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.

HIStalk Interviews Adam McMullin, CEO, AvaSure

Adam McMullin, MBA is CEO of AvaSure of Belmont, MI.

Tell me about yourself and the company.

I’m thankful that I found my way into healthcare in 2006. I had worked around the US and the globe helping companies operate more efficiently by adopting technology. That was intellectually interesting. Getting into healthcare changed my life. That connection to the mission and how you can impact and help care teams and patients helped me find a sixth gear.

Before I got into healthcare, all I knew about healthcare was that a nurse agreed to marry me. It’s an odd coincidence that many of the businesses and teams that I have been involved in a focused around serving nurses with clinically-led and technology-enabled solutions.

AvaSure is the leader in acute virtual care. We are in about 1,000 hospitals, including all of the Top 10 US health systems, one-third of the magnet hospitals, and 70 academic medical centers. We help our customers adopt virtual care to get better outcomes at a lower cost.

What are the clinical and business benefits?

That strong ROI was one of the things that attracted me to AvaSure. The ability to both operate demonstrably more efficiently while having proven clinical outcomes was to a level I hadn’t seen. AvaSure pioneered the tele-sitter market. About 20% of patients have a clinical need for observation, but only 10% or less actually get an observer, which is a person physically sitting in the room with the patient. The data on the performance of the in-room observers is not very strong.

We can take 16 of those observers and monitor them in a virtual care center. We have over 120 studies as to why that improves results, such as reducing falls or harm. That is an ROI around using your team more efficiently during a labor crisis and getting better outcomes. Once you have adopted that, you have also put in the fundamentals of your virtual care infrastructure. That allows you to move into other areas such as virtual nursing, which is seeing a lot of interest.

What is a typical profile of an observer and what is their job like?

In a virtual care center, we have the virtual observers, and increasingly, virtual nurses. The virtual observers usually have a clinical background, where they were providing a significant amount of documentation around the types of patients being observed and what they are seeing in the room. If you look at sitting, there was virtually no documentation. The great catches that we get daily are around preventing falls, because they have clinical insight and can often determine that a step was missed. We have unfortunately found situations where visitors or family members are giving substances to a patient that they shouldn’t be getting, or that they are concealing a weapon. They are doing a lot of things by observing those patients. We are 15% nurses and growing. We work to ensure that those virtual sitters, and increasingly virtual nurses, are integrated well into the rest of the care team.

How are hospitals using the system to improve employee safety?

We unfortunately have had a significant increase across the nation in behavioral health issues. Patients often first present in the ED, where you don’t have the history. We are seeing all sorts of things, whether that’s aggression against a caregiver or elopement, where patients or just take off when they’re not supposed to. By having a virtual observer, we’re able to notify the care team so that they can intervene, call for help, or call for security if necessary.

Are the cameras recording at all times?

That’s a really important point. None of the video is recorded. Otherwise, you would have to have patient consent. The video is being observed in real time and trained observers are doing the job to make sure that they are appropriately monitoring the patients.

Are observers screened or trained to manage the psychology of seeing patients in their most intimate and sometimes unfortunate moments?

That brings to mind a couple of things. We guide hospitals as they are hiring observers to look for people who have clinical experience. It’s a great role where you can have a outsized clinical impact, especially if you’re at a point in your career where you don’t want to be on the floor as much.

Gay Landstrom, the chief nurse of Trinity Health –which credits tele-sitting with saving $22 million per year – told a story at our company meeting about a patient who was nearing end of life. This was during COVID, when there was no additional nurse to be in there to be with that patient. The observer worked it out with their supervisor so they could be one-on-one with that patient. They talked to them at this incredibly intimate moment and then ended up singing to them as they unfortunately and sadly passed. That story really connected what we are doing to the mission.

I’ve heard story after story. I was recently at the VA in North Dallas and there was a virtual sitter who got very attached to the patients she was observing, because you have clear two-way audio. It got to the point that she was bringing treats and brownies. There’s a pretty deep connection because these virtual sitting sessions can go on for days. You need to make sure that you have a high quality connection.

Do observers and patients have a lot of verbal interaction, or is it mostly observers asking patients how they are doing or giving instructions?

Oftentimes there are also redirects. One of the reasons that patients fall is that they need to go to the bathroom and don’t want to call someone to help them. If the observer sees someone with high fall risk who is about to get out of bed, they can redirect them. They can summon the care team, let the nurse know, and let the patient know that help is on the way. Other times the patient might need help with something that is non-clinical, and they can take that need off the care team, which cuts down on the number of times the patient has to engage their clinical team.

As you move into virtual nursing, which is focused on either continuous observation — for example, things like avoiding patient demise and keeping patients out of the ICU — or episodic admissions and discharges. If you’re doing a discharge, the unit is right next to the bed and you’re doing a lot of that discharge documentation and training. That’s a deep engagement between the virtual clinical team member and the patient.

Do observers have access to any of the hospital’s clinical systems for observation or data entry?

Our solution is a purpose-built, high quality, highly reliable, high level of quality of service, audio, video, either mobile or mounted device, plus a very scalable backend technology. For example, we monitor 80 hospitals for Trinity out of two centers. When we talk about integrating with other devices, we integrate with the EMR. You can get into your EMR and you can launch the setting, so you can see both documentation and have the audio-video connection. We integrate out to the clinical communication and collaboration space so that you can appropriately route information to the right caregiver. The cameras are high enough fidelity that you can actually read the monitors in the room, and if there are other key alerts, we can bring those into the system as well.

Once the technology is in place and services have started, who is involved on the hospital side?

You want to make sure that the change management is done with the care team that is actually on the units. We have some best practices to make sure that there is great connectivity and that we facilitate building trust between the virtual care center and those who are caring for the patients. Those in the virtual care center are obviously there ongoing.

We as a company provide 24×7 support for the solution so that we can make sure that you have the quality of service when you are delivering care or observing these patients with a critical need. We think a lot, from the technology side, about Day 2. After you go live, how do you make sure that this is well supported and that we are monitoring the health of the devices and the technology?

Does virtual nursing offer a way for nurses to continue their clinical careers without the punishing physical demands?

I was with a customer last week and we were talking about this. They call them their wisdom workers. In nursing, there’s something called the complexity experience gap. The complexity or acuity of patients has gone up, and as nurses have left the workforce, they are disproportionately the most experienced nurses. You are backfilling them with newer nurses who may have had less clinical training during the pandemic. Using your more experienced nurses in a virtual care center is of extremely high interest. It creates a second set of eyes as a way to better support your new nurses, travel nurses, and foreign nurses.

We’ve even had situations where nurses have suffered a physical disability, but they still want to contribute. Getting them engaged in a virtual care center, where they can be working with patients, supporting patients, and working with care teams, is a phenomenal way to make sure that their wisdom isn’t lost to our healthcare system

Are you seeing creative uses of your system that you didn’t anticipate?

We are seeing a tremendous amount of experimentation with virtual nursing, whereas virtual sitting is a well established use of virtual care in hospitals. People are running new pilots around virtual nursing to test wound care, respiratory therapy, and monitoring patients to keep them out of the ICU. They have put our devices in the hallways to have an extra set of eyes where there’s elopement risk. We do see a fair amount of creativity once you have high fidelity audio and video system with mobile units and units that are wired fully into the room.

What is the company’s strategy going forward?

We are finding a tremendous amount of interest in virtual care, so we are continuing to invest significantly there. As we do that, we are focused on a few things. First, that we continue to make sure that our technology integrates really well with the rest of the technology environment. We’ve unfortunately seen care teams underserved with systems are standalone or not well integrated, and we’ve bulked up in that area.

Second, and this is a bit of an overused term, is artificial intelligence. What that means in our market is computer vision and noticing more about what’s happening in the room. We don’t want to take a care team member out of the chain. We want to augment care team members. But with computer vision, we are seeing success and noticing more about what’s happening in the environment. We know if the patient is in the room or if they are about to leave the room. As we continue to invest in that technology, you can imagine that there are myriad things that we will be understanding, such as an IV bag that is about to be empty or that a tube has been pulled.

We will continue to augment the data layer. As you look in care environments, they are manually run. There’s a lack of data to understand how are we performing, what’s working, and how can we do better. Being able to provide real-time data and visibility into the performance of care units has been highly valued by our customers and we will continue to do more there.

We started with sitting, and now there’s a tremendous focus on nursing, We’ve also seen pharmacists and physicians using the technology. I’ll give you an example. We are working with a micro hospital that wants virtual nursing. They also want a centralized way to bring the specialists into the care team. It allows you to get the right talent to the right place at the right time, improve financials, and get better outcomes.

This is the most energized I’ve ever been in a role. That is because of the opportunity to help hospitals with the staffing crisis, the financial challenges they face, in such a meaningful way. The VA in North Dallas freed up 51 FTEs, so they are able to serve more of our nation’s vets. Being on the forefront of virtual care and acute care has been incredibly exciting. We are making a significant investment into the clinical research that goes along with this so that we can partner with our customers as we work together to pioneer how virtual care can play a role in helping health systems operate effectively going forward.

HIStalk Interviews Eric Ly, CEO, KarmaCheck

Eric Ly,  PhD, MS is co-founder and CEO of KarmaCheck of San Francisco, CA. He was a co-founder and the founding CTO of LinkedIn.

Tell me about yourself and the company.

I am a technology entrepreneur. I have worked on B2B software for multiple decades. I was one of the co-founders of LinkedIn. What got me interested in background screenings and verifications was that I was interested in something like a blue checkmark that would verify the information contained on LinkedIn profiles. That led me to the background screening industry, where I saw an opportunity to bring efficiencies and transform the way that background screenings and verifications get done.

You’ve mentioned the possibility of allowing people to store verified credentials in a digital wallet. How do you see the company being involved in that?

That’s a vision that we are working towards. If we are able to provide a wallet of credentials to professionals in the future, those credentials that are verified can essentially be persistent. When they go for new opportunities, that information is mostly there already. That speeds up the process of applying and getting job opportunities, both for candidates themselves as well as for employers. They don’t have to go and check many of those facts again.

Certainly there is information that needs to be updated with recent changes, but that opens up a world where the onboarding process can be more efficient for both sides. As we are moving towards the world where there is a more flexible and contingent workforce, the need and the value that provides is going to be become even greater.

It would make sense that LinkedIn user identities would require verification, especially now that we are seeing LinkedIn scammers pretending to be both employees and employers. Do you think that will happen?

That’s an interesting scenario. LinkedIn has been successful in amassing the professional information and histories of professionals all across the world. There can be a layer on top of that that provides verification of the  information that has been entered by those individuals. We are creating value by bringing truth so that the information that is associated with those profiles — whether they are on LinkedIn or elsewhere, let’s say on a job site — can be trusted so that when employers are looking at candidates, they will know that the information about the backgrounds of those candidates is confirmed.

The Department of Justice recently announced that thousands of people purchased phony nursing educational credentials, and some number of those folks presumably ended up obtaining licenses and caring for patients. We’ve also seen examples of nurses who harmed patients intentionally in hospitals that declined to prosecute or publicize them, allowing them to take jobs with new hospitals and continue their crimes. What kind of analysis or AI review could detect these issues?

Those are some interesting cases. In healthcare, here’s an example of where verifying someone’s credentials and their background is especially important, because we are talking about life and death for patients that healthcare providers affect. It’s especially important that the backgrounds of clinicians are verified. Beyond verifying current credentials, which is a complicated and complex stack already, skill competency tests could be run to ensure that the individuals have the expertise and knowledge that they need to do their job.

Something we have seen recently becoming more of a problem is verifying the identity of a particular candidate. If it’s possible to hire someone in the place of a clinician without ever meeting them in person, there is also an increased chance of the identity of that individual being falsified as well. ID verification technologies that can be used not only to confirm someone’s background, but to confirm that that background actually belongs to the individual that is being placed on an assignment.

The US has low unemployment and a significant percentage of citizens who have been convicted of a felony, suggesting that employers are either unaware or unconcerned about their criminal history. How would hiring decisions change if finding criminal records at local, state, and federal levels became easy and inexpensive?

Numerous surveys have found that at any given time, 25% to 40% of people have falsified their backgrounds. That’s pretty consistent across the board, whether it’s on an online platform or from a resume. Knowing where the falsification happened becomes an important point.

In this historically low unemployment situation, there might be the temptation to bypass some of these checks in the name of bringing more people on board, placing them, and so forth. That puts the employer or the staffing company at risk, because if something goes wrong, that carries a pretty heavy liability. In a field like healthcare, we are talking about life and death situations, so it’s not a light topic.

Because of the complexities that are involved in doing credentialing and meet compliance, this is an area and opportunity where technology can help. If those processes, as complex as they are, can be made more efficient and perhaps more cost effective, the reason to skip, overlook, or miss some of the infractions or violations that happen don’t have to happen as much. Companies and employers can still protect themselves while going through these compliance processes just as much as they should in more normal times.

How much inefficiency in provider credentialing could be eliminated by technology?

We are entering into a new world in healthcare and the staffing of healthcare. The general trend is that the scale and the velocity at which placements are occurring is speeding up. Hospitals and staffing companies have had to manage their staff at a faster pace than they ever had to before. Based on this backdrop of complicated credentialing needs, it becomes an unmanageable situation. The challenge is even greater when you have costs going up.

Technology generally helps to deliver scale and to deliver efficiency, so there are certainly opportunities for technology to be applied in these kinds of situations to help increase efficiency. That translates into is operating efficiencies and lower costs for the facilities.

That scalability might provide the opportunity to assemble a deep candidate profile that includes social media posts, credit reports, driving, records, online photos or reviews, and any number of information items that aren’t directly related to being hired. Will we see a tension between what is possible versus what is fair or reasonable?

There has been a lot of recent talk about AI and the application of AI. It enables any user to sift through more and more information to catch information that might help enlighten the background of a clinician, for example. The ability to look at more information, to learn more about the candidate, ensures that a qualified candidate gets placed, such that problems and liabilities are reduced. There is ever more information out there, and technology is a tool to help look through that ever-increasing amount of information.

What healthcare opportunities will the company explore in the next few years?

For an industry like healthcare that has maybe traditionally been slower to adopt technology, there are some great opportunities to take a look at making operations more efficient and cost effective. The main reason for doing any of this is to deliver better patient care, which everybody wants. In doing that and evaluating technologies, my recommendation is to not necessarily take a look at point solutions, but instead to have a holistic sense of the technologies that will deliver value to an organization, how it fits into processes and workflows, and how existing workflows can be changed a little to create significant improvements in operational efficiency. To take a higher-level strategic look at how technology can be deployed within an organization would be helpful for the healthcare industry.

Innovation is definitely happening within technology to specifically serve the healthcare sector. From a standpoint of cost savings and delivering better patient care, some good answers are starting to emerge.

HIStalk Interviews Angie Franks, CEO, About

Angie Franks is CEO of About of St. Paul, MN.

Tell me about yourself and the company.

I’ve been in healthcare technology for 33 years, so this is definitely my passion. I have spent the last six years with About Healthcare, formerly Central Logic. We match the demand for acute and post-acute services with the optimal setting of care to get patients to the best place for the care that they need.

How do EHRs fall short in care coordination as health systems expand their range of services and geographic coverage?

EMRs do many things well. But when you move patients across settings of care, or need to optimize the resources inside of your health system by pulling together different silos and different systems, there’s a lot of data that’s not in the EMR that becomes important and instrumental for making decisions around hospital operations and then executing on that. The EMR is more suited for capturing specific data about a patient, ordering tests, getting those results back, and then billing the insurance company.

When you are making decisions about where a patient should go for the care that they need, how to get them there, choosing the best physician, and then executing on those logistics, you are pulling from data that is not in the EMR. You need information that is in a lot of systems. What we see is that hospitals have lots of silos. They don’t work well as a system of care when it comes to the operations and the logistics. That’s where we focus, which involves connecting to, talking with, and interoperating with the EMR as well as a bunch of other systems.

The data inside of an EMR is impressive, especially when you think about the clinical data and all the work that organizations like Epic can do with disease and tracking all of this clinical information. When you look at it from an operational lens and a growth or a strategy lens, none of these EMRs capture and track this data in a way that is useful to strategy and operations. As a result, many health system leaders don’t look at information even though it could change how they operate as a business. That’s a real benefit of looking at your operations differently than how you look at clinical pathways and the billing systems. You get data out of these tools that inform decisions that you make as a health system executive team that have a impact on your bottom line. Data is an important area of focus for us over the long term.

Bed management and bed visibility became important during the pandemic. Will that have a permanent impact on health system operations?

One of the things that the pandemic showed is how silos create bottlenecks in the organization that prevent patients from getting access to the care that they need. Getting somebody out of the acute bed and getting them to a post-acute setting by doing that electronically and in interoperability setting instead of creating a bottleneck for patients who were trying to get in the front door and into a bed of a particular health system. Those bottlenecks exist all over our care delivery system and impact access to care.

We have gained a lot more visibility into the bottlenecks. Health system EDs were overrun during the pandemic and they couldn’t service all those patients, but maybe a hospital down the street had capacity, but nobody knew about it. Even when we put the USS Comfort and 1,100 beds in the harbor inside of New York City, we placed only 107 patients there. It wasn’t because there wasn’t demand for all of the beds. It was because there wasn’t an ability to access them, to communicate and efficiently see what was available, and then match the patient and move them. That speaks to the need for more interoperability in our healthcare IT ecosystem. We have a long way to go.

How well are health systems operating transfer centers and how do they fit into their business strategy?

It is an important front door for health systems. Acute settings have three entry points — the emergency department, scheduled procedures such as the operating room, and patient transfers. Patient transfers are least known and understood. 

A lot of health system leaders and executives may not have spent much time thinking about access points and access channels. They have business development teams and people who are responsible. It’s almost like a sales channel, but putting in place a conscious strategy and an infrastructure to capture more of the demand that is inside of the geographic service area that a health system serves and that net new patient demand for that hospital system. Those are lucrative patients, and every health system wants to capture more market share and then keep those patients inside of their network.

It is competitive for those patients. When you have an optimally functioning transfer center, you capture more of that demand. You impact your top line with revenue and your bottom line with improved margins. It is predictable. You can start achieving an ROI quickly if you invest the time. It’s not a technology implementation. Technology is important for enabling consistency and execution of a business process, but it is changing the way a health system operates and changing the way they utilize all of their resources for matching that patient demand with the right setting of care. If you just defer your front door to the ED, you pretty much get whoever walks in the door at whatever facility they show up at.

Do patients and physicians agree with a health system’s definition and approach to what they call “patient leakage?”

There will always be an amount of leakage. There are appropriate times where the patient is in a setting of care and they need to be somewhere else, which results in a transfer. They need a higher level of service or acuity. That could show up on a report as leakage. You had the patient, then you lost them. They leaked and they went to another system. Some amount of leakage will always happen and that is appropriate.

Hospital operators need to focus on when there is leakage that didn’t need to be. A patient comes into your emergency department, you offer those services, you have capacity, but it was hard to get that patient moved out of the ED into the right bed. It was easier for that ED doc to call their buddy, who is a cardiologist down the road, and move that patient into a different health system. That’s a costly leakage problem, and it happens every day.

It is costly to let patients just walk out the door instead of helping coordinate follow-on services or referrals to a specialist as they take that next step in their care journey. When you leave it up to the patient to just figure it out, it’s not a great experience for the patient, but it also results in a lot of leakage for the health system. It is an important metric to look at, calculate, and focus on, because it has implications to revenue and operationally and it can be a bad experience for the patients as well.

How are health systems changing their business model to address new competitors, telehealth, and new generations of consumers who would rather use urgent care?

What I see health systems doing over the last couple of years, and the pandemic was instrumental in this, is talking about operating as one system of care. How they use all of their capabilities to care for the patients in the community, and do that more efficiently and in a more streamlined manner. The conversations that are happening are really good.

I could give you many examples of what health systems are focusing on. We help them think about the acute and the post-acute patients. That is a  small population of their overall patients and the communities that they serve, but hospitals and health systems have an enormous amount of competition for those healthy patients and the outpatient visits, whether it’s CVS, One Medical, or even Dollar General in some smaller communities. The margin erosion and the patient attrition for services that were maybe more easily captured in the past is an issue, and that revenue has to be replaced some other way.

Health systems are figuring out their population health strategies, figuring out their access channels how to deliver service not only to the patients, but to their referring community. Managing those referring networks as an important growth channel is a different way of thinking. I’m seeing more conversations about that today than I have in the past.

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

I see our company continuing to focus on solving this problem and helping health systems operate as one system of care, doing that by connecting their silos and disconnected systems into a streamlined process so that they can operate more effectively. It is a passion of mine. For everybody who works here at our company, this is what we jump out of bed to do every day. As I’ve gotten older, I see my parents needing to access healthcare services in different ways, and it sure gives you a lens on the importance and the mission orientation of the work that we do. We are going to continue focusing on this. It’s a big problem, and we are in the early innings of the game.

HIStalk Interviews Laura McCrary, CEO, KONZA

Laura McCrary, EdD is president and CEO of the Kansas Health Information Network and KONZA National Network.

Tell me about yourself and the company.

The KONZA National Network was started in 2010 as part of the HITECH and the American Recovery and Reinvestment Act funding that was made available to each of the states. KONZA is a 501(c)(3) not-for-profit organization that is incorporated in Kansas under the name of the Kansas Health Information Network — KONZA is actually a DBA. The organization provides services not only in Kansas, but across the nation. The KONZA National Network provides health information exchange services as well as analytics services.

Kansas managed the process of establishing a health information exchange a little bit different from other states. That is relevant to the way that the KONZA National Network has developed. For example, Kansas didn’t stand up its own state-sponsored health information exchange like most other states did. Instead, Kansas established a process to certify the exchanges that did business in the state. Kansas didn’t give an allocation of state or federal funds to the health information exchanges. Instead, those funds went to the provider community to purchase interfaces and connect to the health information exchange. That was a key component of the development of KONZA and the health information exchange framework in Kansas. 

The state then established specific criteria that all of the exchanges that did business in Kansas had to meet. You had to run a viable business that had providers and payers paying for the services that you provided. It was a subscription model, and everybody paid.

Also, you had to participate in supporting public health. You had to be involved in building the public health infrastructure. It was a partnership. The HIEs all agreed to send data for electronic lab reporting, syndromic surveillance, and immunizations. Kansas was well prepared for the pandemic because we had been working on that for 10 years.

The other thing that was interesting is that Kansas said that all data that was brought into the exchange also needed to be provided to the patients through a personal health record. Early on, all of the health information exchange data was provided to patients at no cost. That allowed us to be one of the early participants in the Harvard Open Notes model, where all of the data that we had available in the exchange was provided to patients.

It was a very different and unique model of certifying exchanges. One piece that was important was that all the exchanges that did business in Kansas had to connect to each other. While we may have been competitive, we also had to cooperate. That was a basis for how we were able to spread this exchange across the country. We had a commitment to all of the things that I just mentioned because of the way the initial Kansas HIE infrastructure was set up.

What are the implications of creating a national network?

Most of your readers will be familiar with the QHIN model under TEFCA that is beginning to come into fruition. The QHIN model is the Qualified Health Information Network model, sponsored by ONC and The Sequoia Project. KONZA has applied to be a QHIN and is working through that process now with ONC and the RCE. That will be an important development in interoperability across our nation, because we will see a number of QHINs that will have responsibilities to connect to each other and share data to establish that nationwide context.

The fact that KONZA already does business with exchanges in 11 states gives us an opportunity to be at the forefront of that. We run exchanges in Connecticut, New Jersey, Georgia, South Carolina, Mississippi, Louisiana, the Dallas-Fort Worth area, and obviously Kansas and Missouri. We also support an exchange in Northern California. That gives us a pretty broad national scope in terms of leveraging the QHIN model. We are excited about the possibilities of what the future looks like for health information exchange as we move forward into the later part of 2023 and 2024 and we have the QHIN model operational.

What challenges remain to giving patients the full benefit of interoperability?

There will continue to be issues with interoperability until we resolve the issues around standards in data sharing, the actual semantic interoperability of using a variety of different code sets. For example, it is still difficult to make sure that labs are being mapped properly to the LOINC codes and that SNOMED codes are being used properly. We often find that there’s still a lot of challenges in being able to do all of the proper coding and mapping.

We work hard at KONZA on data quality. We are part of the NCQA Data Aggregator Validation, or DAV project, where we take all of our practices and hospitals through DAV accreditation with NCQA to ensure that they have the highest quality of data that can be delivered. We check those things, like has the hospital mapped their labs properly to the LOINC codes? And are we seeing the proper procedure codes coming through? Are we seeing duplicates in data?

All of these things are still challenges for us. The data is still messy, so it’s important for us to focus on data quality. We have a couple of key vendors that are instrumental in helping us do that. But it is a core focus for us on data quality. 

If you can’t get the data quality in the place that you need it to be, you are not going to be able to provide a complete and correct longitudinal record at the point of care for a patient. If a patient shows up in an emergency room and the doctor doesn’t know who he or she is, the doctor is dependent upon getting a longitudinal medical record from the health information exchanged to make sure that the physician knows all of the information about the patient before they begin providing care.

We are getting closer. Let me say that I feel enthusiastic about the future of health information exchange, particularly with the QHIN model that is coming into place. I think that we will see continued improvements in the data quality and the data completeness. But it’s still a work in progress.

The early days of RHIOs involved creating centrally administered platforms that left providers to figure out how to connect. How has that transitioned into a more services-oriented approach?

Health information exchanges flew under the radar from about 2010, when they were funded, up until about 2019 and early 2020 when the pandemic hit. Then it became clear to the entire nation that the health information exchanges had been developing products and services using the data that they were receiving through the health information exchange and aggregating that data and being able to turn it into meaningful information that could help to inform public health and others regarding the progress of the pandemic as well as the vaccination status of the population. Health information exchange quietly built that capacity over the years. 

KONZA has 4,500 organizations that contribute data into the KONZA enterprise data warehouse. When we need to aggregate data across the nation and be able to track disease surveillance, the health information exchanges were well prepared to serve as that public health data utility to step into that space and provide information. For example, they provided COVID registries to the state of Kansas before they had the ability to get a registry set up. We set one up quickly for the state of Kansas in about 30 days, because we were already tracking the data and had it coming in for health information exchange purposes.

KONZA also has the ability to aggregate data across practices and across states to be able to look at quality measures. One of the things that KONZA does is calculate and compute quality measures, not only for physicians and hospitals, but across populations, whether it’s an independent physician association, an accountable care organization, or a Medicaid health plan that needs to be able to look at how they’re doing across their Medicaid population.

The health information exchanges have built that capacity and have been certified as having the highest quality data that’s available. It can be counted upon by payers, providers, and others as it relates to quality metrics. We see imminently on the  horizon that quality measures will not just be calculated out of an individual EHR system. They will be calculated across all of the locations where the patient received care. That way, you have a holistic view of how a hospital or a physician practice is actually doing in providing quality care to a patient across the patient’s entire care team, as opposed to just looking at what happened at their facility.

How will you participate in clinical research?

We regularly get requests for de-identified data to be able to be used for clinical research. When KONZA, executes agreements with our participants, we have a secondary data use agreements that allows the data to be able to be used for purposes that advance medicine. Now, it can’t be used for purposes that would be used for marketing or for financial gain. But for clinical research that actually improves the practice of medicine, we have a team of doctors that meets to review each request that comes in to us. 

In the past years, we have focused on delivering data individually as each request came in. But we are building a product, which is being tested with a children’s hospital, that will provide de-identified data to the researchers at a hospital so that they can look into being able to use the data themselves, configure the data, and manage the actual research without us having to be involved. We are excited about our pilot project. I’m hesitant to name the children’s hospital, but it’s around how chemotherapy has affected children’s cardiovascular systems over time. Because we gather longitudinal records over time, we can often look across an individual’s life. We have, in many cases, 15 or 20 years worth of data that we can look at. Researchers are going to be able to take the data, model it themselves, and start using it for some amazing research that we haven’t been able to do before.

What strategies or tactics do you think will be important for the organization over the next three or four years?

Our work with the payer community is becoming more important. Many of your readers are all too familiar with payers having to send individuals out to pull records or asking practices or hospitals to send medical records so they can do their quality reporting around HEDIS and risk adjustment. That business is starting to become less and less because these records are all digitized. There is no reason to go out and make a copy of a medical record on the copy machine, ask someone to fax a medical record in, or have individuals spend time and precious resources doing things that are no longer going to be necessary as all of these records have become digitized. 

More and more, we find that our business is moving towards providing data to the payers so that they can meet their quality goals around HEDIS and risk adjustment, which is one of the reasons that we are so focused on having the highest quality of data. We want to make sure that the data that we provide to providers is correct and complete, and to our payer customers is correct and complete. That is becoming an increased focus for us, to spend time working with payers, understanding the data that they need, the timeframes that they need it in, the format that they need it in, and to be able to deliver that payers. Our goal ultimately is that we can provide the products and services to the provider community in return for the data that we receive from them. We can provide that to the payers and eventually be able to reduce the overall cost to providers in our community to be involved in a health information exchange to a minimal amount. The providers are contributing their data, and we see that as being extremely valuable and we want to continue to build upon that perspective.

HIStalk Interviews Michael O’Neil, CEO, Get Well

Michael O’Neil, JD, MBA is founder and CEO of Get Well of Bethesda, MD.

Tell me about yourself and the company.

I started GetWellNetwork 22 years ago following a personal cancer experience while I was in school getting a JD/MBA degree at Georgetown. I started the company with a simple mission to make it better for the next person. I had spent way too much time going through surgeries, chemotherapy, and coming in and out of hospital beds and clinics. I thought that these amazing people who were delivering my clinical care needed some help in delivering the kind of patient and family experience that could enhance not only my attitude, but also my outcome. I started the company to help hospitals leverage technology to engage patients and families more effectively in their care, and in turn, help clinicians and improve outcomes.

The original concept was somewhat limited, focusing on in-room patient entertainment and education. How did you broaden the company’s reach to include everything from pre-acute to post-care and even remote monitoring?

I look at this as two acts to a play with an intermission in the middle. Act I was long, 15 years of trying to improve a two-day, four-day or 12-day hospital stay. We met a patient at admission and we said goodbye to them at discharge. We we were in many ways proud of transforming the hospital experience at the point of care for the patient, family, and nurse.

A bit before COVID – and COVID certainly accelerated this — we began to invest, both in organic R&D and in some acquisitions. We knew that the impact that we could have on both our customers and people and their health journey, which had become nine or 10 million people in a year. Their journey was not just that two, four or 12 days – it was a lifelong journey, a 30-day journey, a surgery, or what have you.

We had this intermission period where we doubled down on investing in R&D. We bought a couple of companies and that helped us accelerate to build Act II for the last 18 to 24 months. That involves enterprise engagement, navigation, and retention. We have a chance to help organizations wrap their digital arms around either members or patients at scale, but do it with intimacy that is required in healthcare. We are excited about today and what lies ahead.

Patient engagement seemed to align well with value-based care, which has had perhaps less impact than everybody expected on health systems, and now the imperative involves patient recruitment and retention. What are the primary motivators of health systems to improve patient engagement?

It’s actually straightforward , and there is a triple purpose on this. The industry is littered with tiny niche consumer engagement solutions. It doesn’t have many true platforms at scale. When we talk to health systems, payers, and managed care organizations, we are talking about what we would call Get Well Anywhere. The value proposition is threefold. They need to drive their business because these organizations have been through the grinder the last three years. If you can’t claim, stand behind, and share risk in the ability of your consumer engagement solutions to drive business, we don’t think you can do a lot of business in today’s health system world.

Number One is these AI-driven outreach tools that we have now, the ability to navigate people back into their primary care, to help them navigate into a mammogram or a care gap or something like that. It is driving direct revenue when it comes to fee-for-service organizations. But a lot of times, those same organizations also have value-based pockets. They have taken on full inpatient risk in a certain market.

The powerful thing is that the same platform, the same workflows, the same what we call Get Well Navigators — who have been trained to help people in vulnerable moments leverage technology and then pick them up when they can — these same things work to make sure that we are guiding patients to the appropriate and oftentimes lower-cost point of care, or doing self-care. The number one value prop and number one driver of people investing in this now is business, whether you are in fee-for-service or you’re in risk.

The second reason, and I don’t say this lightly, is that loyalty and patient love are more important than ever. We have an internal Slack channel at Get Well called Call Patient Love, and all day long our navigators are streaming comments from our thousands of patients every day who have interacted with one of our navigators, who interacted with a nurse, or who interacted with a physician who has touched them in a certain way. It matters. This kind of patient loyalty and patient love is the second piece. It’s a little softer in its ROI approach but it’s not unimportant.

The third thing is that workforce challenges are everywhere. This isn’t a temporary thing. This has been going on for a long time. How can you leverage the power of the patient and their family caregivers to help drive efficiency of your incredibly precious workforce?

That is our three-part value prop. I will tell you pretty bluntly that we are driving at Number One. We are going at a lot of risk for this. If you have 800,000 dormant patients, we know we can convert them back to activated. They need care, and that care will also drive revenue. Let’s share in the risk of that. Let’s make sure they get the care they need. That allows us to then make other investments alongside of our partners in things that they want to do.

Insurers are making significant inroads into becoming providers, while providers are sometimes taking on the role of payvider. How does this affect your business?

On the payvider side, a lot of our large complex health systems have partnered fairly meaningfully and financially with local, regional or national payers. In those partnerships where they are taking on risk, they of course are terrific partners for us. We are doing a lot of innovative stuff. You are managing 12,000 mothers on Medicaid and you are responsible for their full cost, so we are running a Mothers on Medicaid navigation program that was a feature at the White House last December. We think there’s a way to really help these incredibly important people in our communities have the very best care and have a healthy pregnancy. In that case, you have an aligned payer and provider delivering great care and the solutions match that way.

In a world where you have payers who are starting to invest in direct care as you alluded to, they also need tools. You know from using your employer’s portals and digital tools that nobody uses them. The trust relationship and the navigation is light. We are partnering more and more these days with some folks on the managed care side, because we now have 20 years of data on when people are in this vulnerable spot, what are the interactions? How frequently should we be interacting with them? How can we recruit and hire local navigators who are in market who understand the communities, understand the local vernacular? How do you build trust on behalf of a health system or a payer? Those managed care companies have struggled for a long time with that, and we think we can help. We have shown some data to be able to help that as well.

How did your business change with the pandemic?

In all transparency — as you have built your entire organization around directness and transparency, which those of us who get to read it love — it was challenging. The most challenging thing for us was we lost touch with the clients that we work with day in, day out, month in, month out, quarter in, quarter out. We work closely with chief nurses, chief experience officers, CIOs, and nurse directors on an ortho unit that is doing a certain pathway for post-knee replacement patients and how they are going to navigate through their discharge. This is work that we do all the time. We have a lot of clinicians in the company. That changed. We had to figure out how to support them without being able to be with them, and that’s a difficult challenge.

On the other side, it tested the dynamism of our solutions and platforms. We gave a solution called GetWell Loop. It’s a library of 300 digital care plans. I was at a fellowship in Colorado when COVID broke out. When I got home, w4e met as a team. Within three weeks, we had built five COVID loops. We deployed them over the next six weeks in 200 command centers across the US at no cost to our provider partners. We ended up touching and helping over a million patients stay safe at home, and helped ER beds free up so they would stay available for the sickest people. It challenged folks to support our clinicians in a way that we are typically supporting them.

Thirdly, ironically enough, it gave us a little bit of room to double down on R&D and transformation. We contracted with this amazing firm in the UK to design a completely new consumer-grade UX that we just launched late last year. We built a BYOD version of our inpatient solution that we are deploying now across lots of hospitals without capital investment. We acquired a business that does AI outreach and navigation, which has been amazing.

We doubled down on our government investment. We spent quite a bit of time and resources on getting FedRAMP approval for our cloud-based solutions in the government. We do a lot of work across 70 or so VA medical centers and now we are able to bring our loops and our navigation stuff into those communities for our vets. That is a source of pride and drive for the company as well.

The interest in AI tools such as ChatGPT has been unprecedented. How will AI technology be applied to patient engagement?

We have a front row seat. We were admittedly a little bit slow on the organic R&D in AI. We just didn’t have the bandwidth to get ahead of it. We acquired a company whose foundation is in AI and chat. One of the elegant things that we liked about this was that it has an ability to interject AI and live chat simultaneously. You are building real-time profiles of patients and how they are interacting with the content and our people.

As an example, we are working on a large project in California, where we had close to a million dormant patients. We were given a file from their EHR company. They had not been in to see a primary care physician in over 18 months because of the pandemic. We used our AI to reach out to them. To give you a sense of this, you’re talking about 2.6 million AI-driven, text-based bidirectional interactions coupled with 40,000 supplemental live interactions from our navigators.

The good news is that we are seeing the AI work and people respond to it. But we also would tell you that the realization in healthcare is to think that this stuff will be done exclusively without people. We believe that human interactions in your biggest state of vulnerability will require people to make sure they are monitoring, looking, and attaching in highly personal, delicate, and intimate ways in times of need. We have combined AI with a high-touch approach as well. We are seeing some great results that we are excited about.

How do the areas of patient engagement and patient-reported outcome measures overlap?

This is where things get fairly complicated among the EHR and its capabilities; a large CRM platform and its capabilities; and tools, solutions and platforms like ours.

We are seeing that a large health system will often default to the large enterprise EHR or CRM. We don’t fight against those platforms at Get Well. We spend as much time on programs as we do on platforms, meaning that these platforms are only as good as highly discreet programs that help an individual or a micro population of people navigate through their incredibly individual journey.

It sounds cliché, but you had better be able to integrate into core EHRs in a deep, API-driven, and oftentimes more so these days, FHIR kind of fashion and have SMART apps and things like that. You had better be able to pick up on a broader campaign from a CRM outreach. But in our world, you had better be able to put on top of those two platforms some individualized and personalized programs. Because if not, we are going to see engagement rates just like we saw the portal for 20 years. That’s not good enough. People need help.

How does the company’s history of acquisitions and funding activities change with the current business environment?

It’s been crazy. At HLTH, the buzz wasn’t just patient engagement and health equity, but also the cash burn of companies that have spent a lot of money on marketing knowing that their solutions are fairly niche and are not scaled. I don’t envy being in that kind of startup, early stage, cash-burning mode.

Get Well was not an overnight success. This stuff takes a long time to get  right and to get to scale. But we are fortunate. We have a lot of customers. We have positive cash flow. We are able to invest our own money in things that we actually want to pursue. We will be working this year on an important youth mental health project in Mississippi. We can take our own money, which we actually make, and invest in things that we think are projects of purpose.

The funding environment has changed dramatically, literally over 90 days, because there was a lag. The private markets stayed relatively hot until August and September and then they started to cool. That has been a significant change.

As a company that has been around for a while that has some scale, these are opportunities for us. We are thinking about our strategy. We are thinking about how we might accelerate our own R&D efforts with other companies that might be willing and excited about partnering with us to do something bigger together versus smaller on our respective owns. We spend a bunch of time talking to the ecosystem and staying connected. Honestly, I’m rooting for all of them. Everyone that is doing good work in patient engagement means that somebody on the patient end is impacted.

I hope they all succeed, but they won’t. It’s tougher because there are fewer buyers out there, as health systems consolidate and become fewer and fewer prospects. It is difficult not only that there are so many vendors, but so few customers. It’s a double whammy for the small niche players. Fewer customers, and those fewer customers have a hard time adopting, integrating, and implementing tiny projects that don’t have the security measures and integration depth that these multi-billion dollar, multi-state organizations expect. You have pressure on that side to work with larger, more stable, more comprehensive solutions. Secondly, there’s a big movement at the CIO level to consolidate suppliers.They can’t manage 14 different consumer-facing tools or whatever.

This is not to say that I don’t believe in innovation. Our industry always needs people who have identified a pain point and are going after it in a creative, innovative, new way. However, these entrepreneurs need to spend as much time honing their business models as they are honing their elegant solutions, because too often these amazing solutions can’t get scale on the revenue side, and there’s not a lot of forgiveness out in the market right now for that.

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

One is what I will call Get Well Anywhere. That is, finding our way into relationships where we become that third core solution. You have an EHR, you’ve got a CRM, and you have an engagement, navigation, and retention platform with the depth, the credibility, and the security to make sure that they can deal with these two behemoth solutions while also having the rare ability to deliver digital intimacy that those big platforms lack. We want to find our way into more of these Get Well Anywhere partnerships that are large, where we are sharing risk, and where we can drive business, patient love, and workforce efficiency at scale. We are excited about the progress there.

The second thing for us is that we will continue our work and we are doubling down in the government space. We have had such success in impacting US veterans. We are doing more work these days as well in active duty military clinics and facilities. We are excited about the impact that consumer engagement and navigators can do with the folks that we cherish. We have 30 or 40 veterans on our  cohesive, amazing, and focused team. We are doubling down on their success to make sure that we can impact veterans in active duty military moving forward.

The third thing is that we have primarily been dealing with health systems for 20 years. There are school systems, payers, and other organizations that have a vested interest in engaging constituencies in their health. We need to get outside our comfort zone and help populations do food as medicine, navigating to treatments, and doing self-care. These are the kinds of things that give us great purpose and that we are excited about.