want to see those metrics, which is completely reasonable.

On the other end of the spectrum, we are seeing health systems that are sitting around the boardroom, with the CEO and CFO saying, “I need $5 million in expense reduction out of you, I need $10 million out of you, and $2 million out of you. I don’t care how you do it, just go out and do it.” In those organizations, we are seeing more things that are retrenchment, such as cutting IT spend or vendor use. That’s a challenging situation, because they will regret some of those cuts two years from now. I completely understand the pressure they are under, but there are wise ways to make those cuts and maybe not so wise ways to make those cuts. It’s a challenging position for a lot of these health system executives.

What is the company’s strategy over the next few years?

A few things really matter to us. Our mission is to drive great financial health of our customer organizations. A few things are top of mind. There is a continued need to bring technology to bear in what has often been an inefficient and human-intensive process. As technology matures, whether that is AI or other types of technology, we want to be there thoughtfully using it on behalf of our customers.

The other thing is that we we are fairly acute care focused. We work with a lot of large specialty physician practices, but mostly large health systems. Many of these health systems don’t just do hospital-based care for their patients. They offer ancillary service lines such as home care, skilled nursing, ambulatory surgery centers, et cetera. We have to continue to think about and define the revenue cycle more holistically on behalf of these organizations, because there are opportunities for them to gain efficiencies and drive more revenue out of some of these other parts of their organizations. Those other parts might use different EHRs. They might be managed completely outside of the standard revenue cycle. There could be some good efficiency gains in some of these other areas over the next few years, particularly as we continue to see consolidation in the market.

HIStalk Interviews Christine Swisher, PhD, Chief Scientific Officer, Project Ronin

Christine Swisher, PhD is chief scientific officer of Project Ronin of San Mateo, CA.

Tell me about yourself and the company.

My background is in healthcare, mostly in oncology, but also in building predictive models and AI as software and as a medical device. I’ve worked at Philips Healthcare, which is in the Fortune 500, as well as several startups. I’ve led from idea to FDA clearance and expansion in the US and in Europe.

I am passionate about responsible AI and what that means, to deliver AI that is impactful in healthcare and that improves the lives of patients at scale.

At Ronin, we are fortunate to have a wonderful network and partners such that we are set up to achieve our mission of improving the life of cancer patients at scale and impacting all four of the Quadruple Aim verticals. We build technology such that an oncologist and the clinical care team that cares for cancer patients can see at a glance, and understand, their patient’s journey. We look through all of the structured data, clinical notes, and documents and bring that forward, so there isn’t that 30 minutes of clicking to prepare for a visit, but help them understand their patient at a glance. We also bring in the patient’s voice to understand what’s happening to the patient outside of the hospital and render that in their clinical workflow.

We have a mobile application that engages patients, not just for having a better understanding of the patient, but to empower clinicians with predictive information so they can take actions earlier and prevent adverse events and avoidable hospitalizations or emergency department visits and also better manage symptoms so that patients can stay on treatment longer.

What is the extent of genetics and genomics data that can be used to make clinical decisions?

A lot of that is about contextualizing that information. There’s a big jump from what scientists have discovered and where we are in this, especially in the genetics field. How do we deliver that to have meaningful outcomes in clinical care? How can we contextualize that information alongside their patient record of what’s happening, their entire patient record such as comorbidities, social determinants of health, and patient-reported outcomes? What’s happening to them at home? How can we bring all that together to have a total patient understanding, including their patient preferences?

With that total patient understanding, we can make the best choice for that particular patient. It’s a critical piece of information, especially things like EGFR mutations that are so impactful for treatment decisions that they can be lifesaving. We need to bring them into care decision making.

ChatGPT feels like an overnight success, but probably isn’t to experts in the field like yourself. How will your work be changed by its capabilities and popularity?

It definitely impacts the work that we do it. In fact, I think it enables the next level of technology if we are thoughtful in how we deliver that.

It didn’t happen overnight from my perspective. In 2012, we witnessed a similar event in AI, where there was a technological breakthrough with convolutional neural networks, rectified linear units, and dropout that allowed us to have computer vision perform as well as humans for general domain tasks in classification. That particular event sparked the deep learning revolution.

From 2012 to 2020, there were about 100 FDA-cleared applications, 88 of which were computer vision or in the radiology space. That happened quickly and the characteristics of these winners that were able to deliver on deep learning at that time. Radiologists, pathologists, and recipients of this technology were skeptical, just as skeptical as they are now.

It’s slightly higher publicity now because so many people are using things like ChatGPT in their work. But it’s a lot of mirroring to what happened in the 2010s, when the AI winners in healthcare did three things. One, they prioritized interpretability and risk mitigation. Two, they focused on super-powering the clinicians versus trying to compete with them, and companies that said they were going to replace a clinician were not successful. Third is that they delivered a complete solution, and those solutions fit seamlessly into the clinical workflow. They delivered on the CDS five rights, which means that it was the right information, the right person, the right format, the right channel, and at the right time. That’s the key to success.

None of those things have really changed about healthcare in the past 10 years. There was a technological breakthrough with the transformer architecture in 2017, and then a new generalizable method, which was GPT- based models. We had a new generation of applications like ChatGPT, Stable Diffusion, Dall-E, and all of these generative AI technologies. It’s very much like what we saw in 2012.

If we can take those learnings about what success looks like, and bring those into how we think about this new innovation or new class of AI-powered applications, we’re going to be a lot more successful. I am really excited about generative AI, but I think that it has to be delivered the right way.

We heard way too much back then about big data, which is rarely mentioned using that name today. Will AI and ML help deliver that promise?

We’ve been doing things that are interesting. AI has helped identify sepsis patients earlier and to identify ischemic strokes so that patients can be treated within the golden hour. It’s been able to better detect breast cancer, lung cancer, and prostate cancer earlier. It’s already impacting people’s lives. That was with big data. It’s already living up to, maybe not at the scale that was predicted, but it is actually improving people’s lives at scale.

Now what we are seeing with this new class is new ways that we can better improve people’s lives. Generative AI can help scientists and researchers better discover new drugs, new treatments, and new therapies for cancer and other diseases.

It’s going to enable a better understanding of the patient’s journey, just like what we are doing at Ronin, being able to dig through the 80% of the EMR that is unstructured data documents, clinical narratives, and notes and have a better understanding of patients at an individual level and at a population level. That means that we are going to be able to better predict things like mortality, progression, adverse events, toxicities from treatment, and acute care utilization like emergency department visits. Then by being able to predict them and see what caused them, we can better inform on actions. I’m really excited about the technology, as long as it’s delivered safely and ethically.

The new book “Redefining the Boundaries of Medicine” notes that medicine is based around huge population studies that may lead to the wrong conclusions when a specific intervention doesn’t appear to be effective collectively, but works on subgroups of patients who share particular circumstances or comorbidities. How would a data scientist look at that issue?

This is very core to our Ronin mission, to deliver care decisions that are personalized to that particular patient versus based on population averages. So many decisions in oncology are based on population averages. By bringing data of what happened to patients like them — what happened in terms of their progression, their quality of life, the toxicities that they experienced — we can look at the patient in a comprehensive way, thinking about their demographics, social determinants of health, their cancer and treatment specific risk factors, their comorbidities, symptoms, active problems, and biomarkers as well.

If we bring that together to then say, what happened to patients like my patient, we can provide more personalized decisions. We can also empower the care team, oncologist, patient, and caregiver with data to make that decision.

Previous technologies were implemented as advisory rather than a closed loop system that would require FDA approval. How prepared is FDA to evaluate AI technologies and are the usual retrospective studies adequate to do so?

I have two answers for that. The first is that regulatory and best practice groups are moving quickly in response to the innovation and excitement around generative AI and AI in general. Three seminal documents were released just in the past few months. The White House delivered a blueprint for an AI bill of rights, NIST delivered their risk management framework, and the Coalition for Health AI delivered their “Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare.”

When you look at these three documents, five themes emerge across them. You need validated, safe, and effective systems. You need protections against bias. You need privacy and security. You need interpretability and explainability. Finally, you need transparency and human factors.

Whether or not it’s FDA-cleared 510 (k) software as a medical device, a CDSS, a CLIA-validated laboratory developed test, or AI for another application that doesn’t fit it under those regulatory guidance, it’s still important that it delivers on those five principles. In fact, those actually expand past healthcare.

Those are the things where we will see guidance from groups like CHAI on how we concretely deliver on those principles. The principles have been defined, and now these groups are working very quickly to define the next steps. I also think that infrastructure cloud vendors and AI tooling vendors will, at some point, start to provide certified tools to companies like Ronin and others to accelerate our ability to deliver AI safely. That’s a huge market opportunity.

AI in healthcare, particularly with our last AI revolution in the 2010s, was most successful when it was partnered with clinicians to make them super-powered clinicians. If you look at other domains, the same thing is true. AI did not replace as many jobs as people thought it would.

You could also look at things like when we went from animators hand drawing to CGI. CGI just expanded the scope of what they could deliver, how productive they could be, and allowed them to work at a higher level with the tedious tasks taken away. It’s the same thing of going from FORTRAN to C++ to Python and how we develop AI.

If we look at how those industries are impacted, there’s as guiding principle that AI empowers people and takes the tedious things off their plate so that they can operate at a higher level and deliver higher quality. That’s true in healthcare as well.

How will the availability of complete, representative, and unbiased training data affect the market for AI technologies?

Protections against bias is a key theme in those three seminal documents that I just talked about, and something that we need to do proactively and continuously. It’s not a one-time event where you look at your patient population, see how it performs in subgroups, and then write it up in a medical journal.

It has to be part of your system, where you are continuously monitoring for bias. Then when you detect a bias incident, you need to have the systems in place to rapidly mitigate that issue. One of solutions is representative data, but we need a three-pronged approach, where the first prong is like the brakes in your car, the second prong is the seatbelt, and the last one is the airbag.

The first prong, our brake, is about preventing any foreseeable bias. So that when you are developing the model, you have representation of the populations that you intend to serve. You have subject matter experts that understand that there isn’t bias built into the actual ground truth data or the data feeding into the model. That the way it is delivered from a user experience will not exacerbate currently existing biases in the system, so that there’s a lot of voice of the customer or human-centric design that has representation of the populations that we intend to serve. That’s the brake.

The seatbelt and the airbag are two pieces. The first is that you need to have proactive and continuous monitoring for bias across important subgroups. Things like social determinants of health. Do they have access to transportation? What about their insurance and demographic groups? We need a comprehensive understanding of the different ways that we could introduce bias that causes harm to different types of groups, then detecting that and being able to diagnose any problem quickly before it causes patient harm.

Then knowing that you have a problem, the next step is to fix the problem, so having the systems in place so you can rapidly retrain a model and you have the technology or ability to mitigate bias quickly. The machine learning operations, MLOps needs both infrastructure and practice to mitigate that and then deliver that fix quickly before there’s patient harm. In addition, there are human factors in how it’s delivered so that you can mitigate risk as well.

IBM Watson Health failed at trying to do years ago what people think is possible now. What has changed?

For those that will be successful, what’s different now is the user experience and real-world validation of the technology. What is the AUC, area under the curve, of a model? All these abstract metrics that AI practitioners tend to focus on … instead of focusing on those, focus on the meaningful measures. Does the AI plus the human better prevent acute unplanned care? Does it keep patients on treatment longer with their symptoms better managed? Does it increase progression-free survival? Going back to what a meaningful measure is and evaluating the performance of your models against that, versus abstract measures, is one of those key pieces.

The other one is thoughtful, human-centric design. With those pieces together, that’s where you have meaningful impact. Companies compete too much on model AUC, accuracy, or F1 score. A 5% difference sounds good on paper, but it’s the execution of that. When you delivered in clinical workload, did you live up the CDS five rights? If that’s true, you’re going to have a bigger impact. Focusing on the meaningful measures versus the abstract measures is key.

Is there a tension between the absolutes of data science versus the frontline practice of medicine that incorporates variables that are personal, local, or perceptual?

Especially for CDSs that rely on predictive models, machine learning, or statistical methods, it’s crucially important. It is written in the FDA’s guidance that you need to share the basis of the prediction and the relevancy of the training of the development data. Both of those things need to be shared.

At Ronin, we show that in a way that is accessible to the clinician. You don’t have to have statistical knowledge or machine learning knowledge to understand that. It’s right there at the point of making the decision, the relevance of the patients that are similar that are giving this insight for this particular patient. The basis of that prediction is right there during clinical decision versus buried in a user manual or peer-reviewed publication that might be behind a paywall.

For things like generative AI and language models, we still need to innovate and develop the methods for transparency in sharing the basis of our prediction. When we look back to things like convolutional neural networks, there was innovation on how we do that. Things like saliency maps were invented and the methodology to do that. Semantic segmentation was another innovation that allowed us to provide that type of insight.

We probably will have to invent some new methods, and I’m excited and hope that we continue excited about what that will be. We would like to be a part of that, and I am hopeful that our research community will gather around this challenge.

Will we see a trough of disillusionment with generative AI?

There will probably be a realization of the challenges, limitations, and areas of success. We’re going to learn that. We’re still learning about what this technology can do. How do we really understand what’s going on underneath the hood? How do we get it to explain the basis of its predictions?

People who are skeptical now — especially if they start to use it to help with writing, as a second reader, or to write code – may start to see a lot of value in it. On the other hand, we’re going to learn about its limitations. I think we might see the more skeptical folks being more embracing, and the ones that are less skeptical becoming more skeptical, as we learn more about the limitations.

What will the next few years bring to Ronin?

We are realizing that personalized, data-driven, total patient understanding in care decisions for cancer patients empowers clinicians. We can use AI, machine learning, and data science informatics for that and to bring the patient patient’s voice into it as well, where they can say what’s happening to them outside the home and their preferences can be brought in to care decision-making, even in the data that is driving those care decisions. There’s a huge opportunity to deliver on that vision, and we are already doing it.

HIStalk Interviews Julia Regan, CEO, RxLightning

Julia Regan, MBA is co-founder and CEO of RxLightning of New Albany, IN.

Tell me about yourself and the company.

I’m a long-time health tech innovator. I carried a bag in pharma and started my career in sales. Early on in my career, in the infancy of health technology, I worked for a manufacturer organization. I fell in love with the opportunity to connect different people, roles, and responsibilities across the healthcare continuum to try to create a better experience and world for patients.

The specialty medication market is one of the fastest growing spaces in the industry for drug spend, representing 52% of dollar volume with high-cost medications such as biologics, infusion meds, cell gene therapies, and even those involving personalized medicine. RXLightning brings that specialty medication process and journey for patients and providers into the digital arena.

Our end-to-end platform automates multiple steps of this process while connecting doctor, patient, specialty pharmacy, and drug manufacturers and  their support teams. Our digital platform, for the first time, creates visibility into the experience. The goal is to reduce administrative burden and waste in the healthcare system for the providers and those organizations that are working to help patients, but ultimately to get patients on therapy quicker in a more affordable way.

What is the overlap between specialty medication prescribing and prior authorization?

Prior authorization is definitely a component of gaining payer access and approval for these medications. But it’s not just the prior authorization, it’s also the cost component, which for these medications could range from tens of thousands of dollars up to a million dollars. Because the cost is so high, there’s an affordability component. Drug manufacturers create programs to help patients get access to therapy, helping go through that benefit investigation and that prior auth process, and also more affordability programs. That could be a bridge program, where patients get samples of the drug while they are navigating the access barriers; free drug for people who can’t afford it; and research around foundations and grants. It’s everything from access through affordability as well. We are a little different than the PA, but the PA is still a component of the journey.

What is the manual process that you replace?

If a specialty pharmacy is used, the doctor will send the prescription to the pharmacy and then wait. The pharmacy will reach out to them and say that a prior authorization required, so they will either complete a paper form or use a digital solution. The next step involves affordability. The pharmacy traditionally works through that process, but because the prescription doesn’t have any of the clinical information or patient financial information, there’s just a lot of back and forth among the pharmacy, the provider’s group, the payer, and even sometimes the manufacturer and their programs. This paper-based system is slow and creates inefficiencies due to missing information or ineligible information.  

RXLightning has created a technology solution for just under 1,300 medications that turns those processes into a single solution that walks a provider through that process digitally and also allows them to track their patients throughout. Instead of using Post-its, Excel, or manual processes that live outside the EHR, our technology system tracks that journey with a CRM type of tool.  

Why do manufacturers choose the specialty drug distribution model and what information do they require?

Because of restrictions and cost, a lot of parties along the way want validation that the clinical steps that are required for approval for a given patient have been documented. The traditional prescription information is one component, but it’s also contact information and caregiver information. Sometimes it includes the clinical history, not only from medications, but also height, weight, allergies, and medications that have been tried and failed. Many components that are part of that traditional prior authorization process are part of these referral forms and enrollment forms.

Then there are REMS medications, which are in the FDA’s Risk Evaluation and Mitigation Strategy because of serious safety concerns. Those have different criteria around authorization codes and compliance that in some cases must be submitted monthly.

Another component is consent, opting into different programs for the patient to share information from a HIPAA compliance perspective, as well as the provider consent to allow another party to work on behalf of them to help navigate through that experience. Also for sharing household income information if they are looking at grants, foundations, or free drug programs.

How laborious is the provider’s process and how long does the patient have to wait for approval before starting the drug?

The work of going through access, affordability, and patient data collection isn’t done while the patient is in the office. A patient who is sick now may have financial constraints with affording a medication that can change their life or even save their life. The provider has to call the patient and ask them to fill out forms. They either have to come in to the office or have it mailed to them, which could get lost.

That paperwork process can take weeks or months. With RxLightning, we see it done sometimes in less than 10 minutes. We communicate and capture the patient consent and information via text and email. The majority of referrals are completed in less than an hour compared to the 2-3 weeks it was taking before. 

What is the implementation process? Do you work individually with providers in a health system, or do they need to reach consensus as a group?

Our platform is extremely flexible and nimble, so we can support all of the different scenarios that are out there. If a large health system wants to install it, we go through a corporate business associate agreement, because PHI and patient data is being entered into our system. We traditionally go through security assessments, and we are HITRUST certified.

We have crawl, walk, or run approaches to implementation. We have a standalone portal that providers and users can be up on within minutes once we get through the business associate agreement and security assessment, if it’s required. The crawl approach is that we use our standalone portal and power it with Secure File Transfer Protocol, or SFTP, data exchange. That’s really just around how we are going to exchange information, pulling exports out of the EHR, having that load patients into our system, and then pushing the data from our system back into the EHR.

Our run is being able to do fully single sign-on capabilities or API integrations with the EHR and embedding our platform into those systems. That requires an implementation group and technical support from the health system. Our standalone platform is completely free to provider groups. 

How are insurers managing biosimilars? Are they asking patients to change their specialty drug prescriptions or do they require a different process?

That’s a really interesting question, and I don’t think there’s a exact answer. Each payer is going to create their clinical policies into their rules based upon what their clinical team assesses coverage should look like. There are multiple steps in this process, and our platform does pharmacy referrals. If a health system doesn’t have access to limited distribution and it’s at a single-source distribution pharmacy, they can send the clinical information and package it up over to that pharmacy. Then we close the loop back to the health system pharmacy with the details so they can create a better experience for the patient.

We handle the investigation, pricing, and coverage. There is a PA component of our platform that could be used. It’s very modular, though, so if they already have a solution in one of those, we could plug those into the platform. Then we handle all of the foundation, grant, free drug, and affordability components in our platform. What we’ve looked at is that across that end-to-end experience, we’ve created a tool where it’s up to the health system, providers, and users on how they want to navigate through it and use it. 

Regardless of what the payer criteria are or the decision-making, around the biosimilars, for example, offices can use our platform to navigate those decision points, and complete the processes for all of them in one location, to navigate the patient quickly and efficiently to a therapy that the payer is going to cover and approve.

How have market conditions affected your strategy?

They haven’t impacted our strategy. So many inefficiencies exist across this journey that health systems and provider groups need a solution. RxLightning has approached it from a brand- and drug-agnostic perspective. We haven’t isolated it to one therapy, one disease state, or a limited portion of drugs. We’ve opened it up and said that we are going to try to solve this process for all of these medications across all of these different steps, which today is being done by different vendors or organizations, most of the time on paper. Organizations see that our platform solves many inefficiencies on their team and the work that they are doing. RxLightning helps alleviate provider burnout  because it makes this process so efficient.

It’s not just about the efficiencies upstream, because when you use paper and faxes, inefficiencies happen while you are awaiting a response. The communication back to the provider’s offices creates call lags and call volumes and it’s sometimes uncontrollable for organizations. We work to plug into the different destinations across this journey — manufacturers, different specialty pharmacies, different parts of the process — to close the loop with information back.

If a provider has a patient who needs a cancer medication and can’t afford it, they can go in our system, see all the grant information, and make a decision whether to apply for a grant. If the grants aren’t of open and foundations aren’t open, they can do the manufacturer’s program. We will provide the response back around the approvals or the denials so they don’t have to constantly look, make phone calls, or answer phone calls. That gives transparency through that whole process while also allowing the patient to see updates across the journey.

What will be important to the company over the next few years?

We are looking to expand our provider base. We know that when our platform is used, it saves much time for offices and helps patients get on therapy much quicker in a more affordable way. We are used by some of the largest healthcare systems today, so growing that base and then providing all the digital connectivity points into the drug manufacturer programs, the hubs, and the specialty pharmacies to have a 100% digital, interoperable ecosystem that exchanges information is critical to the success for the industry, patients, providers.

HIStalk Interviews Frank Harvey, CEO, Surescripts

Frank Harvey, RPh, MBA is CEO of Surescripts of Arlington, VA.

Tell me about yourself and the company.

I have been interested in healthcare since I was six years old. My father used to take me on Saturday mornings to the soda fountain at the local pharmacy. I was interested in what our local pharmacists were able to do with patients and the members of the community. From that time on, I’ve wanted to be in healthcare, specifically as a pharmacist.

I’ve been in pharmacy throughout my career. I have been fortunate to be a part of life sciences, with Lilly and Hoffman-LaRoche, and companies such as Liberty Medical and Mirixa, which is a medication therapy management company. I ran my own venture fund for bit. I was excited to get the opportunity to come to Surescripts because it’s such a wonderful company. Surescripts is a mission-driven health information network that is focused on enhancing the prescribing process and forming care decisions. Our mission is to continue to lower the cost of healthcare, improve patient safety, and improve the overall quality of care.

How has the role of the pharmacist, along with the technologies and data that are part of their work, changed?

During COVID, pharmacists really raised their level and used the full scope of practice of their degree. It was critical during that time, because in many cases, physicians weren’t available because they were tied up with so many COVID patients. Pharmacists stepped in to do much more, such as administering vaccines and  counseling chronic care patients.

We expect pharmacists to continue operating through the full scope of their license, particularly because there’s such a shortage not only of primary care physicians, but also of endocrinologists and rheumatologists. We’re seeing a burnout of physicians and many of them are retiring. Pharmacists will have the opportunity to step up their level of their practice to be operating more at the full scope of their license.

How has the Surescripts network changed over time?

When Surescripts first came into being over 22 years ago, prescriptions were transferred back and forth, either by patients carrying the prescriber’s handwritten prescription to a pharmacy or having it called in. Surescripts was put in place to make that process electronic, as the first health interoperability network, if you will. Now the vast majority of prescriptions go from the physician to the pharmacy electronically through our health information network. 

We have continued to expand far beyond that to help with price transparency and to support pharmacists and physicians being able to message each other electronically, with no more faxes or having to jump on the phone. We’ve continued to focus on enhancing the prescribing process and informing the care decisions that physicians, nurse practitioners, and PAs make by providing medication histories of the patients to the physician.

Has the launch of a competing e-prescribing network changed your strategy?

No. We will continue to focus on being a mission-driven company and will continue to enhance the prescribing process and informing that care decision. Competition is always good. We welcome competition that helps move our mission forward. Whether it’s Surescripts doing it or other companies doing it, we’re happy about that.

How will you continue to enhance the Surescripts network?

Even in the last four years, we’ve improved the quality of prescribing, the prescriptions coming across, by about 85%. We continue to focus on enhancing that prescribing process. The other thing we continue to work on is ensuring that, from an administrative standpoint, we’re providing the right information at the right time to physicians, so they don’t have to cull through volumes of information to get to what’s important at care decision time.

How much emphasis is placed on inserting the connectivity result into the prescriber’s EHR workflow?

It is really critical that it’s in the workflow. We’re integrated in every EHR across the country. Last year, over 2 million practitioners prescribed over 7 billion transactions. All of those were integrated into the electronic health record that the physician was working with.

An example is that at the time of prescribing, when the physician is with the patient, transparency apps allow the physician to see not only the therapeutic alternatives, but also the pricing of each based on the insurance coverage that the patient has. It allows a physician to make the right therapeutic decision for the patient as well.

Are you seeing benefits for both the prescriber and the patient?

Absolutely. That’s one of the most important things about having a real-time prescription benefit tool in the physician’s EHR. They can see everything about the prescription and the therapeutic alternatives. Before, they would write a prescription without understanding the price consequences. The patient would take it to the pharmacy, find that they couldn’t afford that medication, and then ask the pharmacy to call back to have the prescription changed to a different medication that they could afford. Integrating that into the overall workflow cuts down a lot of demonstrated burden of the physician, the pharmacy, and the physician staff.

Have you seen statistics documenting outcomes improvement since cost issues might have led to the patient either not having the prescription filled or taking it in lower doses to stretch it out?

We absolutely have. Most recent studies shows that the prescription pickup rate increases by 3% to 5% with use of a price transparency tool with real-time prescription benefits. The patient knows what they are facing from a pricing standpoint, they’re more likely to pick it up, and the doctor is more likely to have written a medication that is affordable to the patient. The most expensive medications are the ones that the patient never picks up, because they never get their health condition taken care of. These tools help the patient.

How has the federal government influenced interoperability?

Micky Tripathi and his team have done a tremendous job. They have so much energy behind their efforts. Interoperability is so critical in being able to get that full patient’s record. A new proposed rule focuses on advancing that interoperability and improving transparency, supporting the access and exchange of electronic health information. 

The role that Micky and his team have played has been critical to moving us forward more rapidly than would have happened without their participation, their urging, and their hard work over a long time. We are a great example of what interoperability does, with 21.7 billion transactions a year across all of our products. We are looking forward to everything that’s happening with TEFCA.

What will the company’s strategy be over the next few years?

We are going to continue to focus on what has been our bread and butter, which is our mission of improving the quality of care, improving patient safety, and lowering cost. We will do that by broadening the areas that we work on across enhancing prescribing as well as informing care. We are looking to work to help broaden the care team, to enable the care team as it expands and pharmacists take a more active role, to make sure that they’ve got the right data to make the right decisions and can communicate that information back into the health record. We will continue to lobby for the right legislation to be in place to enable and empower pharmacists to do what they’re able to do, in partnership and collaboration with physicians, nurse practitioners, and physician assistants.

Healthcare in this country is at a critical phase. We are seeing the continued burnout of our healthcare practitioners and a lack of enough healthcare practitioners, particularly in rural and urban areas. We have areas where patients may have to travel 100 miles to see a physician. It will be important that pharmacists can play a larger role. I believe that we will see, over the next five years, that the healthcare team will continue to evolve, and that will be the best thing for the patient.

HIStalk Interviews Jamel Giuma, CEO, JTG Consulting Group

Jamel Giuma is president and CEO of JTG Consulting Group of Miami, FL.

Tell me about yourself and the company.

I studied finance in college, but I was always in IT. I started working for a retail company while I was in high school in their corporate IT department, and did that through my first couple of years of college. I got tired of working for corporate America pretty quickly and started applying to IT jobs in Jacksonville, Florida, where I was raised. The first place to call me back was the University of Florida health system. I started working in their desktop support group, and one of the areas I was responsible for was the laboratory. I was replacing the lab director’s computer and she said, have you ever thought about becoming a systems analyst? I said, what’s that? I fell in love with the lab, and here I am 16 or 17 years later.

I was recruited by the University of Miami to start their lab team and manage that to grow it to what it is today. I worked at Sunquest as director of interoperability in their product strategy group for a number of years. The travel got out of control, especially being in Australia for a over a year and missing family and friends. I left to work for a five-year-old startup, and after nine months, decided that I was smart and hardworking enough to do this on my own. I started JTG five years ago in September.

Lab was always a healthcare technology pioneer, being the first to recognize the benefit of scale, to implement barcoding and tracking systems, to integrate with systems inside and outside the hospital, and to create a market for health IT that included the formation of Meditech and Cerner with lab as their first offering. What are the lab’s biggest issues today?

Historically, lab leaders were not always the best businesspeople to sell their service, either internally to the health system or externally. I’ve definitely seen a change in lab administration, where we’re starting to see more MBAs and MPHs who understand the business side and can take the lab to the next level. Taking advantage of excess capacity, economies of scale automation, and overall delivery of service for providing providers the first point of diagnosis.

Lab has a huge impact in the ecosystem of a patient’s journey. Without the lab, very few decisions can be made. If you have no radiology or no labs, you have no diagnosis in most cases, or it’s harder to make a diagnosis. With the onset of enterprise EHRs becoming the standard, we’ve seen things change from integration projects to workflow and optimization projects in health systems that allow providers to get more rich data and get it more quickly. It has been interesting seeing the evolution from best-of-breed lab systems to enterprise systems that have that best-of-breed technology embedded in them.

What laboratory-related external technology connections add value?

Folks are looking at more genetic data and genomics. That’s a lot more data than they can even handle. It’s more of a concern at times for providers because of the liability of missing something and understanding and interpreting those more complex and lengthy reports. Hospitals want to provide those services to their providers and patients, but they are also taking a close look at the risk of offering those tests, not just the financial risk of being reimbursed, but also how to interpret these results.

How do we ingest these results? Some of these new reports are 50-plus pages long, where historically doctors are used to receiving a metabolic panel or a CBC that has more discrete results with 20 or 30 assays in it as opposed to interpretative results that are more qualitative and quantitative results that impact how they make decisions to place those orders. They want to be able to provide the patient care, but if they can’t interpret the results or don’t have enough time to review and understand what the results are telling them, then are they adding any benefit to the patient’s overall care?

Are health systems changing their policies or technologies to comply with the Cures Act requirement to release electronic results immediately to the patient?

Health systems historically were risk averse to releasing those results. They don’t want patient going to Dr. Google to figure out how to interpret these results, whether it’s right or wrong. But with the onset of things like Meaningful Use and other technologies that have been embedded in these systems, they are having to release these results. If it’s being sent to a reference lab, patients are getting savvy enough to know that they can register with Labcorp, Quest, or Sonic to create a patient account login and get those results before their provider. A lot of EHRs and lab systems now have automatic release of those within certain parameters. Certain tests, such as STIs and other infectious disease results that are more sensitive, might be released within five to seven days if the provider hasn’t reviewed it. But overall, health systems are becoming more open to the fact that they have to do it, and we are starting to see that paradigm shift at larger health systems.

The introduction of artificial intelligence will bring a lot of opportunities to health systems to provide even better economies of scale to their providers, who can interpret the results before they are released and decide whether they need to add comments. We’ve seen Epic talking about utilizing ChatGPT and Cerner is talking with the FDA on some AI tools as well. AI can be powerful and potentially dangerous, but with the right guardrails, it will help providers, patients, and health systems take advantage of the data that’s already there.

Generative AI seems ideally suited to turn medical language into patient-understandable reports or instructions. Will that effort be led by companies like yours, or vendors themselves?

We are going to all have to partner together to take advantage of those new opportunities and tools. With lab, I’ve seen things like CellaVision, who has been doing artificial intelligence before it was called AI in identifying different cell types in a hematology slide. We’re also seeing things like the Copan WASPLab, a microbiology total lab automation tool that can take pictures of Petri dishes, interpret what’s growing, and group them for the tech to review. Their machine learning and algorithms are getting better every day to help the tech skip things that aren’t value-add, like no growth on a micro plate, and also categorizing things for them to review and confirm.

We will see more of that in chemistry and other areas, doing anything we can to avoid having a tech review a result, using a confidence interval set by the lab’s medical director to allow auto-verification. That will reduce turnaround time and hopefully improve patient care by getting a diagnosis sooner.

Telehealth, remote patient monitoring, and other virtual medical services are limited by the last-mile problem of collecting lab specimens and delivering prescriptions. Several companies have attacked the second issue. How are they approaching the lab collection challenge?

Direct-to-consumer labs is a great example of that. Because of the EUA that the FDA approved for COVID testing, we’re starting to see restrictions and legislation change on patients being able to order their own lab tests. It’s only a matter of time before it crosses all of our states. Across our country, providers and health systems are looking at ways to make it more convenient for patients. Going to a hospital, parking in a garage, and finding the right location are going away. We are starting to see Walgreens, Walmart, and Safeway embedding labs in those shopping centers. You park in a parking lot easily, walk in, get your test done, pick up your Starbucks after you are finished fasting, and you’re out.

That’s one step. But direct-to-consumer, where patients can order the test and self-administer the swab or void into a cup, is another example where we will see this evolve. The concerns that people are raising are also valid. Was the test collected correctly? Is it the same patient who ordered it? Who is responsible for that authorizing provider and interpretation of that result for the patient? There’s still a lot of work to do, but health systems know that to compete with Amazon, Walmart, and CVS they are going to have to change. That will also require lobbying work with the government to make that direct-to-consumer testing possible.

Which of your services are in highest demand?

With the great resignation, it’s difficult to get people to go to work for some reason, so staff augmentation is a big part of our business. We embed full-time employees at organizations to augment the needs of positions they can’t fill. A lot of the work we do can be done remotely, and the pandemic was a great representation of what we can do without having to physically be on site. We’ve done big implementations of new lab systems and EHRs with other vendors and consulting firms that were completely remote, and it’s incredible the amount of work that can be done remotely. Those are some of the big things that are being requested. Also, folks are looking to upgrade their systems constantly and they just don’t have enough people or time with all the competing projects.

Integration work is top of mind for health systems, laboratories, and even private reference labs, being able to interop with their clients, vendors, and patients. Those are quick wins. We are starting to see demand for talking about digital pathology and what that could do for the pathologist, automating some of their workflow and providing remote capability for the pathologist who was historically eyes on a microscope. That still has way to go, but we’ve seen some good headway in the last couple of years.

What have you learned in starting a company and setting its strategy?

From the beginning, I knew that we had to remain focused and not try to be everything to everyone. We’re not afraid to turn down business that doesn’t align with our goals, competencies, and strengths. We are laser focused in the laboratory. and there’s enough business in the laboratory space for not just JTG, but for other firms and vendors. We are happy that we’ve been successful in remaining focused and providing that excellent service to our customers.

HIStalk Interviews Tyler Smith, CEO, Health Data Movers

Tyler Smith, MBA is CEO of Health Data Movers.

Tell me about yourself and the company.

I began my career on Capitol Hill during the recession, but most importantly, it was during the passage of the Affordable Care Act. The HITECH act from the stimulus propelled the digital health transformation forward. Being on the Hill during this time, it was an exciting time to get into healthcare. I left after one year and went to work in the consulting space. I got certified in Epic, spent a little bit of time at Cumberland before they were acquired by Tegria, and then started building what became Health Data Movers.

I focused on application work, while one of my two co-founders focused on data migration and the third brought in our first software development. From the beginning, Health Data Movers has had a technologist focus. Today we offer six core services that we break into two categories. Signature services is software development, integration, and data migration, while foundation services is applications, PMO, and advisory. We are a technologist-first firm. While a lot of great firms that came before us have moved into a desire to be a Big Four advisory-type firm, we enjoy getting our hands dirty and doing the work.

How have health system financials changed the demand for consulting services and affected their technology acquisition process?

I realized as a leader during the pandemic that that change is the only constant. When we saw how the scaling back of fee-for-service could affect budgets, it taught me that have to be flexible and shape-shift with the needs of customers. During that time, we saw pauses in projects, but then when the government acted and figured out ways keep health systems solvent, we saw all these paused projects back in high demand. We were scrambling to put together teams to get these projects kicked off.

At the same time, we also saw a lot of interest in digital health that was created by the pandemic. You saw a lot more digital health firms. We saw more interest from biotech firms that needed to integrate data in and out of the system of record, which is the EHR.  

In terms of our investment, it is staying focused on what we do best, but understanding that ultimately our customers — health systems, biotech firms, digital health firms –have their strategic imperatives and we need to be able to support them from a technology perspective. The directions that they choose to go determines a lot of the direction that HDM ultimately goes.

Are health systems and their technologies prepared to integrate real-world data, life sciences research, and FDA marketing surveillance?

Companies are formed based on ideas and also pre-existing alignment. Especially consulting firms, because folks who have worked together in the past and liked it will work together in the future. One of our co-founders came from a company called OTTR, which was a transplant EHR that was acquired by CareDx, which is a massive life sciences biotech company in the transplant space. We always say that if you can move transplant data, you can move any type of data. We have roots with life sciences because of our transplant background. We’ve been working with CareDx for over three years to ensure that the data from their tests makes its way to the EHR and vice versa. 

As this massive influx of information comes about as these biotech firms are maturing, it has been awesome to see the data from tests that are done by the specialty labs that we work make its way into the EHR. Is the real-world, evidence-rich data entering into the EHR? One hundred percent yes. A lot of the work that we have been doing recently with Epic Aura is getting specialty lab data in and out of the system of record. 

I think we are going to see some really cool improvements in patient care because of the integration of this data. It’s exciting to see how the EMR is moving from being a system for charting and ensuring that there’s billable outcomes to a place where we can have true insights from the interface with the patient and physician that will improve care.

What will the healthcare impact be of new tools such as cloud services, ChatGPT, and low-code systems that make it easier to develop applications?

That’s really exciting. We have an internal team of developers and the energy and excitement they have behind ChatGPT is evident in the Slack channels that I’m lucky enough to lurk in. There’s a specialty that is required in healthcare development, which we see as a competitive advantage because we have a line team of developers. But we also have developers who are well versed in the intricacies of healthcare – HL7 v2, FHIR, and HIPAA-compliant cloud. If there’s now a way for developer to speed up execution, then we can get a lot more done with smaller teams and we can scale the projects that we’re able to take on at a greater pace than just simply scaling headcount.

I get asked a lot about this metric – how big is your headcount? That is important in time and materials type work, but if we are able to empower our engineers to be more efficient with their work, then we can talk more about how many projects were we able to execute. The projects are the work that is pushing healthcare forward. If we can leverage the geniuses that we have in house to take on projects with biotech and digital health firms and essentially scale their skillset, we will be about to move our integration and software development portfolio of work faster, which then ultimately we believe will make healthcare more interoperable, user friendly, and efficient.

How are health systems and their new digital-type C-level officers approaching consumer-facing projects as they begin to compete with big technology and consumer companies?

We have been working on some digital front door related projects with strategy firms and more payvider-type organizations. Then you look at the One Medical-Amazon combination and see the rise of concierge medicine and advanced primary care. We talk about the retail health side a lot internally. Patient experience is going to be a critical next piece where technology is applied. Our core is with the healthcare organizations. We are seeing a lot more interest in the patient experience. I’m excited about this next wave of technology that supports that and I’m confident that Health Data Movers will be involved in that next transition.

How does your experience as a Stanford MBA student influence how you run the company?

It’s crazy how much Stanford influence there is at Health Data Movers. We have a board member who was my professor at Stanford, another board member who was the associate CIO at Stanford Health Care, and then both of my co-founders were either full-time or consultants at Stanford Health Care. But to the broader question around the Stanford influence, it’s just insane how much innovation has come out of a really tiny piece of US geography. When you are around it, you understand the energy behind creating something new and using technology to change the world. It’s not just something people say, it’s something they believe.

I could give you a laundry list of all the positives that I got from my Stanford experience or from being around Stanford, but I’ll focus on the idea that we are all capable of making the world change no matter what discipline we decide to do that in. Going to business school at the time when we were developing the company made me realize that yes, we are a services firm, but services firms can create massive change. Having lofty goals to actually improve healthcare through the implementation of EHRs, optimization of EHRs, and software around EHRs is something that can be achieved if we work extremely hard and have total dedication to the mission and vision.

Are you encouraged that healthcare has the ability and the incentives to implement technology that will truly make a difference?

I’m encouraged because there’s been massive adoption. Everyone had to get on the grid. I think Paul Kenyon from OTTR sums it up really well. It’s like the land grant colleges, or the land grants in general, in the Midwest. The government had to create a reason for folks to move to a certain part of the country, and then they were able to step away. We had to HITECH to get everybody onto the grid, and then we had the pandemic. The pandemic was awful,  but in a lot of ways, it also brought in more interest into healthcare. 

As much as people like to write off the EHR vendors as being resistant to change, it’s impossible to separate that there’s so much interest now in healthcare and digital health. Even though some tourists have left, a lot of folks have stuck around. We will see innovation that comes from a lot of brains and energy being in this space.

Just look at your MyChart interface over the years. It is always improving. While the rate of change is slower in healthcare, it will continue to evolve. I am fully confident that it is continuing to become better. I am excited about everything that will be possible now that we are on the grid and folks are interested in making healthcare better through technology,

My dad was seen at two health systems with what turned out to be Parkinson’s. It’s crazy that they operated on his rotator cuff even though they could have looked in his record to see that it wasn’t necessary. Here I was five years ago, working at a healthcare technology firm, and I’m literally sitting there helplessly with him knowing that the physician isn’t getting the full record. That’s when it really clicked to me. We all have these personal stories and that’s just one of millions. A lot of what we are working towards is to become non-existent as a company, because at that point, we will have created truly interoperable patient care that will fix so many avoidable errors. This is also the platform where innovation from life sciences and biotech companies will be made available to the providers who are delivering the care.

HIStalk Interviews B. J. Moore, CIO, Providence

B. J. Moore is CIO and EVP of real estate strategy and operations at Providence of Renton, WA.

Tell me about yourself and the organization.

I’m the chief information officer at Providence and am also responsible for real estate strategy and operations, so I wear two very distinctive hats. I’ve been at Providence for four years. Before that, I was at Microsoft for 27 years in various roles, the last of which was vice president of engineering for the Azure group. I am well versed on the cloud and the transformation of the cloud, which has been helpful in my journey here at Providence.

Are your dual roles based on your personal interests, or is that an indicator that some fluidity exists in how Providence views its bricks and mortar footprint versus technology?

Absolutely there is some fluidity there in three areas. One, we have a big, bold goal to be carbon negative by 2030, and real estate and IT are the two biggest offenders on the carbon front. A big way that we can solve it for both spaces is through technology, so it makes sense to have that under one leader and manage both of those portfolios to drive it down, but also use technology to more efficiently reduce our carbon emissions.

Two, in this modern workplace post COVID, everything is now a hybrid work environment, with some remote and some in-person. How do we create these rich, collaborative work environments when people are at work to get the best of the workspace, and how do technology and real estate tie into that? 

The final bucket is that the future of healthcare is becoming more and more virtual. Before COVID, a bed was a very concrete thing. A hospital had X number of beds. Now a bed is more abstract. It could be virtual care, at home, or a physical bed in a hospital. Thinking of a bed in more of a virtual way, more of an abstract way, is helpful. Me being able to wear both hats helps us bridge that gap.

What do you think about Nuance DAX and its enhancement with ChatGPT integration?

The first implementation of DAX was good, but there are human beings in the middle doing quality assurance, so it does a good job of transcribing. There’s a two- to four-hour QA process for a human being on the Nuance side to review things before it gets posted to the medical record.

With generative AI, there’s a real opportunity to make that near real time, to cut that quality assurance person out of the middle and use generative AI, that large language modeling capability, to close that gap. We are the single biggest adopter of DAX and we’ve been a early partner with Nuance on that product, actually Nuance and Microsoft before Microsoft bought Nuance.

What is ChatGPT’s potential?

I see the potential as huge. If you would have asked me six or seven months ago what I thought of generative AI or ChatGPT, I probably would have given you a blank stare, or would have said that I think AI has been overused. What we’ve seen in the last six months is just incredible. From 3.0 to 4.0, it really opens your eyes to what’s possible on generative AI with images, video and the whole processing. It’s just absolutely incredible.

The downside is that what everybody sees is the consumer version of it. It was literally fed every piece of social media pop culture, from “I Love Lucy” to  “The Communist Manifesto.” It was fed everything, so it provides for a great model, but it also is easy for people to find examples where it has bias or answers in a misleading way or whatever.

I love ChatGPT and showing them the power, but I worry that people assume that it’s one size fits all versus it’s this large language model that we can apply to clinical settings. We are working with Microsoft and the Azure team to take that technology, not the generic ChatGPT, to train that against our own information here at Providence, our own medical data, so you don’t get the quirkiness of “I Love Lucy,” but get the solid domain of healthcare. I think we’ll see better outcomes than maybe some of the YouTube videos where there’s some funny scenarios with ChatGPT.

How can EHR vendors use ChatGPT to improve or extend their product?

We are an Epic shop and are actually a real example. We’ve taken that power and we are going to use it to train against the Epic inbox. Our doctors are overwhelmed with messages and maybe don’t get the messages until the end of the day. We are training the model to look at these messages, triage them, and bring the most important ones to the doctor’s attention.

It’s an example of something that can be done within the workflow of the EHR. It’s an example of a baby step, by using this technology that can help the productivity of a doctor and hopefully help a patient by getting those critical messages upfront.

Epic has been a great partner with Azure. They have some good computational capabilities that have partnered with Azure. When I hear of them wanting to partner on the ChatGPT side of things, it feels like a natural extension of that partnership.

We heard early on that providers who didn’t move to the cloud would miss out on tools and capabilities and we’ve seen the rise in low-code development tools, ChatGPT, and APIs. Will health systems that don’t have a big engineering group use these tools to do in-house development?

It helps to use some of these generic capabilities and see the art of the possible, but the advice I give to everybody when I’m speaking or on the conference circuit is that you have to get on these native cloud solutions. You can’t be a locked in on prem. You are really missing out on the innovation since and all the innovation is happening in the cloud. You can use ChatGPT without being in the cloud, but our example, where you need to train it on your own models and your own data, won’t be effective for these smaller systems that are locked on premise. The cloud journey is necessary.

Companies clamor for EHR data to use for AI training and to support life sciences research. How is that use of EHR data evolving?

It’s a no-brainer, and it’s much bigger than that. We talk about the big data EHR, but big data is not EHR. It’s  all of the information from the biomedical devices, from wearables, from social determinants of health, all these other things. When you have that data on premise, you’re really limited by the scale-up capability of hardware that you have on premise. Whereas in the cloud, you have basically unlimited storage and unlimited scale.

As part of our journey four years ago, we have already moved all of our data to the cloud. To me, that’s the only way you can connect all this data together, and then as stated earlier, that’s the only place these advanced analytic AI tools exist, is in the cloud. It’s a journey that everybody has to do. My advice to your readers is that it’s much bigger than EHR. EHR data is Step 1 of 20 as far as the interesting data sets that should be in the cloud.

Do we have the interoperability maturity as well as the motivation to connect all of these data sources of a patient’s longitudinal record?

It’s still a challenge. Even if you’re on the same two versions of Epic, you put that in the cloud, it’s still hard to integrate. People are seeing the value more, especially as you connect with other data sets. It’s easier in that you have more computational power, but there’s still some blocking and tackling issues. Bringing that data together, normalizing the data, cleaning the data, de-duping the data, making sure that you have that full 360-degree view of patient is still a challenge.

How will that change if the prediction comes true that consolidation will result in the country having just a few huge health systems?

I don’t see the consolidation trends. I don’t think we’re in a governmental environment where there’s energy to consolidate. Even when they do, look at somebody like CommonSpirit. They are a large health system that grew through acquisitions and they are still on 20 different electronic health records. I don’t know that it solves it.

I think what solves it is that you have the computational power, and where you went earlier in your question, you now have the imperative to do it. So I think you’re going to see more cloud-level integration, and that’s how you solve that 360 degree view of a patient versus necessarily hospitals consolidating to achieve that. Hospitals are consolidated to get efficiencies of scale, but I think the data problem is independent of that.

Both providers and vendors are being challenged to protect their bottom lines as we roll out of an economic environment of extensive investment and experiments with innovation. How will they weigh the adoption of technology that might be innovative with the need to protect margins?

I can only speak to what we’ve done at Providence. Luckily in my first four years, we really modernized that back office. We were already on a single instance of Epic. We are on a single instance of Oracle Cloud. We’ve done that heavy lift in our budget.

My budget is about 15% smaller this year. We have really had to tighten our belt –get rid of contractors, vendors, unfortunately lay off some employees, and reduce or cancel licenses and subscriptions to focus on shorter-term wins. We have that luxury because we have already consolidated, but the feedback I give partners is that if you don’t have a ROI in 12 months or less, we really are not in a position right now to make those bets.

This is where generative AI six months ago wasn’t even a tool in my toolbox, but it feels like a tool that I can add quickly that can have that easy 12-month or less return on investment. The key is productivity. We have nursing and caregiver shortages. There’s never going to be enough. How do we make them more productive? Right now, 50% of their time is spent doing administrative work. If generative AI can chip away at that and get rid of that burdensome administration and allow them to practice their craft, I think we can reduce costs, but also reduce burnout and attrition at the same time.

How will big tech companies that have made recent health IT acquisitions, such as Microsoft and Oracle, influence healthcare?

Although Microsoft bought Nuance, I don’t perceive them wanting to get into healthcare. I see that as adding to their AI capabilities around ambient artificial intelligence and voice recognition for improving their services. It just happened to be a healthcare company. I see that as different than Amazon, which clearly wants to get into healthcare, or Google that wants to get into healthcare. I would separate the two.

Frankly, when I look at partnerships, I look at that. When I was at Microsoft, some of our best customers were retailers that were leaving Amazon to come to Microsoft because they didn’t want to be hosted on a competitor’s infrastructure. I think it’s the same thing in healthcare. When I look at partnerships, is it a partner that is more altruistic, and I think Microsoft is more in that camp, or is it somebody that today may be a tech partner, but tomorrow may be a competitor? That certainly weighs into how I make technology decisions.

How do you as a CIO develop a strategic plan in an environment that changes dramatically month by month?

Like I said, I have the luxury of having closed the book on our big transformations last year. Our focus has shifted to how we optimize the investments we have. Great, we are on a single instance of Epic — how do we optimize that? We’re on a single ERP — how do we optimize that? How do we start chipping away at the holy grail, which is around patient experience, caregiver experience, caregiver productivity, and health outcomes? Our three- to five-year horizon is more looking at those.

Based on our budgets, we will be more opportunistic to chip away at that. Luckily I don’t I need to go to a single ERP or need to go to Epic. I don’t have that cloud hanging over my head any more. Our planning horizon probably looks markedly different than other large health systems.

HIStalk Interviews Shivdev Rao, MD, CEO, Abridge

Shivdev (Shiv) Rao, MD is co-founder and CEO of Abridge of Pittsburgh, PA.

Tell me about yourself and the company.

I used to be a corporate investor for a large hospital system, UPMC. A lot of my investments were focused on AI technology. We put a lot of capital into Carnegie Mellon University and started a machine learning and health program there. A lot of the founding DNA for Abridge comes from Carnegie Mellon, and a lifetime ago, I went to Carnegie Mellon myself. In the middle, I became a practicing cardiologist.

At Abridge, we’re building technology that can be a part of all of the conversations that I as a clinician have with patients, whether they are over the phone or even over telemedicine. The technology, in real time, creates clinical notes for me that can help with clinical care team communication. It also structures information for me, that can help with billing oriented workflows. And Abridge can also help my patients as an extension of my best intention, helping them better understand and follow through on everything we talked about, even when they’re not in front of me. Our goal is to unburden clinicians from clerical work and help them and their patients better understand and follow through on the healthcare plans that will improve experiences, and economics immediately, and also improve outcomes over time.

How do you differentiate Abridge from Nuance DAX? 

This space is ripe with opportunity. Between Abridge and other companies in this space, we are pointed in different directions, which will lead us to very different destinations. Abridge is based on this idea that healthcare is really about people. Upstream of all the diagnostics and therapeutics in healthcare, the most important people in healthcare – providers and their patients – are having conversations. Being able to structure and summarize conversations in real time without any humans in the loop, and then being able to structure that data, means that we can start to unburden clinicians from the three customers that they’re serving every time they see a patient.

First and foremost, there’s the patient. We know that’s the most important. But then there are colleagues on the care team for whom they need to create a different kind of clinical artifact. Then there is everyone in revenue cycle, everyone on the coding and billing side, that they also need to be thinking about. We’ve taken the tack of building technology that doesn’t have any humans in the loop, that we can democratize across every single doctor and nurse out there, that doesn’t anchor on scribing per se.

That’s a word that that company, and other companies, might leverage increasingly if they’re using AI to basically power more efficient scribing. But that’s not really our positioning. What we’re building is more of a co-pilot that can be a part of all of these conversations that can create these summaries in real-time to help everyone better understand and follow through. As a tech company, our mantra is cheaper, better, faster.

It would seem useful for the provider to set aside 30 seconds at the end of the visit to intentionally dictate a summary that could benefit that provider, the patient, and anyone who has to interpret the chart downstream. 

That is absolutely one of the key differentiators between Abridge and any other company in this space. While we are physician driven by me, we are also patient centered, and we are AI powered. We think that’s the key triad for clinician facing AI solutions. For everything that we are building from a product perspective, the person who’s going to benefit the most should be the patient. But we are AI powered. This is all about technology. We can partner with and help services companies, but what our offering is all about is being able to be in the workflow incredibly fast. We want to be able to create value for everyone involved, and that starts with patients and their clinicians.

When we started this company, we knew the kind of technology that we wanted to point at this challenge. We knew it was based on this new type of machine learning model called a transformer. One of the key papers about transformers came out in December 2017, and we started the company in March 2018. But from a mission perspective, we also knew that there’s such an opportunity to help patients better understand and follow through. Given the way healthcare is evolving, given all the increasing momentum around providers taking risk and payviders becoming a bigger phenomenon, being able to not just put the patient at the center of workflows, but actually demonstrate and measure how you can help them better understand, follow through, adhere to their care plan, and actually improve outcomes even over time, will be a game-changer in healthcare.

I started seeing patients eight or nine years ago as an attending after fellowship. I would pick up the phone after a procedure, like a Holter monitor or an echocardiogram, and I would start dictating the procedure report. People in the basement of the hospital were actively, synchronously on the line listening and typing, and then that report would end up in the medical record. In relatively short order, it evolved into this new world where I would pick up the phone and essentially do the same thing, but it would get recorded, and someone later on would listen to the whole thing and put the report in the medical record. Then it evolved in very short order to this other world, where there was a technology in the middle that was transcribing everything that I said into the phone and calling out where the speech recognition technology was less confident. The humans who were listening later could just focus on those words, correct those words, and get them back in the medical record. That created this huge efficiency.

But the final form of dictation of monologues was a product where I could pick up a Dictaphone and just dictate and see the words in real time show up in my medical record the way it does on our phones these days. I could correct things on the fly.

They say that history doesn’t repeat, but it rhymes. We think that this space of dialogues, not dictations, will follow a similar pattern. In this space, the first model was scribes or extenders in the corner of the room, writing the note in real time as I have an encounter with my patient.

For some companies, that evolved to humans who connect and listen in real time to the conversations through audio or video. More recently, we see companies record conversations for humans to listen to later on and be able to write the note.  Those companies are trying to build technology that can help them be more efficient in listening to the conversation, writing the note, and getting it back into the medical record.

This is a key point of differentiation for us, because at Abridge, we are generating a note draft along with structured data that we integrate into the medical record in real time. We are not comparing ourselves against a human and saying that AI is going to be better than all the things a human can do in the workflow, especially at the clinician level in relation to a doctor or a nurse and how they might want to document or think about, especially the decisions that they need to make.

Instead, what we comp against is technology that in real time is listening to the conversation, generating a summary, structuring data, and putting it into all the different slots of the medical records. Your workflow is that much more frictionless, but we still require the clinician end user to be in the loop and work with the AI-generated output. It’s apples versus oranges compared to an AI-powered scribe model, but we think it also follows a similar pattern of evolution to what we’ve already seen happen in the dictation space.

ChatGPT has sucked up a lot of the technology air in the room in its few weeks of public availability. What advancements and disappointments do you think we will see? 

In terms of advancements, there’s no question that there’s an ability to leverage this kind of technology, these sorts of what they call foundation models or large language models in healthcare technologies. There’s no question that there is incredible value. At the same time, we are seeing in real time that t’s pretty easy to create a flashy demo with these technologies, but that doesn’t mean that that demo can translate into actual enterprise workflows inside of hospitals, inside of clinics, that have a different kind of standard in terms of reliability, credibility, transparency, and auditability. Those are all the different dimensions of trust, which is a requirement, which is table stakes. 

Everyone is going to find a way to leverage this technology in some part of their stack, their modules, if you will. That doesn’t make an AI company, though. There will be also be AI-native companies like Abridge, and an AI-native company is not going to leverage one of those large language models in a superficial way. It’s not going to be a straightforward query or prompt. As an AI-native company, Abridge builds technology underneath those models and beside those models. We fine tune those models, we build technology on top of them, and we integrate them deeply into workflows. That’s where the magic actually ends up happening.

There’s a joke that every company in the United States is a healthcare company, because every company is offering healthcare benefits to their employees. There’s an interesting phenomenon now where every company will be able to say on some level that they are an AI company if they are leveraging an API like GPT. That’s not an AI-native company. AI-native companies will be able to commoditize different solutions in their space and drive value up the stack to new ideas. Those are the companies that are going to have to have the talent, the expertise, and the data to actually build their own models, which can coexist with the large commercial models that are out there.

Will technology companies see the danger in trying to promote their AI products as replacing the physician’s judgment?

It’s definitely a risk. There’s no question about it. The framework that makes the most sense is that AI can assist, augment, and automate. How you point any one of those — assist, augment, automate — frames at solutions is the key.

What does that heuristic look like? Imagine a two-by-two, where the risk, the consequences of making a bad decision, is on the X axis. The volume of decisions is on the Y axis. All the decisions on that half of the two-by-two that involve a high consequence for any given decision going sideways deserves a frame thinking about AI as something that can be assistive or that could augment, but not something that can automate anytime soon.

Whereas where there are low consequences of decisions, and where there’s a lot of volume of those low consequences of decisions happening as well, that’s low-hanging fruit for this kind of technology. When you think about the healthcare workflows inside of clinics, it’s probably not at the point of care that you’re necessarily automating doctors or nurses and the decision-making that they’re doing, the creativity that they are having to bring to the table. It’s probably way more likely that it’s in the back of the office in the rev cycle, authorizations, coding, and all those workflows where there isn’t the same sort of stakes from an outcome perspective.

How could technology in general help healthcare scale to address the clinician shortage and their uneven geographic distribution?

That’s part and parcel with the mission of Abridge. When we think about the current climate, healthcare systems are underwater. We hear from the president of UPMC on the physician services side that staffing is the number one concern for hospital CEOs, because nearly two-thirds of doctors are experiencing at least one symptom of burnout. We keep seeing headlines around hospitals actually closing departments or ending services. When you think about hospital margins, they are as slim as ever before.The cost of labor is a 19% expense growth per discharge. The drivers here are absolutely putting so much pressure on the system at large to figure out how they can increase productivity from a dwindling labor force, and at the same time, actually have that labor force be smiling all the while. How can they bring joy back to that labor force in such a way that they’ll actually end up seeing more patients? It’s a very, very tricky line to walk and pull off.

That’s where technologies like AI can come in, and generative AI specifically. The way that we leverage AI at Abridge is that this is technology that’s getting out of the way. You can bring it into your conversations. This is technology that can scale because it’s all technology, it’s real time, and it’s flexible enough that we have an API that can integrate with telemedicine, for example, or call center conversations. Not just doctors, but nurses, PAs, medical students, and trainees. Everybody can benefit from this technology. That will lead to people having better conversations with their patients, being more present, and patients having better experiences. In the case of Abridge, since we also have an offering on the patient side, we want to be able to demonstrate that it is improving understanding, and better follow through. The aspiration is to demonstrate better outcomes. 

Financial markets are down and health systems are struggling with their bottom lines. How will the market look in the next 3-4 years and how do you position the company?

The idea more than anything is to leverage technology to rise to the moment of this public health crisis. In terms of strategy, there’s a great quote that startups get disruption when they get distribution faster than incumbents get innovation. It summarizes all the Clayton Christensen books. The name of the game from a strategy perspective is finding a way to create as much impact as possible. That’s always the promise of technology, that it can scale infinitely and that we can distribute this at a price point that all the healthcare systems, all the clinics can actually afford. Not just for their doctors, but their entire staff over time. That that aspect of our strategy is crystal clear, that we have to be cheaper, better, faster. We have to leverage technology and all of the affordances that come with it to get this out there at this moment in time, right now in 2023 when the need has never been greater.

In the moment right now that we are in, it feels like we have two huge waves that are starting to intersect. At Abridge, we are riding both of them. One of those waves has to do with this public health crisis, clinicians burning out, margins remaining slim, and this challenge around us as a society of the healthcare system not having enough clinicians to actually deliver the care that everybody needs, that our communities require right now. How are we going to respond?

In parallel, we have this other huge wave around generative AI, and all of us as a society starting to understand that this is a solution, there is a lot of magic in this. How do we find a way to get them to intersect to point generative AI at this public health crisis and create value? 

Paradoxically, generative AI can be just the thing to highlight the humanity in healthcare, to help people be more present and focus more on each other. That more than anything is going to improve experiences, outcomes, and start to solve this challenge that healthcare systems are dealing with. At Abridge, that’s our mission, that’s what we’re all about, that’s what we’re focused on. We have been super excited to be able to partner with large healthcare systems, not just UPMC, but we recently announced University of Kansas Health System, where over 1,500 clinicians are going to be able to leverage our technology in real time in a very deeply integrated way with their healthcare electronic medical record system. We are excited to be able to demonstrate that we can scale this across systems and across the entire United States over time in a very short order.

HIStalk Interviews Robbie Hughes, CEO, Lumeon

Robbie Hughes, MEng is founder and CEO of Lumeon of Boston, MA.

Tell me about yourself and the company.

I’m an aerospace engineer by background. I got excited about healthcare when I was given a problem coming out college, which looked to me like the normal sort of problem you would see in any industry. Fifteen-plus years later, I’m still doing it, because this is healthcare and things are a bit different.

Our product is the Lumeon Care Orchestration platform. We are a companion app for EHRs that automates clinical and patient workflows. The end result is a massive improvement in care team productivity that transforms the patient experience and improves the wellbeing of the care team more broadly. It’s a tricky thing to do, but we are lucky in that it works extremely well.

You said the last time we spoke that your product helps standardize decision-making rather than standardizing care. Can you give some perspective or examples?

There is a common misconception in the way people think about care processes, that a journey of care starts on the left hand side of a sheet or a screen and ends up on the right. That’s just not the reality we live in. Every patient is different, every disease progression, every care process is different. Things unfortunately don’t happen the way we expect them to.

But if you were to present yourself in front of a physician or a care team member more broadly, they would work you up following a relatively common set of protocols and methods. The output of that workup would essentially be a personalized care plan for you, based on what they see right there in front of them. Standard decisions are being made inherent to how care is delivered, but the way that we implement care from a technical perspective is to assume that care is linear and standardized.

The question becomes, how do you embrace that personal aspect of care that is delivered by care teams, but try to bring the operational efficiency that comes through standardization as you might see in other industries? This personalized yet standardized thing is a bit of a Rubik’s Cube that people struggle to conceptualize and to use in reality. But it actually boils down to one very simple thing, which is that the decisions of around what care should be delivered should always be consistent and should always be repeatable.

For a given presentation, you should always get the same output. That should result in some specific personal action, some specific personal activity for that patient. That inherently means that for every decision, you’re going to get a personalized output, and every patient’s care journey will be the product of a bunch of personalized actions — not standardized actions, but personalized actions based on standardized decisions. The trick to all of this, the trick to delivering great care, is how do you repeatedly and reliably deliver that personalization in a scalable form to create predictable — not standardized, but predictable — processes. Lumeon has worked at how to do that very well, one of the biggest misconceptions that sits at the heart of why scaling healthcare can be difficult. That’s the core of what our business does.

We’ve laid out EHRs so that other clinicians and even the patient themselves have to reverse engineer a bunch of chart elements to try to follow the thought process behind the actions. Are patients themselves usually aware of what their doctor is thinking and could technology help them understand?

That is the $84 billion question, isn’t it? I would reframe that a little bit. Why do we do what we do today? It’s worth saying I’m not a physician, I’m an engineer, so everything looks like a problem to be solved to me [laughs]. The way I think about this particular problem is that if you look at the way a care team practices today, there are these interactions I have with the patient, there are interactions I have with the EHR, and a lot of this stuff is based around this notion that I, as a care team member, don’t, necessarily trust what’s documented in front of me. I’m going to ask the patient or about their history. I’m going to order another MRI. I’m going to do all these things because I as a responsible clinician need to understand that what I’m doing is the right thing for that patient, and that’s a perfectly rational place for them to be. And in a world where people are paid on activity on a fee-for-service basis, that makes economic sense as well.

But in a perfect world, they would be able to look in the EHR and see a complete record with everything there. As a result, they wouldn’t need to reorder things and redo things, because they look at the documentation and say, OK, this is  complete, I trust it, life is good, I will do the right thing by the patient.

So back to your question, the way the patient perceives this is maybe inconsistent delivery, repeating things that they’ve already done, potentially gaps in care where mistakes are made or things aren’t followed up, et cetera. From a care team perspective, what they experience is the repetition of things that should have been done already, but they don’t have necessarily 100% confidence have been done to their satisfaction or done well.

The more we fragment care through increased specialization and more handoffs, the more this problem permeates. In a perfect world, all the documentation would be there. This is actually one reason that what Lumeon does is hard. If you’re trying to introduce automation into clinical care processes, there’s this pyramid of need, and at the bottom of it is complete and accurate data. If the complete and accurate data doesn’t exist in the EHR today, then how on earth can you hope to safely implement automation on top?

You get to the same situation that the care team has, which is that most of it is there, but not enough for them to be able to run it completely, so they ask the patient or they go to secondary sources of data. It’s similar to what we do. We create a composite record, we ask the patient, we ask the EHR, and we ask other secondary data sources and other authoritative records systems that we can speak to. We create this composite synthetic record that says, the EHR says this, the patient says that, the Surescripts or DrFirst or whoever else says these three things, and therefore we believe that the complete picture of the patient is this. And by the way, there’s a conflict between those two things, so we had better give that to someone to reconcile.

If you can create that trust in the data through this super record or composite record, and you can then use that to provide a basic level of cleansing and then ideally automation on top of it because that you’re missing things or things need to be sourced, et cetera, then you are automatically eliminating a huge amount of the stuff that plagues the care team from a busy work point of view. But you’re also joining things up incredibly efficiently for the care for the patient, because what they’re experiencing is direct, precisely choreographed outreach and engagement that is specific and individualized to them.

The psychology is interesting that providers don’t trust each other’s data and instead ask the patient or repeat the test.

It’s very unfortunate, isn’t it? The way that our chief clinical transformation officer would put this is, if we have to go hunting and pecking inside the EHR for something and can’t find it within 10 seconds, we just order another one. Because once you end up in this situation where you have a giant system of record with a huge amount of stuff in it, if it isn’t immediately available and reliable it, you automatically create this need for hunting and pecking.

Once you get into that situation, then immediately you are demotivating the care team. They have better things to do, so it’s easier to place an order, because obviously we have massively optimized for order creation instead of looking through retrospective or historical data to see if something exists. From a Lumeon perspective, or more broadly, from a care orchestration perspective, a lot of the value is bringing that relevant data to bear in the form of specific and automated action so that we can identify even before the encounter is open that we’re missing a couple of things and so we need to do something about it.

In fact, we are missing so many things perhaps that maybe this encounter isn’t worth having face-to-face. Maybe it needs to be diverted to a phone call or something else. That sort of intelligence, I use the word choreography, can be a massive driver of efficiency because it is eliminating that waste work that shouldn’t exist.

How has the business model evolved of an ecosystem between EHR vendors and companies like yours that can add value if given access to EHR data?

It is becoming increasingly clear. From a regulatory perspective, that the roles and responsibility of the EHR are very clear. It is a documentation system, a quality system, and a billing system. There is an entire industry based around the creation, maintenance, and support of that and the regulation around it. That is a treadmill that exists and will continue to exist for a long time. There is a further regulatory point around giving others access to the data that sits within that. Again, that’s only going to get stronger as payment models become more exotic and the need for data and the application of data becomes more acute. Now from an ambition perspective beyond that, it comes down to a cultural question, which is, what is the culture of the company and what are they trying to solve for?

A huge amount of the work that we do as a company is effectively services led. We are sitting with our clients. We are listening to what they do. We are listening to their challenges. We are applying our best practices and our tooling to address their specific challenges, which may be actually unique to them, but against a standard set of models that we have developed over time that we know to be good practices. What that creates is an organization that is obviously strong in product, but also strong in services, change consulting, data and insights, and integration. There’s a bunch of core capabilities that we need to have there and muscles that we are working, which are inherently different to other companies where, for example, maybe they sell something online, it’s very light, you click and you install. The muscles they are working are different.

Just as the comparison between those two companies is different, so the comparison between EHR company and a EHR partner company is going to be. Every company in its DNA has a purpose and has a trajectory that is set based on the things that they do that differentiate them. When a company tries to be everything to everybody, then they will end up losing some of that discipline and some of that excellence. That doesn’t mean that they won’t create a solution that is good enough for some use cases, but it would be exceptional if that company ended up creating the best-of-breed solution in all of those use cases. I don’t believe that you’ll ever see companies that dominate everything everywhere. My belief is that we will find that focus and discipline of execution creates companies that are differentiated through that focus and that discipline. That’s true for the EHR as it is for any other company.

The market has changed due to COVID, hospital financial problems, and hospital consolidation. How do you get a prospect’s attention when they are experienced change management fatigue or have a full plate?

The reason people buy Lumeon is because they have a urgent need to effectively do more with less. They will have strong opinions around how they want to deliver care. They’ll have a strong desire to grow, and they need to work out a way to do that in a way that they haven’t done before, which is to change their care delivery model so that it is supported through technology.

Our experience is that right now we are at a fascinating time in the market, where people are effectively creating rolling budgets. If you can walk in and partner with a health system and say to them, we are going to both improve the quality of care you deliver, drive more revenue, and make your care team happier, and do that on an ROI that pays back on a same quarter or same year basis, everyone is open to that conversation today. That’s a testament to how open people are today to change. They’ve seen what happened in COVID and what was possible. There is an urgency that I’ve never seen in the market to drive that kind of change. It’s incredibly exciting.

What are the company’s goals over the next three or four years?

From a product perspective, we are continuing to develop our knowledge library, our repository of best practice recipes of how to effectively do what I’ve described, do more with less, but in very specific areas. From a personal perspective, that’s the thing that I’m the most excited about. Its truly a knowledge and a knowledge library of how you go into particular use case areas — surgery, inpatient case management, ambulatory care, whatever it might be — what are the specific recipes that work, how do they get done, and what are the outcomes? That is my passion and that’s what we do exceptionally well.

We have started on this journey. We have more to do, but in the space of three years, we will have the most unbelievable content and evidence behind it. That’s the thing that I’m focused on, because it ultimately comes back from, we’ve done this because we’ve delivered these results for our customers.

HIStalk Interviews Ed Gaudet, CEO, Censinet

Ed Gaudet is founder and CEO of Censinet of Boston, MA.

Tell me about yourself and the company.

I’m a high-tech entrepreneur. I’ve done 11 startups throughout my career, mostly focused on building products and applying technology and automation to solve customer problems. I’ve done cross industry, everything from finance and energy to healthcare. I entered healthcare in 2010 when I joined Imprivata. I took Imprivata into healthcare, drove marketing and products for them, and then built their cloud platform for communications. We eventually took that company public and then private when Thoma Bravo purchased the company in 2016. 

I  left and attempted retirement, but that didn’t go too well [laughs]. My wife cordially commanded me to go find a job and get off the kitchen table. I started Censinet in September 2017, partnering with investor Keith Figlioli of LRVHealth. We found a syndicate of other investors and launched the company.

Who are your main competitors and what are your differentiators?

I saw while working at Imprivata this requirement to fill out security risk assessments. We used to joke that if you see one assessment, you’ve seen one assessment, because they are all different. They were in different formats, the questions were different, and semantics were different, so it took a lot of time. You could never get really leveraged. When I looked at problems to solve as I was exiting retirement, I kept coming back to this problem. What was interesting to me was looking at all of the alternative solutions that had been out there in the marketplace for probably a decade. Yet the problems — breaches, incidents, and attacks — were getting worse. Whatever we were doing in terms of trying to protect healthcare wasn’t working.

I looked at the problem around risk management in particular. I felt like there was an opportunity to disrupt the market and do something completely different to ultimately move the needle in risk and start to take out risk in healthcare. That was the idea behind it.

Some organizations aren’t what I think of as competition, but they they were providing solutions at the time. They were doing assessments through a combination of technology and services. You had folks like HITRUST with their framework. Then there were a bunch of early-on entrants that were trying to automate the problem through a pipeline approach, a single application, and you couldn’t get leverage.

For example, if Intermountain was using a single application to manage risk, and Cedars-Sinai was using the same application but they weren’t really connected, where’s the leverage? In looking at other markets, technologies, and architectures, I had this epiphany that we should put it on a network. We should think about it as a multi-sided platform. Could we streamline the automation on an exchange, a platform that was connected to the different actors in that process of managing risk information, and ultimately put controls in place to effectively reduce risk over time?

What are healthcare’s risks and how do they compare with those of other industries?

I learned through the Imprivata experience that healthcare is different. It is an ecosystem in and of itself. It’s a large ecosystem. The workflows are different. The requirements are different. The regulations are different. Other competitors or solutions were taking a broad approach to the problem, but I felt like we had to be purpose-built for healthcare. We had to think about the problem through the lens of the CIO and the CISO in healthcare and not worry about other industries, because the problem is so big.

We started with third-party risk. We thought about the vendors and those products and services that they were providing to the health systems. How that could affect risk. At the time, the percentage of third parties that were involved and integrated into the business process of health systems was fairly manageable. But in the past five or 10 years, that percentage has grown exponentially. You’re seeing every business process in a health system directly being run on some type of digital or IT infrastructure or technology.

Cyber risk was mostly in IT problem. Your IT organization would manage the security risk assessments, the process for collecting the data, create the remediations or corrective action plans, and manage that through the business. Cyber risk is now enterprise risk that affects every single department within a healthcare organization. Every business process is affected by cyber risk, because they rely on technology to do their work.

That has made a big impact on our overall strategy and where we’ve taken the product. Where we started with third parties and built the platform, today we have over 34,000 assessed vendors and products in our digital catalog. On the other side of the network, we have over 100 customers across more than 500 facilities. The network is growing, and every new provider we add, every new vendor we add, has a geometric effect. Providers bring new vendors, new vendors bring new vendors and new providers. There’s this flywheel that happens. We get this incredible network effect on our platform, which drives a number of benefits to the participants. 

Part of the vision was that if we’re going to solve this problem around risk and around cybersecurity, we have to take a page out of the bad guys’ playbook. If you think about what they’re doing and why they are so effective, they are organized. They have a cyberattack conveyor belt. They have applied manufacturing principles to cyberattacks. They have this concept of micro services, where each person has a certain role that they manage in the attack. It’s not just one person doing the full stack attack. That organization has made them effective and dangerous, yet from an industry perspective, we haven’t come together. The vision for Censinet was a platform to facilitate that ability to drive that leverage and drive the power of the community to protect itself.

Many recent incidents involved business partners or external technology vendors. What do you look for and what do you provide to the organization that engages with you?

Our history from an organizational perspective is third-party risk. We’ve leveraged that into other areas of risk management. When you think about an initial customer implementation, the customer comes on board and they can easily and quickly start sending out assessments in the platform. They’ll search for a particular vendor or product. They will use the platform to send out an invite that vendor and its products into that process. The analogy is where you want to do an assessment on a vendor and its products and you send out any email with a spreadsheet. We’re automating that workflow and sending out an email with a link to the portal.

The vendor fills out the questionnaire, attaches any supporting evidence or documentation to their claims, and it sends it back to the provider. The provider then has full automation capabilities for things like rating and driving corrective actions or remediations automatically, or they can do it manually in the platform and they can generate all their reporting through the platform as well. That end-to-end process, without us, can up to six weeks the first time time a vendor comes on board. Our SLA guarantee is 10 days or less for that full assessment, which is incredible. The next time that vendor gets asked to do an assessment by somebody else in the platform, it’s a click of a button. The network effect continues to drive that value as more people are added to it. It increases over time and it’s exponential. 

We are doing not just that facilitation. We are also doing those governance functions. We’re driving the curation of the assessment data, the questionnaires based on the regulations that are ever changing, as well as the corrective actions. If a vendor answers in a certain way and risk is generated, then how do we correctively reduce that risk? What do we put in place to move that risk from a certain inherent risk to a residual risk that we can accept as an organization? We do that all on the platform.

Typically without a platform like ours, you do a point in time, set it and forget it. I’m going to purchase this product, I’m going to do risk, and then maybe I’ll be able to do a reassessment at some point, which nobody ever does. With our system, once you do your initial assessment, you’ve got the data in there. You can automatically set up a reassessment for some time, usually a year later. You can tier that vendor into a critical, high, medium, or low tier, which can drive automation on the back end. You have the ability to periodically and continually assess that vendor and their product or products based on maybe a scope change.

For example, if you just set it and forget it, you miss the ability for risk to appear based on some type of scope change. Blackbaud was a donor management that many health systems used a few years ago. On paper. it seemed like it was low risk. No PHI is going to be on this, so we’ll send it through a low risk assessment process. Users changed the scope of usage, and introduced risk, by putting PHI in the application. Because nobody was looking at it, nobody was continually assessing it, they missed it, and it caused a huge breach issue across a number of health systems. 

Having this lifecycle approach is another differentiation that we bring, and an innovation that we bring, to the marketplace. Think about it as a longitudinal record for risk in the same way that the EHR is that longitudinal record of care.

Customers are always faced with the decision of how much they are willing to spend to mitigate whatever risks exist. What framework do they use to evaluate the exposures you call out?

Without a system like this, they are rolling the dice. It’s anyone’s guess. There’s an inability to manage a risk program in a way that can be data driven because the artifacts are scattered. They’re not centrally located, they’re not pulled together, they’re not driven through automation. They might be in emails, spreadsheets, sticky notes, and conversations, so the ability to assess all third parties is difficult without a system like ours.

You have to automate that process. You could have 1,000 vendors with 2,000 products in your environment. You start to apply a solution like ours. Those have to be added to the system. That data has to be captured through maybe a reassessment that can be automatically set, because every day that goes by, someone is buying something new that needs to be assessed.

We often see customers will start with net new vendors and products and quickly realize, wow, we have all these other legacy products that we have three-year contracts with. We need to add them to the system as well. We encourage that, because ultimately you have to understand what that risk is. With a system like Censinet, it doesn’t take a lot of time to do that. There are tools to basically apply tiering to those different vendors and products. Which by the way, people do regardless of whether they have a system or not.

Let’s say they have a handful of products, but they’re doing it manually. What we find is that there’s this tiering that happens a priori before they even do an assessment. They will say, we can’t handle everything, so we’re going to make some judgments. We’re going to stratify artificially these vendors and products into buckets of risk. That’s high, that’s critical, that’s medium, that’s low. But there needs to be a true business impact analysis, where you’re understanding the product and the vendor relationship through the eyes of the business, because ultimately they understand the importance and criticality of that product, not the IT organization. 

There’s this real disconnect with the risk management programs that occurs. Everyone thinks they are doing the right thing by doing these assessments, but there needs to be a broader rubric and a strategic lens to apply across the organization when it comes to risk. Because as you said, you otherwise could be spending a lot of money and getting little benefit. We see that all the time. We see organizations throw point tools at the problem and not think through strategically how to manage risk. Not just today, but in the future.

If you take a tool and you apply it to a terrible process, you’re going to get a terrible result. Vice versa, if you have a great process and you apply a terrible tool, you’re going to get terrible returns. If the tool is good, then the tool should inform the process. The leadership team needs to take that into consideration when they bring these things on board, because they are transforming their organization. They should be open to that. They should be willing to change, because ultimately they’re going to have to change to stay in the game. It’s no longer good enough to throw spreadsheets at this problem. You need a better approach, a more strategic approach, that includes the right resources, the right process, and the right product or technology to move the needle on risk.

What will be important to the company over the next three or four years?

When we first started off with third-party risk, our customers would come to us and say, we love what you’re doing with third parties, but we have another dozen or so risk processes, silos if you will, within the organization. For example, Intermountain said, we have institutional review board processes and we do a number of risk assessments, but we do it in a different product. We are holding this thing together and we have people supporting it. Can you consolidate it on your platform?

We’ve been working with our customers to identify those silos of risk and consolidate them on the platform. We’ve added things like IRB and the ability to do enterprise risk, where the health system can assess its own facility, its own operations, using NIST CSF, using the health industry cybersecurity practices, the HICP framework. Those are being recognized as security practices. In the event of an incident, if you an prove that you’re following the NCSF and applying it, or HICP, and  there’s some type of event or incident, OCR has to take that in consideration as part of some recent regulation. Public law 116-321 provides — I hate to use the word safe harbor, but effectively it’s a safe harbor – if you do the right thing from an enterprise risk perspective. 

We look at M&A transactions, the risk involved with acquiring a new organization, and assessing the risk of that and how you bring that into the platform. If you’re building applications internally or doing integrations, those require assessments as well. You can do that now on the platform. We started off with technical suppliers and technical products, but what about the non-technical suppliers, like a laundry service that may be critical to a health system? The health system is so large that it requires a certain laundry service, and maybe there’s only one that can service them accordingly. What would happen if that laundry service was hit with a cyberattack? That hospital wouldn’t be able to function without laundry. 

Elements of suppliers that are non-technical could have huge impacts to health systems. Maybe the organization is thinking about those, maybe they’re not, maybe they’re in a different system. Medical devices typically are being managed through the biomed team, but there should be some connection with the IT team. Why are they doing it in two separate places? Why are they doing it with two separate processes? We are starting to see the consolidation of all these silos of risk on the Censinet platform, which continues to drive down the unit economics for our customers and deliver interesting, unique value.

HIStalk Interviews David Lareau, CEO, Medicomp Systems

David Lareau is CEO of Medicomp Systems of Chantilly, VA.

Tell me about yourself and the company.

I’ve been with Medicomp about 20 years and CEO for 10. Medicomp’s core business is connecting all of the clinical information and data that is in an EHR, whether as terminology codes or free text, and making diagnostic sense of it, either for the providers at the point of care or for people reviewing the record for diagnostic relevancy, which is important now with Medicare Advantage and value-based care. We’ve been building this for 45 years. It seems that the industry is moving in the direction of not just trying to paid for transactions and coding them, but getting paid for caring for patients effectively and proving that it was done. It’s an exciting time for us.

Doctors say they are burned out from keystroke overload and entering data that doesn’t contribute to patient care. How might that situation improve?

There are a couple of ways to go about it. If you approach the EHR like a burden, as most of them are now, you’re just trying to isolate the clinician from the EHR. Ambient AI is a play in that space, saying that we’ll just listen to what’s going on in the room, and then maybe at the end, we’ll tell you or a reviewer that you have to meet these quality measures and your documentation might not be sufficient to pass a Medicare audit. Capture stuff at the point of care, get it coded as best you can, but don’t really use the EHR as a tool for the clinician. Just try to isolate the clinician from the usability of the system.

Or, you try to put the information in front of the clinician, at the time they need it, for the patient and the condition or multiple conditions that they are dealing with. Here are the clinical quality measures that apply. You’ve met the documentation requirements. You have all the information properly done. Then present them what they need, when they need it, so that the EHR becomes a data repository, not a repository of text and other stuff that has to be dealt with after the fact. If you can’t do that, if you just keep popping up stuff that’s not clinically important when they are thinking clinically, they are going to get burned out and they will be frustrated. 

Value-based care, 21st Century Cures, and TEFCA have increased the need for what we think of as diagnostic interoperability. Either diagnostic interoperability between systems or diagnostic interoperability between the clinician and the system itself, saying, I’m dealing with this patient. They have these conditions. Show me what I need. Show me what reflects the way I think and work. Also, let me complete my work here and get on to the next patient.

One of the big things that people contact me about is Medicare Advantage. Medicare Advantage is not saving the government the money that they thought it would. There’s more and more people of the baby boom generation retiring and they are living longer with chronic conditions. We have to bend the cost curve down. How do we do that? One solution they’ve come up with is to take better care of the patients and their chronic conditions. CMS has said, we’re going to come and look at your records, and we want to see evidence that you have managed, evaluated, assessed, and treated every one of these conditions for which you’re claiming risk adjustment and risk adjustment solutions have been on. Make sure we get these things coded so that we get a higher risk adjustment factor for each patient. Fine, but are they really taking care of the patient? Does their documentation prove it?

That’s where we are seeing the most interest in what we do. At HIMSS, we will be promoting whether you have the processes and technology in place to protect yourself against Medicare Advantage fraud audits, because that’s about managing patient conditions, not just getting the diagnosis code right. We’re getting lots of interest on that from people who haven’t talked to us before.

It’s an exciting time to be in our industry. Some people get excited about AI, and other people poo-poo it. There’s a great place for it if you have good, clean, high fidelity data. Then it can empower these learning models and algorithms. The industry is in such a state of flux because of all that. W are just glad we are in the space we’re in.

Microsoft and Oracle are now deep into the healthcare application area via acquisition, and both companies have placed big bets on cloud and speech recognition. What changes do you excpect and how will they affect other companies?

There’s a great place for speech, text, and the technology. Natural language processing, NLP, which a lot of these approaches rely on, provides at best 75% to 85% data fidelity. Most of those systems are trying to find codes in text – SNOMED, ICD, CPT – through language models. They work pretty well, but when you are trying to get a full clinical picture of the patient, you need to turn all of that into computable data that you can filter diagnostically. That’s what enterprises are being asked to do. Manage these patients, especially under Medicare Advantage and value-based care, manage their chronic conditions, and show that you did it. A lot of the models are relying on reviewing that stuff after the fact to make sure we did it.

We were pretty excited a few years ago when we got approached by Emtelligent, which has a natural language processing engine. They wanted to add our concepts that are in our engine to the roster of vocabularies they looked at. I told them that we weren’t really interested in that, but if they could do a version of their engine that targets our vocabularies, then we can filter that stuff diagnostically. We can take the text record and say, show me what in this record applies to chronic renal failure versus diabetes and then pass that to algorithms that say if it looks like it’s documented adequately to pass a Medicare Advantage audit or not. There’s a real exciting mix of voice navigation and voice capture of information, but that still needs to be turned into data that is computable. We sit in the middle of all that.

How does the growth of ChatGPT and other AI tools impact company strategy?

The Gartner Hype Cycle says that it takes a while for hype to build, but I’ve never seen such an upward thrust in the hype cycle when ChatGPT came out from OpenAI. But there are valuable uses for this, because that kind of technology at its core does statistical analysis of data and pattern recognition. If the data is good and the information that you’re trying to process is best processed as data like they’re seeing now — images, MRIs, and mammograms in a consistent format – there’s an opportunity to get high fidelity data out of that and apply AI to it. 

Machine learning is valuable for remote patient monitoring, for patients who are willing to do it at home, for monitoring their hallmark findings for chronic conditions. Trying to support the clinician at the point of care is problematic, unless you just say that we’re going to use this stuff to capture all the information. We’re going to use voice, speech, and sound and turn it into something and then process after the fact to figure out if we have gaps in care. That whole framework for where this stuff is and where it fits now versus in 10 years, we are constantly looking at that.

We’ve decided for now that our place is to make it possible to take in all this information — whether it’s text or codes from these various terminologies and code sets — diagnostically organize it, and present it back to the user. Eventually that kind of information will be valuable for ChatGPT or other AI algorithms that then apply machine learning to detect patterns that would otherwise not be detectable. We are constantly looking at that. 

People used to call our stuff AI back in the 1980s, not the same way that people do now because we built it using physicians who determined what’s appropriate when you’re thinking of one diagnosis versus others. That’s valuable data. Getting data acquisition and being able to diagnostically filter it is important. We do that pretty well. If people can start applying AI and machine learning to the data to our data points, it will be valuable. We’re pretty excited about it.

ChatGPT provides a chatbot-like response to user input as an ongoing conversation. Will that affect the usual software design paradigm of static screens full of data entry fields and submit button at the bottom?

The chat paradigm is an evolving target. As a conversation proceeds, different things seem to become relevant. The challenge is that clinicians, not just doctors, are pretty highly trained users. They’re not like me going out on the internet and typing in a few searches to put together an itinerary for a three-day visit to Phoenix, I don’t know anything about Phoenix, never been there, so it’s a good tool for that.

When you’re dealing with a highly trained clinical user, and when you think about physicians — medical school, internship, residency, their experience – they are already pretty good at clinical pattern recognition. They would like systems to present to them what they know they need to do their work. That’s what we try to do.

ChatGPT does that by searching the internet to find things that the user is not familiar with and and constructs information for presentation. Our engine does that from a diagnostic framework, pulling all this stuff together. But the technology inside things like ChatGPT will be more useful to the clinician when they’re dealing with conditions that they are not familiar with. For example rare diseases. The National Organization of Rare Diseases has a list of 1,100 to 1,500, depending on how you count them. Rare diseases that in some cases, if detected early, will lead to much better outcomes. If missed, there’s not much you can do about it. You can’t really prompt every clinician to consider the symptoms, history, physical exams, and tests that are relevant for every diagnosis the patient might have.

But with artificial intelligence running in the background, you can present the things to the clinician that make it usable for 98 or 99% of all patients. An algorithm runs in the background that says, this patient might have this condition. If you want to see the hallmark findings of it, click here. If not, go about your work. They tell doctors in medical school that if they hear hoof beats, think horses, not zebras. For things like the zebras in medicine, AI and machine learning could be valuable.

Medicomp has made few announcements of executive changes, acquisitions, or funding, which usually dominates the headlines of other companies. How does that position the company in a challenging economic environment?

People have a tendency to chase the latest hot thing. If you guess right, great. But if you guess wrong and you give away equity or control, you can no longer focus on what the core business is or the core value that you bring. We’ve been clear from the beginning that we wanted to focus on providing a tool that presented information to clinicians, the way they were trained and the way they need it. 

To do that, you need patient capital. You can’t chase quarterly results. You have to approach your people as the most powerful, valuable, and non-replaceable resource in the company, because when you’re creating software and intellectual property, turnover kills you. Change of focus changes or ownership kills you. People say, we’re such and such and it’s in our DNA. I always say to them, yes, until you get a new CEO, and then who knows what’s going to happen? 

We’ve been consistent in what we’re trying to do. We’ve never gone into debt. We don’t chase the latest thing. We’ve always thought it was going to be critical at some point in this industry to move away from tracking transactions to get paid to tracking conditions to get better outcomes. Our engine was built to do that. We’ve been able to retain that focus and get enough people interested in using our stuff so that we had the revenue to stay on track and we had the opportunity to continue to our core engine and all the mappings as the industry changed. Then, adapt for what we needed to for our core mission, which is diagnostically connecting data and presenting it and tools for documenting it, if people want to use our documentation tools.

Changes are fine if you really need to change your focus, vision, or mission. Peter Goltra set one out for us a long time ago and we’ve been able to stay with it. We’ve been pretty happy with that. It has also allowed us to keep the people we need to adapt to things like Meaningful Use, 21st Century Cures, ECQMs, quality control measures, and TEFCA interoperability. Figure out what you’re doing, get really good at it, and stay at it until something tells you you’re doing the wrong thing. So far, we’ve been fortunate that we seem to have made the right big choices whenever we needed to.

What elements will be important in the company’s strategy over the next few years?

We think the healthcare IT industry is on a path to realizing that the clinical record of a patient, regardless of where it resides, should be computable data that will power analytics, AI, and machine learning. The challenge is going to be filtering that data and presenting it to the various people who need it and meeting all the requirements that are being forced down on the providers by all kinds of things. Home healthcare has a set. Hospitals have a set. Ambulatory has a set. 

We think that over the next three to four years, we will see an increasing move and realization that the important thing is caring for the patient using AI machine learning, and other techniques for identifying people in a population who are at risk. But you still have to somehow deliver the care for each of those conditions, one patient at a time. The industry is coming to the realization that it would be much better for these health information technology systems if we had data, not just a bunch of stuff electronically stored. We are excited because of the realization in the industry that data is paramount to everything.

HIStalk Interviews Steve House, Managing Director, Baker Tilly US

Steve House is managing director of Baker Tilly US of Chicago, IL.

Tell me about yourself and the company.

I realized the other day that I have entered my 40th year in healthcare. I started back in the early 1980s as a biomedical engineer for Phillips Medical for a decade, and then GE for a decade. I did work for Aetna building ACOs and then Kaiser as a senior director of data. I’ve been around in different spaces around the healthcare environment for a while.

I joined Baker Tilly a year ago. I am a subject matter expert in healthcare. My official title is managing director. I go out and do a lot of strategic work for hospitals, doctors, insurance companies, things like that.

Baker Tilly is fundamentally a tax and audit firm that was started back in the 1930s. It has expanded into all kinds of areas. We have a digital division that does ERP implementation. We have a robust Oracle team. We have an EHR team that was an acquisition of Orchestrate Healthcare. We do strategy service line analysis. We do all types of financial, technical, and clinical sustainability type programs. It’s 6,600 people, almost a billion and a half dollars in revenue, so it is pretty good sized, I think about #9 on the overall consulting size list.

How has health system C-suite leadership changed its thinking about health IT?

It has been a pretty big change and it’s going to be bigger going forward. We have a big labor problem. You have technology like the EHR and work that augments it. That technology is great to have, but it can’t slow doctors down significantly. We have big shortages in primary care, internal medicine, and obviously mass shortages in nursing, so the technology needs to be enabling.

We went through a phase of nearly 20 years where we were getting a handle on the data and making sure that we made it interoperable. It’s not all the way there, but certainly all those things were factors. Now we have to put doctors and nurses in a cockpit of a jet fighter-like concept, where they get the data they need and can make quick, accurate decisions and move them forward. We are in the midst of that transition, and I think it’s absolutely necessary.

Will technology-enabled telehealth and virtual monitoring allow healthcare to become more scalable and then more affordable or more accessible?

Yes. I’m in charge of our hospital-at-home programs. Plenty of people are looking at programs like that, where you are distributing healthcare services differently, in which patients and caregivers become more engaged. You have tools, technologies, social determinants, and an ability to look at it in simplified media formats, like a mobile phone. Suddenly, some of the labor that you need for delivering healthcare services is going to come on behalf of patients and their caregivers themselves as they invest and get engaged in the process. That has the potential to give us the greatest improvement and maybe put us on a path where we can actually succeed in this.

How will patient perceptions of the healthcare system change as more and more physicians become employees of entities whose primary objective is profit?

It’s always going to come down to access first for patients. When you need the system, is it available to you? We have significant access problems because of labor issues. Physicians being employed is, on the face of it, OK as long as you don’t lose productivity and therefore reduce patient access to the system.

But there’s also the other factor, which is that around the world, cost and outcomes — outcomes being lifespan and quality of life — have significant patient incentives. If you’re going to employ doctors and you’re going to have an issue with access because of labor pool problems, the most important next thing you can do is to make sure patients are incentivized to help themselves. You’ve got to make it comfortable and possible for them to manage their own healthcare at some level, and they must be incentivized to do it. Otherwise, it will just become a growing burden cause of aging.

What will happen as ever-larger health systems and insurers encroach on each other’s turf?

A debate has been running in the areas that I travel around the United States about the difference between medical care and healthcare, healthcare being population health, preventative medicine, the things that we do in that category versus, medical care that hospitals and doctors are fundamentally trained to do. If the insurance companies creep into this space in a significant way, the question is, should we think about splitting healthcare and medical care?

In other words, are hospitals and doctors the best places to do preventative medicine, nutrition, counseling, fitness, and weight management? Or did insurance companies find a way to do that part themselves? They try to pay for it, although I don’t think it is always paid for it at a level it should be. But the bottom line is that as they creep in, hopefully they take their biggest incentive — which is reducing variability and outlying costs because people get sick quickly or they’re not maintaining their health — and address that issue directly. If they did that, the system would work better for the patients.

Is it reasonable to expect most people to monitor their own health and use wearables, or is that just a nice idea that will impact only the few people who are willing?

I saw a statistic recently that of all the people who have a gym membership in the United States, somewhere around 4.5% actually use it. I don’t think that’s an indicator that we have got it figured out. Not everybody has to go to the gym, but I was on a task force during COVID and we determined that the average 80-year-old has lost 80% of their lung capacity. That’s obviously a huge danger sign for people with respiratory viruses. The bottom line is no, we have not done a great job of it.

If you take a system like Singapore, they use HSAs, and if you maintain your health and you meet criteria for blood pressure and weight and things like that, many of the dollars that go into your HSA that you’ve saved automatically become your retirement fund, and you don’t pay taxes on it. Those folks over there using that type of system, and they’re not the only ones, do a tremendous job of maintaining their health and staying in shape because they really want to retire. It’s that simple.

What are the technical priorities of health systems?

There’s still a lot of work to be done on the EHR side. Integration work needs to be done to finalize systems. We talk sometimes about a post-EHR implementation world. I don’t think we’re there yet. You have to go from gathering data, stewarding it, and placing governance around it to actually making it more usable. That’s the next phase and hospitals are looking at that.

The other side of healthcare is whether CFOs, CEOs, CMOs, et cetera have enough information to understand how to compete effectively in their own markets. It is still competitive marketing. Competition in healthcare is good for all of us because it drives better and lower costs. We must do a lot better job on financial reporting and cost accounting. We must do better on issues surrounding the data that we provide people so they can make better decisions in their markets.

What parts of health system digital innovation will stick?

Anything that can allow a patient to make a good decision when they need healthcare. If you’re at the mall, start to feel sick, and don’t know what it is, is there’s a kiosk there that gets you good information or provides contact with somebody who can answer your question on whether you should go home and take an NSAID or go to a hospital urgent care? We still haven’t gotten that figured out and we need to. On the patient engagement side, it’s making information available to patients so that they know how to make routine decisions. It’s all online, but not as functionally usable for patients as it needs to be.

As someone who ran for Congress, what do you expect to see from a political standpoint that will make US healthcare different in 10 years?

The one thing that you get when you are in Congress, or are running for Congress, is that there are 10 lobbyists for every member of Congress on the healthcare side. Political will is butting up against the lobbying process that goes on.

There’s a lot of things that should change, including how we manage PBMs, what safe harbor was intended to be back in the 1980s when it was passed, to how we pay for it. Even the fact that Medicare itself is both a payer and a regulator, and when you’re a payer and a regulator, that’s a disconnected process structure and it should change.

Will it change? We’re sitting at 20 or 21% of GDP. A point will come where if it doesn’t change one way or the other, the system is going to break. Some people want single payer, some people want more competition. I’m not a fan of the single-payer idea. I don’t think that’s going to work. But the bottom line is that if something doesn’t change soon, the sheer weight of the cost is going to become a problem that breaks healthcare down.

What factors will be important to the company and the US health system in general over the next few years?

I think it’s process change culture. There’s a lot of cultural issues in healthcare. The first question I ask any healthcare executive these days is, how is your culture? Are you capable of changing? Have you imagined a different environment? Do you have the information and reporting to give you enough decision-making capability?

Some organizations in healthcare have spent a decade or more just training their own leadership on how to make decisions and do it quickly. Healthcare needs to get faster, a lot faster, on the diagnosis side. A lot faster on the change management side. A lot faster on the decision-making side. That’s probably the area where we need to do the most work. Baker Tilly, as a strategic consultant and someone who does operational work, is focused on those areas.

After spending so long in healthcare in my career, I cannot wait to see this next phase, where data use rather than data aggregation and interoperability becomes our priority. What we can do with tools, devices, and modern concepts of how doctors will interact. The average doctor has 16 minutes to spend with their patient, and 11.3 minutes of that is used to input and take data out of an EHR. That’s not an equation that works in the long run. I have confidence that we’re going to see massive quantities of new technology and ideas come up to help solve that problem.

HIStalk Interviews Sachin Agrawal, CEO, EVisit

Sachin Agrawal, MSc is CEO of EVisit of Mesa, AZ.

Tell me about yourself and the company.

I’ve been in healthcare consulting and software for 20 years, always focused on the enterprise needs of hospitals and health systems in areas such as revenue cycle, physician network alignment, quality and safety, et cetera. I joined this business about six or seven months ago and took the CEO seat on January 1.

We are network-agnostic virtual care operating platform, primarily for large operators of physician networks and all the professionals that surround them. Typically hospitals and health systems and sometimes significant category leaders in other healthcare delivery categories, but mainly focused on the underpinnings of operating virtual care for these big healthcare delivery orgs.

How would you describe the virtual health technology marketplace?

It is asymmetric in terms of how I’ve seen other HCIT markets operating. It was forced upon everybody, but from the perspective of providers, it was forced upon them for obvious reasons. But it  not one that evolved from the critical foundational needs that hospitals and health systems have. 

As a result, a lot of health systems are picking their heads up, now that we are a few years out from the onset of the pandemic, and saying that they were forced to drive a modality that has been disruptive to their core operations rather than additive in all the ways that they need to be, given the economic climate. I was surprised by that as an outsider. I understood the needs of the providers well, but as an outsider from virtual care coming in, I was surprised by how much of the evolution of the market, from an intelligence perspective, has remained at the surface level despite the tremendous utilization that we saw the past few years.

Providers didn’t have a choice about implementing virtual visits as the pandemic started, but some brought in telehealth companies that use their own medical staff. How are heath systems valuing telehealth’s value to their brand or as it relates to their other services?

This is a head-scratcher for me. It’s puzzling to have seen hospitals either promote the utilization of those networks or let those virtual-first networks promulgate and post up in their back yards. That goes everything that I’ve learned about what complex healthcare delivery organizations are trying to do, in terms of raising the bar on quality and safety, balancing fee-for-service reimbursement with value-based reimbursement, looking at network leakage and network integrity, and things like that.

The common denominator across all those topics is that hospitals and health systems have been focused on tightening their networks, clinical integration, physician practice alignment, and increasing M&A to employ clinicians. I look back on that and it’s puzzling, because in a lot of ways, it’s the antithesis of all those things.

Hospitals and health systems are picking their heads up and saying, this is not aligned with the Quadruple Aim. We need to do something about it in the medium to long term, but we also have to figure out how to engage with those networks in an appropriate manner in the short term, because  going cold turkey is challenging in this labor environment and in this cost environment. There’s a tough needle to thread for healthcare delivery organizations. They are talking to us all the time about how to thread that needle.

How has the patient and provider experience changed as telehealth has moved from a quickly implemented solution to a permanent strategy?

The impetus during the pandemic was to take what was inherently meant to be a brick and mortar set of clinical protocols and a brick and mortar operation and just virtualize it. I’m quite explicit about painting the difference between virtual and digital care. Virtualizing care is what we just talked about — what organizations had to do. Now the industry is at its inception of the next chapter, which is to digitize aspects of care that they otherwise didn’t have the time to think about – design, change management, organizational buy-in, and things like that. That impacts how service lines themselves in a world where you can be digital first. It impacts who’s doing what in terms of top-of-license activities versus bottom-of-license activities. It impacts where people fit.

I can’t tell you how many stories I’ve heard about the pandemic when clinicians were still going into their offices, obviously socially distanced, and doing virtual visits out of the office. That’s not what the promise of virtual care was meant to be. Virtual care itself needs to go through this digital evolution while obviously honoring the systems, processes, and workflows that are in place, many of which are focused on clinical satisfaction, safety, and things like that. I don’t think there needs to be a revolution, but a thoughtful evolution that we’re just at the beginning of now that we’re picking our heads up post pandemic.

How do virtual care needs vary by specialty?

Significantly. I’m excited to see the data around providers leveraging their own networks and clinical protocols in a virtual way to drive similar, if not better, quality and safety outcomes et cetera. It’s great to see the early data on that. What’s needed going forward is both the complexity and the opportunity of going from virtual care to a digital evolution as use cases expand. 

As you go from urgent and primary care up the ladder to things with higher acuity and higher complexity, there could be device dependencies. There could be wearable dependencies. There could be group consultation needs and things like that. Importantly, you need to go from just a provider-to-patient relationship to potentially many providers per patient relationships, or many providers to many providers type relationships to drive complex consultations. That ecosystem, in terms of the need to create connectivity and to do that process and service line that I’m talking about, is going to be underpinning unlocking additional value from virtual care efforts.

What are some telehealth best practices that can help physicians work at the top of their license, such as pre-visit chats and triage?

That is part of an important broader question around what we can do to alleviate the burnout issue and the turnover that happens, which then impacts the high cost of recruiting, credentialing, and privileging clinicians to get back on the front lines. I’m reminded of a story of a customer who is the middle of digital reengineering as opposed to just virtualizing brick-and-mortar care. They are one of the more progressive institutions that I know of in the country, a Top 15 health system. They measure very carefully evening pajama time, where clinicians come home after  busy day, spend time with their families, and then most likely after hours after kids are down and settled in, they are logging right back into the EHR and doing complex charting. It’s because they had this backlog as they went about their visits throughout the day.

This is a critical piece when it comes to the top-of-license question. Pulmonologists didn’t go to school for decades to sit at home in their pajamas doing charting. This could be impacted on the front end through the intake process, the virtual triage process, and the asynchronous process where patients can assume more ownership. It should happen throughout the process as well, in terms of removing the barriers to documentation and charting. Then on the back end, the integration into the leviathan health systems,  power health systems like EHRs and revenue cycle. 

I think of it as the underlying need for integration throughout the process — beginning, middle, and end — to drive down things like evening pajama time. This institution would tell you that, as they have seen a drop in that based on digital re-engineering, they can directly tie that to a drop in turnover and therefore in recruitment and backfilling costs. It’s a KPI that they are looking at carefully, which is the promise of digital as opposed to sticking to your brick-and-mortar workflow and hoping for the best.

What do you expect to happen with telehealth when the public health emergency ends on May 11 and rules and payment policies go back to the early 2020 world?

It has significant implications. There’s a reason why pre-pandemic, the system was largely averse to some sort of a national credentialing or privileging approach, or even a cross-state credentialing privileging approach. First and foremost, we’re probably going to go back to life as we knew it before the pandemic from that perspective. That puts a significant accountability right back onto health systems to do credentialing in multiple states and cross-state privileging and things like that, which is a huge lift. They are already dealing with significant resource turnover. Just keeping up with the credentialing and privileging activities in their home state is drowning them. I think we are going to see a consolidation of where providers are able to practice virtual care. The other thing this will highlight is the need for those higher-acuity use cases that you are talking about.

Even within state borders, we’re going to see a greater separation of access to care. This is all driven by social determinants of health, access to specialists and subspecialists. Health systems will have an accountability. They’re going to have these key resources largely aligned with them, the subspecialists, that they need to find a way to liberate their time to cover a broader swath of a population even within a state. It’s going to beg the critical questions of how to re-engineer our processes to digitize that so that we can have our most important resources go further at the top of their license.

What changes do you expect to see in the next few years that will affect the company and the industry?

We have set up our company’s strategy to align directly with where we think the industry is going. I’ve been around the block in healthcare and I’ve seen platform categories come up over time. Usually these platforms are filling a critical void that exists between the core hospital systems, some of which I’ve mentioned — scheduling, EHR, revenue cycle, and digital front door if that comes into maturity. There’s a gap between what those core systems do and how to re-engineer care or to drive the efficiencies and to drive quality and safety standards up.

For the industry, as the dust settles on a pure outsource model to virtual networks and things like that, and there’s increased focus on how to we assume command and control of this as a health system, the industry will need a platform layer. I’ve talked to many CIOs and CMIOs in the past six months, and two of them from Top 10 health systems have described this as a need for a middleware to integrate in and out of the core systems, to author workflow, and to ensure that those workflows are being set up for the right people to do the jobs at the top of their licenses.

That’s a complex set of needs that needs a dedicated approach. That market will have plenty of room for participants, because the needs that it addresses are going to be significant. Of course we at EVisit are setting up our strategy to be one of the emerging leaders in what we believe is going to be a really exciting category in healthcare delivery.