HIStalk Interviews Peter Butler, CEO, Hayes Management Consulting

Peter Butler is president and CEO of Hayes Management Consulting of Wellesley, MA.

Tell me about yourself and the company.

I’ve been at Hayes for 25 years. We are a technology-enabled company leveraging our MDaudit software platform to drive billing and audit compliance productivity as well as revenue integrity solutions across healthcare organizations.

Is it hard to retool a consulting firm into a software vendor?

It’s challenging. After a long corporate career in consulting, you develop a name for yourself in that area. We got our start with IT consulting, then over a period of time, moved into revenue cycle consulting and EHR implementations and so forth. Our MDaudit platform took a greater foothold in the industry and we were experiencing quite a lot of trust with it.

We saw this, years ago, as the future direction of the company. We foresaw health IT consulting needs diminishing and becoming commoditized. We wanted to leverage our strength. That’s when the software piece came in.

It was a difficult journey trying to change the mindset of a 25-year-old company and people who have a lot of longevity in it, asking them to think differently, more like a software company. It came with a lot of challenges.

Are you happy that you made that decision early when you see other consulting firms just now starting to react to market changes?

Very happy. When we were going through that transition, the hardest part was that it wasn’t happening fast enough. I look back in the rear-view mirror and say, OK, we did it. We got there. This is good. Where do we go from here? It’s important for us to stay relevant in the industry and in our client organizations.

We’ve turned the corner. We are looking forward to building ourselves as a software company and continuing to make a difference in healthcare.

What are the top issues in billing compliance?

Years ago, the top issue was how a healthcare organization with 2,000 providers could audit all of them annually. Then they acquire two more medical groups of a couple of hundred providers. How do they get through those audits with limited resources? Their organizations weren’t giving them the staff since they were really seen just a cost center.

Now the trend is, I have limited resources, so let me take a step back and look at all of the billing compliance risk areas to my organization. Bubble those to the surface so that I can take my limited resources and go tackle those challenges. Are they really risk areas that I should be concerned about, or are we a billing outlier for good reason because we are multi-specialty and we specialize in this type of service? In the old days, they were looking for fraud and abuse inside their organizations.

Now it’s taking a different turn. Where can I sharpen my attention to the revenue cycle? What am I actually providing for service, but not billing for? Compliance officers stay in the mindset of looking for areas where they can ensure that their organizations are billing appropriately, not over-billing Medicare things and like that. But they’re partnering with revenue integrity leaders inside their organization who are looking at the same data. What are we leaving on the table? We’ve delivered these services. There’s more pressure on reimbursement. We want to make sure we’re getting paid for everything we’ve done.

Is anybody doing a lot of billing compliance work as due diligence before provider acquisitions or mergers?

They are, but they should be doing more. I’ve had conversations with compliance officers who said, I just got a message from the CEO that we’ve signed our letter of intent. We’re moving forward with buying this practice or hospital. They aren’t paying attention to making sure that, as part of the due diligence process, they are billing and coding appropriately. Let’s understand the risks of acquiring this organization. It’s almost been an afterthought from senior leadership that the compliance professionals find themselves in post-transaction.

Is the focus different when a private equity firm is the buyer, such as the trend of acquiring dermatology practices?

We’ve had some of those PE-backed companies call us and say, we’re about to make an offer for this dermatology practice. Before we finalize it, can you do some diligence around their revenue cycle and their billing practices? Make sure that they are billing and coding appropriately and that what they are telling us and what we’re reading in the reports is actually what’s happening.

Those are mini-assessments. They don’t take a lot of time, but they give the buyer an opportunity to understand where the risks and opportunities are. Once they finalize the deal, if they go forward, where can they find revenue opportunity and operational efficiency? There’s definitely a lot of that from the financially-minded buyers.

What trends are you seeing that aren’t getting much attention?

A lot of revenue cycle leaders in years past ran their organizations based on metrics. They would tell their staff, you need to make X number of calls or you need to touch X number of claims. A trend I’m seeing that will pay dividends later is that instead of looking at volume-based metrics or metrics for the sake of metrics inside those revenue cycle follow-up departments or patient access departments, ask that if you touched a claim, what did you do with it? Did you make changes to it that positively affected the organization? Were you able to identify root cause and go back and make changes that actually stuck so that we’re not seeing these problems over and over?

Some of our clients are assigning audit-minded people to look at the goals and responsibilities of those who support the day-to-day operations. Looking at whether their daily tasks drive positive change, the quality outcome in the operation. They are using spreadsheets to document who they’re working with, the types of audit completed, the follow-up, and the result.

It can become an arduous task, but the concept is, are you driving better quality outcomes in your role, or are you just saying you made your 50 calls or worked your 10 work queues? What was the result of that? That’s an important trend and overdue in healthcare.

Hopefully we can instill some best practices in the industry so that we have less need for those auditors. You’ve done your training and you’ve built some great training programs to educate the people who are touching every aspect of the business operation.

Do you have any final thoughts?

Some interesting things are happening that we’ll see more of as quality reimbursement plays a bigger role in healthcare. CMS recently proposed some E&M simplification rules with the concept that it will save money and provider coding time. They’ll save 50 hours a year or something like that, taking away all of the detail-level E&M coding and documentation you have to do. CMS is also looking for ways to save money for the taxpayers and the government, so it has to be viewed through that lens as well.

It will come at some point, probably not in January, but it will come with challenges that the healthcare industry needs to walk through. If you’re billing Medicare, you’ve got Blue Cross Blue Shield as secondary, and you’re doing simplified billing for Medicare, what do you do with that claim? It gets passed down to a secondary payer. There are other issues around RVUs and how you reimburse your doctors that will be impacted by changes like this from CMS. We have a lot of work to do as we think about simplifying the billing process in the industry. It won’t come without challenges.

HIStalk Interviews Kurt Garbe, CEO, IMAT Solutions

Kurt Garbe is CEO of IMAT Solutions of Orem, UT.

Tell me about yourself and the company.

IMAT Solutions solves the core data problems of healthcare companies. We focus on how to improve data quality, data currency, the amount of data, and the type of data that companies can look at.

How do you position the company among competitors?

Many companies look at different parts of data — analysis, cleanup, or integration. We take a more comprehensive approach. This is a data platform. What are the requirements for the different types of data you’re trying to bring in, the comprehensive data? How do you look at cleaning up the data that’s coming in? How do you look at the currency? How do you make sure you can quickly access that data in a comprehensive way? We look at all of those components, not just some individual pieces and parts.

How would you assess healthcare in terms of your C3 framework of data that is clean, comprehensive, and current?

Healthcare is still, unfortunately, at the early stage. We know this from talking to our customers. It’s across the board. Different companies have different strengths and focus on different things, but we haven’t found a lot of evidence that people have taken the full picture and made a lot of progress.

Are healthcare organizations making decisions using data that is either bad or incomplete?

Absolutely. The core question is, what data are we even talking about? The data related to healthcare and the health of an individual includes a lot of free-text data, unstructured data from lab reports, notes, and so forth. When we talk to people through surveys and discussions, 80 percent aren’t looking at that data yet. They don’t apply natural language processing to figure out what insights they could get from that data.

It’s the old story about the elephant. We look at data as this big elephant. Some people look at data as just the foot or the trunk. They’re only looking at the pieces and parts. They don’t usually say their data is good — they admit it’s a challenge, something they’re looking at, or the subject of some new initiatives. We don’t find a lot of complacency and satisfaction.

It gets more complicated where a health system has several groups. Each says they have clean data, and they probably do to a great extent, but the data is not coordinated. How they describe their data and how this other group describes their data are not consistent. It’s therefore not particularly useful in having a real impact.

What due diligence is required before accepting a new source of data to understand its semantics rather than just finding matching columns that can be joined to create a bigger database?

I wish we identified some rules of the road out there. This is a major effort and a major problem. Like everyone in data and healthcare, they’re doing the best they can. Often they’re just prioritizing. They are saying, we can’t absorb all the data, but can you give us the following type of data so we can work on that first? Let’s cut the problem into small pieces.

That’s a practical approach that works, but it takes a long time. They are often disappointed with the impact of those efforts. You get the greatest impact when you’re using the largest amount of data to make decisions.

Will artificial intelligence and machine learning help solve the problem?

We’re in an unfortunate race. People talk a lot about AI and machine learning. But with these systems, as much as they’re making great progress in AI and machine learning, the inputs — unstructured and free-form data — are still weak. An AI engine or machine learning algorithm can’t necessarily turn it into something meaningful and useful.

Years ago, everyone was talking about predictive analytics. We have these great models, but the source data isn’t very good. You’re trying to do more analytics and use more of these advanced tools on poor data to get to that answer faster, as opposed to getting a better answer. People still have to spend a lot of effort to to turn unstructured data into something useful and meaningful that a predictive analytics engine, AI algorithm, or machine learning can do something with.

The challenge, and it’s a big one, is that the unstructured data multiplies the amount of data you have by a factor of five or 10. It’s 10 times more than you used to have, so how do you get meaningful results from it in a meaningful time frame? If it takes a week to process through all that data every time you run a report, create a model, or do some analytics, you’re not going to do it often. That’s why we talk about the currency, meaning how quickly you can get insight out of all of this data that you have.

That’s why we talk about the C3. It’s not just the fact that you have comprehensive data. You’ve got all of your data in an unstructured form, and through an NLP process or even manually, you’ve cleaned it up. It’s consistent, it works well. But now, how do you get results out of that in some meaningful time frame, where you can run reports, look at the reports, and say what works, what doesn’t work, or look at these fields instead? You’re now interacting with the data. That’s where this third C of currency comes in. That’s the only way you get high impact from whatever tools you have, whether it is predictive analytics, AI algorithms, or machine learning.

What lessons did you learn from connecting the aggregated datasets of two HIEs together after Hurricane Florence and validating that the result was accurate at a patient level?

The historical approach to interoperability or interconnecting data is to tell Company A, “Here is how we want you to give us output.” That’s historically a huge problem. Company A doesn’t have the time or they don’t see the value of doing that. Our approach is, just give us what you have. We won’t ask you to change your formats, your fields, or anything else. You give us what you have, this other organization does the same, and we’ll re-index that data and provide one comprehensive view.

The major lesson that we’ve learned in integrating new clinics and new hospital groups into these data pools is that we have to lower the bar of what they have to do. We’re not asking them to change their format, because those IT discussions are often where interoperability gets bogged down, where you ask people to change what they do. We don’t do that. Just provide us what you have and we will make it work for you.

How do you see the company and the general areas of data interchange, quality, and interoperability changing in the next five years?

Our aspiration, and the hope that we have for healthcare, is that tools such as AI, machine learning, and predictive analytics can help deliver real results now. We need to raise a bar on the baseline of getting comprehensive data, making it current so it can be analyzed in real time, and making sure it’s clean, consistent, and makes sense.

If we can get to that baseline, those other tools will get you what you want in healthcare — bending the cost curve, improving outcomes. Without that, we’re still in some ways guessing. If we can address the core data issues, those tools, as well as others that we can’t envision today, can help us make decisions on what it actually happening instead of guessing, which is what’s happening now in healthcare.

Do you have any final thoughts?

The topic of improving healthcare through data is not new. It has been envisioned, talked about, and hoped for for 20-plus years, if not longer. What is exciting now is that the technology, the ability to actually get there, has caught up to that vision. We look forward to helping make this vision come true.

HIStalk Interviews Rachel Marano, Managing Partner, Pivot Point Consulting

Rachel Marano is managing partner and co-founder of Pivot Point Consulting of Brentwood, TN.

Tell me about yourself and the company.

I’ve spent my entire career in healthcare IT, almost 18 years. I’m a computer science graduate. I started my first job at Cerner, where I learned the healthcare IT industry through the Cerner consulting concept. I eventually moved into the hospital side, going to work for Advocate Health Care to get off the road. I did a good bit of implementation and then worked my way into the Epic space and became a certified consultant for a variety of consulting companies. I did everything from build to project management at the project director level.

I launched Pivot Point Consulting in April 2011 with the intent of continuing in the healthcare IT industry, but as a consulting group and a vendor. I’ve seen multiple angles of the industry — software development, the hospital side, the consulting side, and now as an entrepreneur in the healthcare IT space.

What are the most important things you learned from working with Cerner and Epic and their products?

Their products are achieving the same goal, but have different ways of getting there. Both have strong implementation methodologies. Obviously their philosophies and corporate cultures are different. Cerner’s support model is different from Epic’s. Pivot Point Consulting serves both markets.

I’ve worked on both sides and have seen the advantages of both systems, the integration, and how they play in the industry. My roots are Cerner and I spent a good part of my career in Epic, so I think they are equally important in this industry. They create tremendous value for organizations. Many of our consultants have found themselves in both worlds over the years.

Cerner has made a lot of advances in their interoperability and in the international market, which has given them many additional clients. Epic continues to grow domestically and internationally. Epic has a unique way of managing the implementations — giving feedback, doing progress reporting, and ensuring success in install, implementation, and outcomes — which is different from how Cerner manages its clients. They are different animals, with both achieving the same end goal but with different paths to get there. We’ve seen tremendous success with our clients on both products.

How has hospital and health system consolidation affected the consulting business?

It’s certainly a different landscape when there is a lot of merger and acquisition activity. But by definition, that creates opportunity for migration, implementation, and optimization in consolidating older systems to one standard system. It has created a lot of strategy, advisory, and assessment-level work for us and in the entire industry. We’ve done quite a bit of M&A work in the last few years in helping with pre-planning, organizational IT strategic planning, and infrastructure planning for M&A.

We’re doing a large M&A strategy session right now with an organization in downstate Illinois. They didn’t know how to approach the amount of M&A they will be going after in the next 10 years and how that would affect them operationally, strategically, and financially. We put together roadmaps.

Consolidation has, from a consulting perspective, allowed us to look at the industry differently and to see the future state of where these systems will be. Many of them will be unified, integrated, and on similar platforms instead of best-of-breed. We’re going to see a lot more organizations on one platform where they can transfer data more easily.

Are large health systems in less of a hurry than before to rip and replace the systems of the hospitals they acquire in favor of the corporate standard?

One of our larger clients spent probably $200 million on Epic implementation over the years. They were bought by a much larger organization. Things are integrated between the two systems other than the Epic instances. The large organization is maintaining its existing Epic instance and the smaller organization will maintain its Epic instance. They’re both on Epic, but they are running independently by design.

The sheer cost of starting again, redefining workflow, and standardizing all these things between the two systems almost makes the juice not worth the squeeze after these organizations have spent so much money. Things are working, they’re getting the reporting that they need, they’re compliant, and their workflows and operations are efficient with those instances. It makes great sense for some organizations, less for others. Ultimately cost, resourcing, staffing, and other competing projects all come into play into that decision-making. But for some organizations, once they sign on the M&A dotted line, they’re moving forward and starting with the migration.

What projects are floating to the top of health system lists?

We’re seeing a lot of patient engagement, population health, privacy and security, optimization. A lot of managed services, outsourcing the support of these systems. More organizations are shifting energy away from EHR to ERP. The concentration is now that we have the data, what do we do with it? How are we using those measurements to improve performance, clinical outcomes, return on investment, and cash flow? It’s a much more advanced space.

Almost all of our clients are focused heavily on patient engagement initiatives in one way or another. How patients are interacting with their patient portals and what their experience is like from a technology perspective. Systems are in place, we’re live, software is working. Operations, workflow, and clinical and revenue cycle are functional. Where do we go from here in these Phase 2, 3, and 4 post-live scenarios?

Do health systems know what they want to do with population health and patient engagement or are they looking for direction?

Both. More-tenured organizations that have been on these EHR platforms and have software, analytics platforms, or tools are much further ahead in deciding what their initiative looks like or what it should mean. We have small organizations that haven’t even said the word. They’re looking for our guidance and our advisory around the right moves. What tools should we be working with? What vendors are good in this space? Should we be bringing Healthy Planet live? Should we be doing some type of integration?

Most of our large organizations are already underway and have someone leading the charge with population health in some regard. Some of our smaller organizations that might be a little bit further behind are looking for direction and directive. Some don’t know how to approach it, it’s lower on their list, and they’re still trying  to get their technology in order.

What do CIOs tell you is the hardest part of their job?

I haven’t heard as much about CIO turnover. You’ll see it with M&A, but jobs are also evolving into other areas. Some of our CIOs are more focused on innovation and driving revenue into the IT department where before it was more about creating a specific technology infrastructure.

Their challenges continue to be resourcing. I hear this consistently. How do we continue with additional future-state projects with the existing staff? How do we leverage organizations and potentially managed services or outsourced solutions to maximize our organizational resourcing?

Definitely innovation. We have CIOs who are focused on developing programs internally in their IT departments to drive revenue, to create revenue-generating entities within their organization that can align potentially with their IT shop. Potentially consolidating efforts with other local hospitals, leveraging other IT departments and their resources. We’ve seen a lot of unusual approaches to the post-EHR implementation world in CIO roles and evolving how they play in their organizations.

What are the issues most commonly involved when a health system calls you wanting to replace an incumbent consulting firm?

Typically we find that organizations are unhappy with the relationship, the level of consultant talent, or potentially the level of experience and ability. A lot of times, we’re called on because they’re unhappy with the level of service.

But we also find that organizations are looking for a firm that can do more than just one thing and can cast a wider net of service offerings. The group understands their culture, nuances, and their uniqueness and are able to go in other directions, whether it be at an advisory level, a managerial level, legacy, potentially on revenue cycle or clinical, training, and managed services. We’ve seen a good bit of that and we’ve seen organizations that are looking for companies at a certain KLAS level, where they’ve had vendors that have fluctuated in that KLAS standing. Organizations consistently say they’re looking for vendors within the top 10 in their category and that’s who they stick with.

Our focus is relationships, trusted advisory, strategic connections with our clients, and offering value. Being able to identify a challenge and provide a solution. We can do that at more of a strategic level, but also with staffing. We’re trying to approach it differently. We definitely do staffing, but we’ve always been a firm that has been consultant led and consultant driven. We have a different vision on how we work with clients and how we engage with them.

What are the biggest opportunities and threats for health systems, CIOs, and companies in the next 3-5 years?

Merger and acquisitions. We’re going to see in the next 10 years more and more organizations being consolidated, with fewer and fewer independent organizations. The challenges come with combining facilities, the cost of doing that, and technology integration. That will drive the future of the healthcare market. The continued advancement in the technology itself will also change how we are leveraging data.

Do you have any final thoughts?

Our organization is evolving and certainly has changed over the years. When Pivot Point started, we were focused pretty heavily on Epic and Cerner implementation. At that time, that was where the industry was, and that was the main focus of most organizations. We have changed with the times and evolved with the industry and continue to meet the needs of our clients.

We have cast a wider net into some of these divisions, departments, and areas where we see challenge and opportunity. A lot of that is around that managed services space and assisting clients with post-live initiatives. We’re going to continue to see more organizations putting energies in and around that as well as the strategic and more challenged areas around privacy and security, population health, mobility, and even compliance and infrastructure and technology.

HIStalk Interviews Rizwan Koita, CEO, CitiusTech

Rizwan Koita is CEO of CitiusTech of Princeton, NJ.

Tell me about yourself and the company.

I’m the founder and chief executive officer of CitiusTech. We founded the company in 2005. This is my second company — I started a tech support company. Before that, I spent about five years with McKinsey & Company.

When you and I spoke last in 2015, CitiusTech was about 1,600 or 1,700 people strong. We are now at 3,200 people. It’s been a fairly strong growth year this past year and over the last few years. We do a whole bunch of stuff in healthcare technology for our customers across what we call the Clinical Value Chain.

What is driving the company’s strong growth?

From the revenue perspective, we are now part of the Healthcare Informatics Top 100. Our revenue was $127 million last year and are on track for close to $150 million this year. We also made a strategic investment in a company called FluidEdge Consulting, which is at about $25 to $30 million. We are hoping that, on a consolidated basis, we will end this year with revenue of about $175 million. As you can see, that’s a very significant jump from where we were last year.

The growth of the company is essentially coming in a couple of areas. We do a lot of work with payer organizations in the US market. We do a lot of work with provider organizations. Both of those markets have accepted CitiusTech solutions and our services very nicely. We also work with some of the medical software and technology companies and support their growth. That business is actually doing quite well. It’s a fairly homogeneous growth across our offering with providers and tech companies as well as with payer organizations. To a smaller extent, we work with pharma organizations as well.

There is a tremendous shift toward data management, a tremendous shift toward analytics, and now a significant shift toward data science and machine learning. We at CitiusTech have a significant amount of expertise in these areas. We’ve been able to do value-added work for our customers.

How will artificial intelligence and machine learning affect healthcare in the next five to 10 years?

I’m going to talk about history a little bit. Ten years back, the emphasis was on deploying what I would call foundational applications, such EMRs, health information exchanges, and connectivity software. A lot of big problems in data integration still remain and are getting solved. Steadily the focus of the industry has moved towards, what do we do with all the patient data, clinical data, financial data, and operational data that is getting generated? What’s the best way to manage that data? That could be on-premise, cloud, or a more traditional enterprise data warehouse versus big data solutions.

After the data management problem starts to get solved, the next logical question is, how do we start to use more analytics? Increasingly there is a lot of focus on what I would call the standard analytics, like regulatory reporting and and Level 1 analytics. But as the industry is maturing, we see a tremendous focus towards a slightly more advanced analytics. How do you take this massive amount of data that is now getting captured — EMR, lab, pharmacy, or claims — and put it together to be able to solve more complex problems? These are often not possible to solve using traditional analytics, But some large healthcare entities are using machine learning and AI tools to use that information to drive their problem solving.

If you look at the market, there are a lot of smaller proofs of concept and very interesting pilots going on. But the number of real-life deployed applications at scale is still small. You have lots of tools and utilities, but a small number are actually being used for inpatient care at scale. We are trying to help our customers solve that problem.

There is a dichotomy between what’s happening in pilots, research, or academic settings but little of it in production. In the next five to 10 years, we are going to see a tremendous number of successful models getting deployed in the real world for improving patient care, improving efficiency, and reducing cost, all of which are critical for healthcare.

Will use of AI and machine learning create a competitive advantage for health systems that deploy them more quickly or skillfully?

There will be a clear stratification of the types of organizations that can use machine learning and AI. At a simple level, if you take the provider market and hospital systems, a very large entity — Mayo Clinic, Cleveland Clinic, New York Presbyterian, Baylor Scott & White, and other large health systems — will be able to gather that information, and for research purposes or otherwise, build and create their own models.

The bulk of the healthcare ecosystem will largely be dependent on the vendor community to facilitate the use of such advanced tools. If I had to fast-forward five to 10 years, I would say that a lot of the deployment of these tools will be driven by the vendor community — EMR vendors, medical imaging vendors, lab services companies, or some of the other guys who have the financial, intellectual, and technical horsepower. They can aggregate large data sets, build models, and then test those models and get them through the FDA approval process and other barriers that are required before deploying these models in the real world. I see a greater likelihood of that happening. Some of the very large health systems also have a strong R&D inclination and have the ability to drive innovation, but that would be much harder for mid-tier and small hospital systems.

Thousands of models are being created today in healthcare using machine learning and AI. These models can be created in hospital research centers, academic institutions, or by five guys in a garage who have deep clinical insight. If you look at thousands of these models and then look on the production side, you find that the number of real-life applications in production is low.

The reason for that is that customers are getting bombarded by a lot of models — created internally or externally — but they don’t necessarily have the skills required for model validation. Imagine that I’m a large medical imaging company. Tons of folks are coming to me and saying they have great algorithms for medical imaging. I as a medical imaging company must have the horsepower to be able to put together a team that can independently take clinical data, run it through the models, validate the efficacy of the models, and fine-tune the models before I can validate whether the model is effective or not. Model validation is a huge pain area for the industry.

The second area is model operationalization. If you have a validated model, the task of integrating it with the clinical workflow is reasonably complex. Say, for example, that I have a model in medical imaging. Knowing that it’s a validated model, I still must be able to incorporate that model into the workflow of a radiologist. If it’s a colon cancer detection algorithm, then the characteristics of the colon cancer patient’s image needs to then fire up this AI or machine learning algorithm. The algorithm should be able to give back a response that is clearly visible to that radiologist or specialist who is looking at the colon cancer image. The radiologist should be able to either accept or reject the proposition or the findings of the machine, the AI algorithm. Once they accept it, that information should get fed back into the algorithm to incrementally optimize and enhance the algorithm. The result should be presented back as part of the report or to the patient or what have you.

It requires a certain degree of engineering effort to incorporate the model into the clinical workflow in addition to meeting the data science capability. To operationalize the model, you need a bundle of different skill sets — data sciences, product development, QA and validations, and perhaps FDA certification.

We find that technology companies and hospital systems that are trying to operationalize their data science models often don’t have that blend of capabilities that is required for them to truly operationalize the model. We end up with a scenario in which there are a lot of pilot models, the number of models that are validated are fewer, and the number of models that are operationalized is really, really small. Obviously these things will change in the next five years, so we’re at a very exciting juncture, but it will require a serious level of thought on the part of the stakeholders to be able to actually achieve the validation operationalization, which is one of CitiusTech’s core value-add to our customers.

Do you have any final thoughts?

Our company is on an interesting trajectory where are helping our customers drive innovation in healthcare. We are also seeing tremendous growth from a business perspective. I’m really excited about the kind of work that we are doing for the segments that I described. We are setting up a very strong advisory board that we will announce in the next two or three weeks. We’re doing other things to drive the growth of the company both organically and inorganically, actively engaging with other companies that may have complementary skills and solutions to ours. I’m really excited about the growth part of the company and looking forward to the next five years.

HIStalk Interviews Chris Klomp, CEO, Collective Medical

Chris Klomp is CEO of Collective Medical of Draper, UT.

Tell me about yourself and the company.

Collective Medical is a Salt Lake City-based developer of collaboration software. I started working on the company with two of my best friends from Boise, Idaho. We grew up together and we all went to Brigham Young University together. Two of us studied computer science and I was the token business guy. I went off to Bain & Company and then Bain Capital for roughly a decade.

One of our moms, Patti, is a social worker in the emergency department. She had been working on complex patient care coordination, particularly for patients who move across emergency departments. She had hypothesized that not only was this happening, but that a subset of those patients was probably opioid-seeking. Nobody talked about that 15 or 20 years ago, so she was pretty prescient on the ground.

The guys didn’t want to go work for “the man.” Patti, who is a pretty intimidating and awesome lady, told them to “build a computer program” for what she was doing in a circulated Word document and they did. They won a couple of business plan competitions and decide to take it out to the world. It took a lot of years and a lot of bootstrapping, but off we went.

My dad was a physician who told me that healthcare is the highest calling, so that’s what I wanted to do in some form. I had a bit of circuitous path, but I found my way back and we’ve been doing that since.

Collective Medical builds collaborative care networks. We help disparate stakeholders across the continuum — emergency, inpatient, skilled nursing facilities, mental health stakeholders, and even health plans and ACOs with their care managers – become aware when a patient needs them, particularly those vulnerable members who have figuratively fallen. We then unify their records collectively and help pick that person up.

How do you see the company fitting into the interoperability landscape?

We’re attacking from a different direction. I’m not sure I would even classify what we do as carte blanche interoperability. Interoperability is principally concerned with moving data from Point A to Point B. There are a number of pathways by which that’s taking place.

Health information exchange has made tremendous advancements, particularly in the last several years, in linking communities together to unify a care record. There’s a lot more work still to be done, but they’re making great strides. You have the networks like CommonWell and Carequality that are doing that with CCDs and certainly have ambitions to do more. You have platforms like Epic Care Everywhere that are, in some regards, even more advanced in how they link data from Point A to Point B and unify that into a single patient record.

The world is focused on these opportunities for good reason, but it’s a necessary but insufficient condition of driving coordination across an otherwise highly fragmented set of providers in a landscape. We have data silos and we need to unify those. We should have a single patient record that isn’t replicated with duplicative tests or because a patient goes from one site of care to another. However, it’s highly unlikely that the entirety of the country is going to be comprised of organizations like Kaiser, Intermountain, and Geisinger. Even those organizations — and I can say this because Kaiser and Intermountain are among the owners of our company — still have affiliated providers that they don’t own and that aren’t on their same record of care. They still require collaboration and coordination across those disparate providers.

You can either throw a tremendous number of expensive, scarce bodies at the problem, which isn’t scalable, or you can use technology. I’m not talking about mere notifications that an encounter has occurred, which we do, but a deeper level of collaboration. A mental health provider in the emergency department creates a crisis plan for the patient at 3:00 in the morning that involves a primary care provider who is affiliated with a multi-specialty clinic that is not connected to the health system and a Medicaid managed care manager. How do you help those individuals get on the same page and interact with the patient in sequence so that we’re not wasting resources or missing opportunities to help the patient navigate across the continuum, efficiently using the existing technology infrastructure of each organization? That’s the set of problems that we’re focused on.

Notifications are a mechanism to gain provider attention or to nudge them to intervene to mitigate an identified risk. But your phone has 15 notifications an hour popping up and most of that is noise. The more that we can increase the fidelity of those notifications and distill signal from that noise to make them actionable, the better.

Patti’s original work involved competing hospitals sharing her Word document, which was probably shockingly collaborative back then. Is the questionable business case for broad interoperability a non-issue when the addressed problems are overuse of opiates or EDs, which are in nobody’s best interest?

The premise of our business is that bad people don’t go into healthcare. That’s true even with the big, bad health plans that sometimes get painted into a corner. I’m not suggesting that there aren’t disagreements or even mistrust in healthcare and I’m sure there can be tense moments during contract negotiations between a health plan and a health system. But our job is to find the opportunities where there’s an alignment of incentives. When good people are reminded of why they joined up in healthcare and what their true purpose is, those instincts of competition or mistrust that might lead them to not want to share data fall away. When you give them a cause or a reason to collaborate, people will rally.

Let’s say we have a low-income, low-acuity pediatric asthmatic patient who’s bouncing around emergency departments. Nobody’s looking to increase their volume by having that patient coming to their hospital. The health plan, the Medicaid ACO or MCO, and the pediatrician, pediatric pulmonologist, or emergency department physician all have a perfectly aligned set of incentives to get that patient into the most appropriate care channel, stabilize them, and help them lead a healthy life. What level of interoperability and coordination is required to restore that child to a point of health?

How will Virginia’s statewide ED collaboration project work?

Our objective is to connect healthcare at scale. Virginia is a perfect example. You have 130-some hospitals and health systems, hundreds of post-acute operators, and thousands of ambulatory providers across the state, along with Medicaid, Medicare, and commercial health plans. The state’s objective was not only to reach a level of interoperability in terms of data sharing, but even more so, to reach a level of collaboration to manage down medically unnecessary utilization, avoidable friction, or risk.

The state evaluated a number of different paths and vendors and ultimately partnered with us. In five months, we connected 100 percent of the state’s acute care hospitals. We brought on all of the managed Medicaid organizations. In the next wave, we’re onboarding skilled nursing facilities and non-Medicare and other ACOs. We’re beginning to bring on ambulatory providers as well.

The state of Virginia had phenomenal leadership and vision. They didn’t just talk about interoperability that could move data from A to B. They’re goal was real coordination. It’s called the EDCC — Emergency Department Care Coordination — initiative because it starts in the emergency department, the front door of the healthcare continuum for so many vulnerable patients. Virginia is seeking to instantiate workflow broadly out into the rest of the community. Not just through interoperability, but by actually prompting coordinated sequences of engagement of various providers across specific patient archetypes to drive resolution.

Interoperability is the base layer. Then, how do we use data to coordinate human behavior? We make it easier for them by meeting them in their workflow, not making them go look up information. They can understand which of their patients are at a place of need and coordinate with others who can help meet the needs of that individual, to lift them up and catch them before they fall.

How will the company’s momentum or direction change following the large fundraising you completed a year ago?

We bootstrapped the business for most of our history. We aren’t a non-profit, but we’ve effectively run it that way. We don’t dividend out proceeds. The principals haven’t taken raises and draw pretty nominal salaries.

Our goal now is to invest in the platform and to grow networks. Building network effect-enabled platforms is capital intensive because you need to reach critical density in a given geography to create value for the constituents there. We’ve done a pretty good job of that. We’re live in 17 states, not just with one or two hospitals, but penetrated broadly to 100 percent of acute hospitals. We’ve got a bunch more in the hopper.

We realized that while bootstrapping a company gives you tremendous autonomy to do the right thing, it’s a rate limiter to growth. Building a network effects-enabled platform hasn’t been previously done at scale in healthcare. We raised capital to accelerate our growth across the country, to deepen our technical capability with significant R&D dollars, and to gain partners who can help us think through these things since this is our first rodeo.

Our whole point is to act as a rising tide. It’s not to give any individual health system a competitive advantage — which isn’t to say they can’t find it by using our software — but our goal is to help communities lift up their most vulnerable patients. We think about the entire country as that community.

HIStalk Interviews Mike Linnert, CEO, SymphonyRM

Mike Linnert is founder and CEO of SymphonyRM of Palo Alto, CA.

Tell me about yourself and the company.

The team and I have been doing customer relationship management solutions for large consumer service brands for 15 to 20 years. We’ve had the privilege to work with some of the biggest brands in the country, such as American Express, AT&T, Wells Fargo, and Verizon. We’re taking the learnings from those industries — how they take data, how they distill data down to action, how they use it to proactively engage their customers — and bringing that insight into healthcare. There’s a real opportunity for it.

How does healthcare compare to other industries in its use of customer relationship management systems?

We’re 10 to 15 years behind. You can see it in a few key ways. Healthcare is just starting to think about how to proactively reach out to our customers. Traditionally, the business model was that we waited for them to need us and call us, then we focused on providing good access. The paradigm is shifting. It’s both a competitive imperative and a business imperative, but it’s also a health imperative to drive healthier, happier customers. Health systems are beginning to aggressively reach out.

You see pockets of it starting to happen, in particular, with organizations that are looking at population health and starting to take some risk. They’re moving from “we have a lot of data” to “we have lists that we need to call or execute against.” We’re seeing it more aggressively by organizations that have taken more risk, or those that have the luxury of being able to be forward thinking. But they’re in the early stages. They haven’t thought about how to use technology to drive it, haven’t identified the business metrics that indicate that they’re doing well, and haven’t institutionalized the process.

Health systems historically didn’t want to make it obvious in a customer-facing way they were running a business. Is it a change for them to be behave like a for-profit business in going after new patients, upselling services, and measuring doctor loyalty?

I would say it’s less about thinking about being a profitable business and more about improving delivery to customers. Other customer service industries have found a way to take the business they have, distill it down to a few key metrics, and then take action based on those metrics. Can we distill all our data down to value, delight, loyalty, and next best action for every single customer we have?

The most important of those is the next best action. A health system should be able to answer the question of, if I had the privilege of talking today to any one of the million people that I have in my patient / customer database, what would be the most important thing I could say to them? That involves looking across the health system. We execute in different silos — the population health team, the primary care team, case managers, care coordinators, revenue cycle, and on and on. I need to grab all the data from all those different groups and distill it down to action. What do we want to do?

Then I need to the able to prioritize those actions by combining what it takes to keep my patients healthy and loyal, the capacity I have available to serve them, and the metrics that drive my business. The metrics I use to drive my business don’t have to involve profitability. Some look at growth. Some look at profitability, because no money, no mission, and I need to run the health system. But if my goal is delight, I’m measuring how happy my customers are with me. That’s an important metric and it impacts my next best actions as I allocate them.

People miss the concept of stirring capacity and business metrics into patient need. When I’m looking for the right patients to reach out to proactively, I don’t want to call a patient and extol the virtues of an annual wellness visit if their doctor doesn’t have any capacity to do annual wellness visits for the next three months. If I’m going be proactively reaching out, I need to prioritize who I can serve the best right now. That’s a fundamentally different way of metric-driven thinking.

How much overlap exists between pure analytics systems versus your system of using analytics to drive consumer engagement?

We think of ourselves as an algorithm-driven CRM company. It has two parts. Part one is getting all the data that we can, factoring in the corporate priorities or imperatives and the available capacity. Running algorithms that map the combination of those three variables into next best actions for everybody. That’s part one, the analytics.

Part two is how to engage customers around those next best actions. Engaging them is where a traditional CRM takes over, but they’re not well married to that next best action data analytics piece within healthcare. Once we inject those next best actions, we can start looking across the different silos of the business and saying, for this list of patients, the population health team is the most important next best action. The population health team might determine that their metrics are driven by the imperative around driving down per-member, per-month costs, which is really a proxy for making sure we’re seeing the right numbers at the right venues and the right times.

I’ll give you a tangible example. Some of our clients are coming to the conclusion that the next best actions that can help them bend the cost curve and drive patient delight are weekly or monthly phone calls. Maybe we take our high-cost, high-need patients and put them on a schedule. We’re not calling to say “you have a care gap” or “we have some coding gaps we’d like to get closed with you.” We’re calling to say, “Hey, how are you doing? We noticed that you’re consuming a lot of care. How can we help you better map into the services we have that are maybe more appropriate for you, making sure we’re seeing you in the right venue?”

We find that those weekly and monthly calls aren’t necessarily just health focused around how the patient is feeling, their pain, or their medications. They evolve to be things like, “How did you do last week? You were going to do a 5K, how did it go? How’s your family doing?” It’s in the context of those weekly calls that we discover the things that we can be doing to help. Referrals to job placement, referrals to food banks, getting a patient to see a primary care doc for an emergent issue before it turns into an ER visit.

This sounds like new ground for hospitals in having non-billable patient conversations. Do you coach them on what they should be doing?

We work together with our clients. Our business model is fewer, bigger clients. We talk to every one of our clients every day. As we learn things with different clients and we see things work, we’re constantly sharing.

But the driving force usually has to start within the medical group or the executive team. There has to be a metric or an imperative that gets reduced down to next best actions. Calling people with a potentially high need is not enough. You need a true metric that says, the way we’re going to measure success around this effort — and I’m grabbing a random one — is that we’re going measure per-member, per-month cost and customer delight. If we do that, then we can show that based on those metrics, we can identify the actions that drive those metrics. We can reduce our next best actions to a dashboard that we can manage against. It’s not spinning up an effort, but rather trying to drive a metric, and in service of that, here are the things that we’re going do.

Frankly, things go pretty fast. If you don’t see the metric moving the way you want within a month or two, then something’s wrong. If we’re doing a good job of tracking both activity and accomplishment, we can say that the metric is not moving because we didn’t get in touch with the patients we said we wanted to. Or, we got in touch with them, but our schedules are such we weren’t able to get them in for the appointments we wanted them to have. Or, we got them scheduled, but some of them no-showed the appointment.

If you’re tracking that, you can decide what to do differently. You should be able to be reduce whatever issue you’re tackling to next best action and what to do differently for each customer.

Are those health system and medical practice efforts segregated by whether a given patient is covered by a risk agreement versus being billed under fee-for service?

Some of those things get considered some of the time. We’re looking for the opportunities to create value for our customers. What do they need from us? You make a really good point that when people come to us, it’s easy. We just do the things that they ask for or the things that we believe they need. When we switch that and say we’re going to go to them and we’re in the proactive outreach business, we have a problem. If we have a million people in our customer database, we couldn’t call all of them today even if we wanted to. If somehow we could call all of them today, we don’t have appointments or services available for all of them today. Now we’re in the business of trying to figure out the most important people to call.

You’re correct that part of the decision involves corporate priorities. If we have a priority around our ACO and one of our priorities for our ACO patients is driving down per-member, per-month cost, then we look at those people who might have the the biggest impact and what things we can do for them, then call them first. Those things can range from consuming care in the right place to leveraging social determinants of health. If we know financial security is a challenge for you right now and that drives your health, then let’s make sure that we’re talking to you about referral to job training or job placement and engage around some of those things through the proper channels.

What best practices have you seen for health systems improving their relationships with physicians?

You have to be really clear if you’re going to have physician outreach. What’s the purpose? What is the definition of success? We see a lot of physician outreach teams meeting with providers and talking about referral patterns, but it’s not clear how you measure them. An executive team could say to the provider outreach team, we want you to make sure our providers are reducing leakage. That’s probably the most common one we see.

But some of our more sophisticated customers are also saying, we want to educate our providers about what’s going on in the system and where we think we’re moving forward. Or, we want to educate our providers about our solutions to help them drive their quality metrics. Or, we want them to understand that we have marketing programs they can take advantage of. That’s one aspect.

The other aspect is that if we do next best actions the right way, we’re having a pretty big impact on provider satisfaction. Systems that have moved into population health are using their population health system to surface lists for the primary care office, such as those people who need retinal exams or breast cancer screening. The lists help offices hit their quality scores, but they create another administrative burden for the office. Now the office has to figure out which lists move which metrics, which metric they are furthest behind on, and how they can find time to do outbound calling. That’s a challenge for them.

The right way to do that — and the way any other industry would do it — is to say, let’s look at those lists as yet another feed into our candidates for next best actions. Then go to the office and say, we have one list. We’ve run the algorithms for you. We’ve prioritized the most important people for you to reach out to.

If we’ve done that right, we can even offer to take that outreach effort out of the office. And if I’m really looking forward, instead of having you remain accountable for your quality scores, let us the central health system be accountable for reaching out, driving the right patients to you, getting them on your schedule and into your office, and letting you know the most important things to do with them while they’re there. That puts you in the business of engaging the patients, doing the things you see as most important. Just make sure to check our list of why this particular patient is in your office or why we reached out to them to come see you.

Do you have any final thoughts?

Healthcare is evolving really fast. If you look forward five or 10 years, most health systems are under-serving their customers today. They are under-investing in their customers and in proactive outreach. If they can generate these lists of next best actions, use the data and lists they have, inject their business imperatives and capacity availability, and map next best actions for every single patient, then they can engage in proactive outreach in a way that drives patient health, drives patient delight, and hopefully reduces provider burnout. It also drives financial performance.

That really is a big change because it requires rethinking about metrics and where they are going. We’ve taken in over five billion lines of data in pursuit of coming up with these next best action plans for every single patient in our universe.

The imperative we see is that if you don’t do it, somebody else will. There are a lot of people coming into healthcare today who are trying to compete with health systems. Their number one observation is that most patients are not tightly tied to those systems, so they have an opportunity to insert themselves between the health system and the patient and grab that customer relationship. If health systems can start mapping the next best actions and engage in proactive outreach, they can drive the relationship they want to have.

I would love people to think about us as the next best action guys. Being able to reduce all the data to actions, not just presenting more data, is the critical thing that will happen in healthcare. It has proven successful in every other consumer service industry.

HIStalk Interviews Rich Berner, CEO, MDLive

Rich Berner is CEO of MDLive of Sunrise, FL.

Tell me about yourself and the company.

I approach this as technologist, having grown up programming computers since fourth grade. I got into healthcare about 15 years ago, working in a variety of roles across a number of the big EMR and population health management companies. While I come at this as a technologist, I spend most of my day with teams and clients, getting them to focus on the outcomes versus technology.

MDLive was founded in 2009 and serves over 27 million members, providing virtual care for urgent care, behavioral health, and dermatology needs. We have over 1,200 clinicians across the country, operating in all 50 states 24/7.

Surveyed Americans love the idea of virtual visits, but the number who have actually experienced them is small. What will drive adoption?

Our greatest challenge is getting the word out there. People who use this service tend to come back about 1.8 times per year after the first visit. Where payers or employers are covering most of not all of the cost of the visit, we can get adoption rates as high as 30, 40, or 45 percent.

Have state-specific virtual visit restrictions mostly been eliminated?

2017 was an inflection point. It felt like the regulatory environment, payer environment, provider environment, and consumer demand came together. We’re seeing significant growth this year. Now you’re seeing CMS continue to talk about the future rules, and now that they are seeing the results, they’re going to be covering more types of visits virtually.

Have health systems mostly decided not to set up their own virtual visit service?

Whenever new technology comes out, people might be a bit threatened by it. But we have seen our hospital and health system clients view us as a partner, where they’re using our platform with their own clinicians, and where appropriate, they’re using our network to complement what they’re doing. We’re both trying to solve the same problem, which is how to improve the access and convenience of healthcare while increasing quality and driving down cost. We enable them to do that in partnership versus competition.

How do you recruit providers and prepare them to practice in a virtual environment?

We have nine years of hard work doing recruiting to bring these folks on board. They get credentialed with our groups. We also give them training, not only on the tools, but also things like webside manner and how you provide care virtually versus physically.

As a large, national medical practice, can you do a better job than small practices in terms of practicing evidence-based medicine and monitoring quality and patient satisfaction?

For our payer, employer, and even our health system clients, when you’re able to manage quality with fewer touch points, you have a better ability to drive quality initiatives. We’re doing it at scale across the nation. We definitely think that’s an advantage for us and our group to improve quality.

What expectations do virtual visit patients have and what do they like or dislike most often?

While many patients have a good relationship with their primary care physician, many don’t have a primary care physician at all. Or even if they do, for certain types of conditions, the most important thing they’re looking for is convenience or privacy. The ability to get the care they want, when they want, where they want. We are working with patients to identify situations when they are less likely to be satisfied. If they think they already know what the answer is and want a certain prescription or antibiotics or they have a condition that may not be appropriate to treat virtually, we do our best to identify that very early on in the process so they don’t get too far into a visit before recognizing that it may not be appropriate for virtual, or the condition they have may be different than they thought.

What patient information is available to the provider before the visit? What information from the visit is shared with the patient’s primary care physician or health system?

For our payer, employer, and hospital and health system clients that feed us data, the provider has access to all of the information that those organizations have. In addition, we have Sophie, our interactive chatbot, that collects a certain amount of data. We’re rolling it out this quarter, where she is automating the triage process so that the provider can get presented with predictive SOAP note. It’s our goal to give the provider as much of the patient’s story as possible before they see the patient, so that when they do, they can focus on the things that they were trained to do — empathize, educate, and make sure they get to that proper diagnosis quickly and develop the plan of care.

What technologies do your doctors use to document and complete the visit?

They choose the device they want to work from. Then we have a lightweight EMR that automates as much of the visit as possible to focus on letting the physician do what they’re trained to do, which is focus on the care they want to provide. We take out as much of the registration, billing, scheduling, and documentation as possible. We’re seeing this have a significant impact on helping solve one of the biggest problems that is out there, which is physician burnout.

What are the characteristics of doctors who most enjoy providing virtual visits and what is their satisfaction level compared to a more traditional setting?

We do surveys regularly and focus on addressing any concerns that are raised. We believe there will a movement for the rise of the virtualist. These will be classic clinicians who, more and more, want to do this full time, similar to the hospitalist movement in the 1990s. We are seeing a broad array of physicians who want to do this, from millennials who want work-life balance to people who are getting near retirement and want to pull back from the shifts but still want to be able to provide care and focus on care rather than a lot of the administrative stuff.

Are providers satisfied with working episodically and not having ongoing involvement with that patient’s overall health?

I’ll answer in two ways. One, our physician satisfaction is higher than most national groups and survey averages that we’ve seen. They get a lot of real-time feedback. Once consumers become aware of this service and use it, they are so thankful for not having been forced to go to the emergency room or urgent care or driving 50 miles. They are getting that real-time feedback. They’re also getting feedback from surveys. For a lot of our clinicians, the patient can select if they want to schedule an appointment with the physician versus see one in real time, so a number of our clinicians see the same patient when they request a visit with the same clinician.

Does the patient choose the doctor or their location before the visit begins? How is a patient matched with a provider?

The clinician they ultimately see has to be licensed to provide care in that state. The consumer has the ability to say, I want to see the first available, or I want to schedule an appointment from a list of clinicians who are licensed to practice in the state.

Are you seeing doctors seeking medical licenses in multiple states just to prepare themselves for offering virtual visits?

Yes. The vast majority of our clinicians have multiple licenses.

What are the benefits of virtual care for people who are seeking counseling or psychiatric services?

As much as 40 percent of the population has behavioral issues. Many of them aren’t getting addressed, either because of access or embarrassment. We’re excited about providing these services virtually, which gives these people the ability to do it in the privacy, comfort, and convenience of their own home.

How will virtual visits change in the next 3-5 years?

We’ve done great work over the past two to three decades in automating the healthcare industry with electronic medical records, population health management systems, and even incorporating genetic information to make sure plans of care are personalized. But we still fundamentally haven’t disrupted the healthcare industry or the way care is provided. Telehealth represents a real opportunity to disrupt healthcare — to put it on the consumer’s terms and to give them care where they want, when they want, and how they want.

Looking out three to five years, we can see a healthcare system where a large portion of primary care is not only provided virtually, but is also automated and optimized through things like artificial intelligence and machine learning and with chatbots like Sophie, to help make that shift to proactive, predictive health management as well as care.

Do you have any final thoughts?

We’re extraordinarily excited about the opportunity in front of us. It’s not often that you can provide a service that’s better for the consumer, better for the clinician, and better for the healthcare system overall. Consumers can access it conveniently, clinicians can focus on providing care, and quality and cost will improve. It’s an exciting time for MDLive and the healthcare system overall.

HIStalk Interviews Paul Roma, CEO, Ciox Health

Paul Roma is CEO of Ciox Health of Alpharetta, GA.

Tell me about yourself and the company.

I have been the CEO of Ciox for a little over a year. I came from the professional services world as the global head of analytics for Deloitte & Touche, which constituted 87 countries and all of the analytics work that that global firm does. My background throughout my entire professional services career, outside of running the global analytics business, was healthcare — life sciences, domestic government work, international healthcare work, providers in health insurance.

Consumers complain about the cost of getting copies of their electronic information from their providers and Ciox has sued over the HIPAA limitation on how much providers can charge. What are the current topics around that issue?

Just to be clear, Ciox is not suing over what consumers get charged, so let me reframe that a bit. We are, in particular, very pro-consumer and consumers getting their health records. I want to be 100 percent clear on that. Our lawsuit has nothing to do with the rate in which consumers are charged or whether they’re charged.

Our view is that there is a burden that is put on hospitals and physicians in professional, for-profit situations. The legal profession, the insurance profession, and others are using a consumer angle to create a burden on the doctors to feed them the record at a very low rate. Our lawsuit has to do with that. We believe that the people that are using information for commercial purposes should pay, and that the cost of producing that information in the proper format should not solely rely on the doctor and be a loss item on their balance sheet. They should be reimbursed for it. That is the bulk of our beliefs and our lawsuit.

So a for-profit company using a patient’s medical record for commercial purposes is different than patients getting copies of their own records?

It is, yes. There’s a explicit differentiation between the two.

Say I get a study done. I go to one of my local hospitals and I want to get that record to bring it to my primary care physician. We do literally millions of those, sometimes multiple millions a month, in which we either don’t charge at all, which is the usual case, or we charge very little. We are very pro consumers getting their health information.

We also do tens of millions of doctor requests for information for continuity of care and things like that, for which we don’t charge, of course. If it is for the consumer and for their health, we are very much in favor of that information being dispersed, being liquid, and transacting at a frequency and rate that is conducive to health being improved.

Are you seeing anything on the horizon that would change the way that the ownership and exchange of medical records will work in the US?

Near-term, no. Long-term, in my opinion, it is somewhat inevitable that the benefit of the data flowing in a secure, de-identified, and traceable way and being available for research outstrips all the reasons the walls are built up for us not to share the information. Long-term — whether it’s a change in definition, a change in regulation, or a change in the belief system of how that information moves — I do think we will see change.

What is the interoperability technology marketplace position of the newly announced HealthSource?

HealthSource fits squarely in the enterprise need for clinical information. We service providers, health plans, life insurance companies, and life sciences companies. HealthSource is a cloud-based, HITRUST-certified product that allows for both the interoperability with third parties — because we have hundreds of thousands of digital connections that we build into workflows — and sharing within the enterprise.

At some of our larger clients, we service 100 different use cases that require clinical information. Health insurance examples would be prior authorization, medical management, risk adjustment, and quality. Our HealthSource software integrates to those use cases and provides the information that they need from the medical chart, the EMR, to improve their process with the clinical information instead of relying on, in the health insurance case, claims and other secondary clinical information. We’re using the primary source to improve their use case.

How much technology and labor is involved in providing a complete electronic chart?

It varies. I’ll say two things. One would be that, as both a citizen and someone running a business, I wish it didn’t vary. I wish it was more liquid and that the outcomes were faster. The reality of the situation is that a large integrated health system has, on average, 17 different EMR systems. A vast majority of hospital systems have not even brought their acute systems to a single system, let alone all the specialty, post-acute, ambulatory, and other. Even within one practice area, they haven’t centralized. I would say that’s the norm.

Because of that, to your point on labor, about half of the cost comes from technical integration, formatting, and information and data management. About half the cost is still from manual touches, whether that be on the front end to work with the information or on the back end from a QA perspective.

Our particular business is reliant on, and cautious of, the regulations that are put on it. We are fully compliant to SAMHSA, as an example, which is a federal regulation to redact substance abuse information. There are many other things that we do. We not only get the information and put a longitudinal view together, but we structure the information — both technically as well as from a redaction perspective — so that it is compliant in the situation we’re offering.

One of the major distinctions for us that has cost associated with it is that we are not a generic exchange for clinical information. We are very particular as to what we’re sharing and making sure that it meets the regulations, that the information’s been redacted appropriately, and that the endpoint is receiving the format that it needs. All of those things are unfortunately more costly than just broadcasting information.

We have the possibility of expanded data sets that include genomics data, wearables data, and other data sources that aren’t being widely captured and collected and stored today. How do you plan for that as a company?

Our clients ask us to add a major source almost monthly. Many are the examples that you just gave. For example, genetic information and the translational makeup of information that combines phenotypic and genotypic data together to create a full picture of the person’s health and vitality. That’s been in our system for a long time, so we’re covered off on that. But below that, there are numerous social determinant categories, such as activity-based tracking from wearables and other IoT devices. We have a backlog on a monthly basis for life science companies and health insurance companies that are driving those changes and requests for further integration.

We lean in heavily on the Argonaut system, which is HL7 standards-based FHIR communication. It simplifies those things. The endpoint can communicate with us at that standard and they’re using the CCDA format, which we use. It’s pretty easy. But some of them still require proprietary interfaces. We maintain at this point about 700 different interfaces, so it’s still pretty costly to do all the endpoint integrations.

Are you seeing promising uses of artificial intelligence or machine learning to make sense of that wealth of data that we now have moving around?

This is a whole topic in and of itself. My background is as a data scientist and my formal work is in the technology of artificial intelligence and cognitive computing, so we can go as deep as you want.

Current state is that for us as company, it’s our largest investment — the structuring of data and the intelligent understanding and summarization of that data. Within the HealthSource product, we have a component called Smart Chart that takes all of the unstructured elements — progress notes in the EMR, a pathology report that’s coming out of the prognostic indications or from test results — and structures those and puts them in an analyzable format.

To your point on AI and cognitive technologies, we then come back through in a cognitive match and build a probabilistic model with confidence levels that deciphers the diagnosis codes, the DRG codes, and many of the other prognostic indications and then builds insights from those. Those insights in our generally-available product are generating tons of value.

To get back to the first part of your question, those technologies I just described are already showing literally hundreds of millions of dollars of increased profit for our clients. Hundreds. Not tens, hundreds. That fuels our investment and the industry’s investment. The “man versus machine” shift in terms of capital investment in those things is increasing on a monthly basis. There’s more information that leans in on the limitation of what a human can decipher.

But the information and the correlation of that information is also getting to the point of complication. Even if you or I are reading it, it’s a 1,200-page EMR. You’re deciphering a list of genetic bases from the four billion genetic bases that are written in a progress note that don’t have a paint-by-numbers key next to them. I have an MTHFR gene expression and I happen to know that that’s a methyl pathway issue that could cause drug toxicity. There’s lots of other things. But that’s in the progress note written out, and as the clinician looking at it, there’s four billion of them. How in the world do I decipher that?

I’m using the most acute example, genetic basis, just because of the number. But the complication of this information has exceeded what even the most well-trained doctors can comprehend. That comes back and fuels the investment curve. There’s been so much progress made and it’s starting to pay off.

Do you have any final thoughts?

The US needs a better way of sharing information — with consumers, for seeding research for better therapies, and getting better information to doctors. Ciox is in the middle of helping all three and that’s the mission that we’re on. The HealthSource product is squarely designed to first give better information to doctors, second to facilitate consumers to get that information in a format they can use, and then third to power research and insights at these large organizations — health insurance, life sciences — that are ultimately trying to create better therapies for us. We’re excited to be part of that mission and believe there’s a lot of value in it.

HIStalk Interviews Lillian Dittrick, VP of Actuarial and Healthcare Analytics, Health Alliance Plan

Lillian Dittrick, MAAA is VP of actuarial and healthcare analytics at Health Alliance Plan of Detroit, MI and is a fellow of the Society of Actuaries.

Tell me about yourself and your job.

Henry Ford Health System owns a health insurance company called HAP, Health Alliance Plan. I am building for them both their actuarial and analytics function. I am an actuary and an FSA in the Society of Actuaries. I have extensive actuarial and analytics experience for both the payer and the provider. This is a good and exciting fit for me since it’s both of them combined. I feel strongly that payers and providers need to collaborate for both to succeed. We have the same end goals. Whether we’re calling them members or patients, we’re supporting the same people.

Prior to this, I was at Highmark, leading their provider analytics area, and before that, I spent a number of years embedded in a large provider system.

When I hear “actuary,” I think of a life insurance company person who can tell from an Excel worksheet when I’ll die. What is the training of actuaries and how is their analytics approach different?

[laughs] Your comment is more what a life actuary would do. A life actuary is more mortality versus a health actuary, which is morbidity. There are a number of tracks you can go down for an actuary. It could be in more the investment realm, too, and a lot of actuaries are in that space.

Predictive analytics is a lot of the education, which is newer to healthcare, but not newer to many industries. You have to go through a series of exams that have a heavy reliance on math, actuarial science, and modeling in general. It’s really in that modeling space.

Over the last few years, the Society of Actuaries has added specific education that speaks to predictive modeling. They’re revamping their education and recognizing and understanding the importance  of predictive modeling. Actuaries, with that heavy math and modeling education and background, are well suited to do that kind of work in any industry.

Beyond EHR and claims data, what data sources are important for creating a healthcare model?

Both of those are important. It’s important for payers and providers to share that information so they have as complete a picture on a patient as possible.

Also important are social determinants of health. There’s a lot that goes on with a patient that can be used to predict their future healthcare use that you will not find just looking at their claims history. Information about whether they have someone to help them, if they need help getting medications, or if they have transportation issues. People present in the ED or hospital because they didn’t have a way to get to their follow-up appointments. Or, they have a financial barrier to obtaining medications that would keep them out of the ED and hospital. Payers and providers alike, more strongly in the provider realm right now, are recognizing that and are performing assessments to capture that information.

A number of government grants are going on now to help providers work with the community to link people up with all of the resources that may be available, such as social services, that can help fill in those gaps to make sure that people are getting the appropriate care they need, when they need, and where they need it.

Reports suggest that insurers are buying consumer data to, depending on who you believe, either cherry-pick less expensive patients or to create tailored health interventions. What are people doing with less-obvious data sources and what are the ethical issues involved?

That is very much a concern. When SOA did the survey, challenges around HIPAA and regulatory issues came up pretty high as a barrier to implementing predictive analytics. All insurers that I have worked for, because you were speaking more to the insurance side, are very aware of those ethical issues. I haven’t seen them using any data inappropriately. They’re all using that data to try to understand the best care to wrap around a patient. I’m aware of least two places, here and Highmark, that have programs with Lyft to help people get the transportation they need to their appointments. Unless you are able to collect that information, you’re not able to provide that extra level of care that the patient needs to make sure they’re receiving that care where they need it and when they need it.

What are the analytical challenges of trying to draw insights from a population that’s heterogeneous to begin with, but that is also changing all the time?

Not having complete data and those regulatory issues or having the technology and skill to deploy those kinds of models. I don’t think employers always realize that when they have actuaries on the staff, those are the skills they need and the people who are suited to doing that kind of work. They are under-utilizing the skillset in the actuaries they have.

Incomplete data is always on the top of the list. What I have found in my experience is you can do a lot with what you have. You do not need to wait for perfect information. There will always be holes and some gaps in your data. Tools, technology, and methodology can help you fill in some of those gaps. But even with having some gaps in data, you can draw a lot of good conclusions by just going forward with the information that you have.

How could a mid-sized health system create a predictive analytics service and what low-hanging fruit might provide the fastest benefit?

Leverage models that are already created first. There’s a lot of them out there that are good. It’s not like you’d have to re-create the wheel and do all of that coding yourself. There’s models that are available out there that you can utilize that use both claims and EHR data. You can alter them based on what you have.

The larger EHR vendors have embedded predictive analytics in their model that can be leveraged. If you are a smaller organization trying to figure out where to start, especially on the provider side, you can generally utilize models that you have within the vendor that you’re already using.

The low-hanging fruit that I’ve found involve inappropriate ED utilization, inpatient readmissions, and admissions for something that could have been prevented around chronic conditions. I’ve seen models in all of those areas embedded in EHRs. That’s the easiest place for people to start.

University of Minnesota is offering to license an algorithm they developed to predict one-year patient mortality based on EHR data. Is it as simple as just creating a good algorithm and seeing results?

If someone has created an algorithm, you can take it in house and make it fit for your data. It could be that with your population and demographics, you’ll get different results, and maybe you need a variation of that model. I’m not saying it’s a “one size fits all” model, but if a health system or payer has found success with the theme of a model – something around readmissions or blood utilization — then it’s likely that someone else will, too.

Do actuaries get involved on the front lines with convincing clinicians to trust their information and to change their habits?

Yes, absolutely. The success I’ve found is from beginning to end, where we have had the physician and clinical involvement. Both from designing new algorithms and new processes all the way through to having physician champions that are out there helping us. Sometimes they are the ones taking that message out and sharing it with other physicians. I absolutely believe that.

Whoever your audience is, but certainly with the providers, you can’t just dump a whole bunch of data and Excel spreadsheets on people. You need to present it in a way that’s visual, actionable, and tells a story, so that anyone can pick that information up and know the two or three things to work on right now for success in that model solution is that’s being developed. You’re not going to pull it across the finish line unless you have the physician champions as part the build as well as visualizing the information in a way that is easily digestible.

We have mountains of newly electronic information as well as AI and machine learning tools to apply to it. What will be different in five years?

There will be more leveraging of AI, the automation technology that helps us handle that huge amount of data that we’re dealing with today, along with doing a better job of visualizing the data.

HIStalk Interviews Jeremy Bikman, CEO, Reaction Data

Jeremy Bikman is CEO of Reaction Data of American Fork, UT.

Tell me about yourself and the company.

I’ve spent a long time in healthcare doing research and helping hospitals, clinics, and even the vendor side make better decisions. That’s what our company does. We get organizations, whether they’re a hospital or vendor, answers to their biggest problems really quickly.

What are the most-hyped and most-promising healthcare technologies?

Over-hyped is blockchain, hands down. People don’t even know what it is. It’s moving so fast. You would think that in an industry like healthcare, people would be more skeptical because we’re supposedly a more data-driven, evidence-based industry. You go to HIMSS and someone says they’re doing something with blockchain. You ask them to describe its advantages and they end up talking about the technological benefits. You ask what that means for a hospital and they can’t articulate it. How is it going to improve the bottom line, top line, patient care, whatever it is? They’ll answer it as a feature statement rather than benefit.

Most promising is, surprisingly, artificial intelligence. I say “surprisingly” because healthcare is typically last to the tech adoption game on anything that’s emerging. But we’re seeing that it’s picking up the pace pretty significantly, mainly in the imaging departments, but also expanding outside.

We launched some research around that. We wanted to keep it open ended, asking the C-suite where they saw it being used without giving them a list to choose from. Number one was virtual health services. It’s interesting that they said that since CMS just said that they will materially up the reimbursement level for telehealth, telemedicine, or I guess I’ll use the macro term virtual health. That correlates to what the hospital C-levels are saying, that AI will be the most disruptive, impactful, and beneficial emerging technology.

Second is machine learning and deep learning. I was surprised that CEOs of hospitals said that. We get skeptical when someone makes a choice like this, so we asked, you said machine learning, do you even know what you’re talking about? They really did. They could talk about it, saying, we have all this data, and if we could use machine learning algorithms to look at it, maybe it could help us predict the types of patients who are most likely to miss an appointment or not take a med. These algorithms could help us with medication adherence, following a certain protocol, or even with logistical issues.

On the imaging side, it was much easier for them to answer that it could help a radiologist diagnose something or notice some lesion or some problem with a vessel within an image much more quickly. That would make them more efficient and hopefully raise the clinical efficacy of the encounter and the diagnosis.

Then they brought up the nebulous interoperability, which they couldn’t describe it at all. Most of the research I’ve seen around interoperability is pretty garbage. Everybody defines it in their own way, and if they can define it their own way, then we don’t have a definition. I don’t know how you attack a problem that has a nebulous definition.

Wall Street and private equity firms are buying high-income medical practices such as dermatology and are already deep into hospitalist, ED, and anesthesia staffing. How will that change the market?

It will be interesting to see if pay-for-performance ever really takes off or some mandate from on high alters the financial dynamic whether they’ll really stay in. Do they go the way of a lot of these vendors that come in and do the hokey pokey, where their right foot’s in, their right foot’s out? You never know. That’s why a lot of healthcare organizations are professionally skeptical. They’ve learned to be about those new entrants that say they know healthcare or that buy their way in.

People buy up amazing companies and do layoffs right away. You talk to those acquired installed bases over a few years and they say, it’s all changed. Things were going really well before. I understand economy of scale, but the problem is when that they get integrated, it goes in the opposite direction. Things are getting worse. They might be getting some sort of year-over-year benefit from economies of scale, but the end users don’t.

You’re seeing the same thing with Wall Street, private equity, and others jumping in. There’s money right now and there’s inefficiency. But once they’ve squeezed as much inefficiency out as possible, then they start looking at their returns. They owe their limited partners or their investors. That’s who they serve. How long will they stay in the game? Are they in it for the long haul? I doubt it. Some are, so they will be able to make some improvements and then look at it as a long-term play.

You’ll see a lot of them getting out in the next decade or less. You can see these guys having to go private again or coming up with their own ownership groups or whatever it is. You’ll see the investors stepping out. That’s again if the government doesn’t step in, behind the scenes, and collude to help make markets happen, keep people in business, and keep themselves elected. I’m going to get really cynical if we get into the government aspect. Which I’ll certainly do, and I’m willing to fall on my sword about my opinion of government and business collusion. But enough about the HITECH Act.

What changes have you seen in the big four inpatient EHR vendors of Epic, Cerner, Meditech, and Allscripts?

Hospitals and clinics have learned that an EHR is not the panacea it was made out to be, or I should say, it was mandated to be. It certainly needed to happen, but whether it needed to happen as fast and in such a rigid way is up for debate.

\What they’re finding out is that, we put the EHR in because we were explicitly or implicitly promised that we would see a lot of improvement. Patient care would improve, and over time, our organization’s financial position would improve, all because of digitizing patient records, order entry, the MAR, and everything else. What you’ve seen — at least from the research I’ve done and research I’ve read – is that there has not been a material or even statistically significant improvement in hospital bottom lines, clinic bottom lines, or patient outcomes.

Now what are they doing? We have to create accountable care organizations. We have to coordinate patients. We have to get them in their own little sub-populations. How do we treat those patients? We had better have analytics. Do we even have a real data warehouse? Crap, now we have to go get a real data warehouse. Now we have all the data, we don’t know how to analyze it, so we had better get several analysis tools. Do we know how to do that? No, so we have to hire Accenture or Deloitte or some other firm to come in and help out.

They start realizing that for all the time and money they spent on an EHR, all they have done is that the ball got kicked into the end zone and it’s been advanced to the 20-yard line. You mean that we have 80 yards more to go? Yes. Now they’re having to look at everything else to understand that the EHR, these big clinical systems, get put in and they’re the operating system of the hospital. You have a lot more apps and a lot more things that you have to load on top of it.

That’s not the way it was sold back then. Ten years ago or so, no one was talking about having do do all these sorts of things and I’m not sure everybody knew it. When you’re a hospital trying to run your organization in dealing with state mandates, local mandates, employers, payers, and Medicare, it’s tough. You have to rely on the vendors you work with to help you out. You really do. I’m not sure the vendors really understood that it’s not just putting in the EHR. I don’t think anyone would have bought it if they realized, we’re going to spend how much of our budget? Then the upgrades are going to be all this and other sorts of stuff? That’s just the foundation now. We have to do all these other things and bear all this additional cost and labor.

It’s shocking that so much money has been spent on the space, our space. What are the outcomes? Are hospitals in better financial shape? Has putting in all this technology caused a significant improvement in outcomes — financial, operational, specifically for patients? No. You certainly had to put in these systems, but the end result has not been as super positive as everybody expected. I don’t think anyone was necessarily to blame. I don’t think Epic, Cerner, Meditech, or Allscripts went in knowing, ha, you’re going to have to dump huge amounts of money here and then load all these other solutions over time. Because I don’t think people anticipated it. We have so much more that we have to do. I really see healthcare at about the 20 or 25-yard line.

Looking back at the HIMSS conference, how are vendors approaching the market?

It’s net fishing, where you’re just throwing out instead of being precise. They’re just trying to catch it all. So many vendors say they can do pretty much everything. If you look at the HIMSS listings for vendors, you know some of them really do just one or two things, but they will list 15 or 20 because they’re just trying to catch attention.

HIMSS is something you have to do, but I’m wondering about the value of what’s going on there. I love it because you get to collaborate with everyone. That’s the best part of it. People come by our booth just to hang out, ride our bikes, and try to break a clavicle or something. They just come to talk. Most of them just shake their head because everybody does everything and it’s all becoming white noise. It’s hard to differentiate.

My recommendation to vendors is to know who you are, know your ideal customer who you can have the greatest success with, and try to be precise in your messaging to that group. Because everyone’s getting washed out. That means that only the largest of the large are going to get attention because of their sheer scale, size, and reach.

Being precise is better for attendees and eventually better for vendors. You may not get as many people coming by your booth, but you’ll get a better quality of interaction and probably end up closing more business. But taking that approach is a scary step into the dark, because everybody is saying they do lots of things and trying to get more people to come in. That confuses the message and prolongs the sale.

The most successful vendor at HIMSS seems to be HIMSS.

They bought Healthbox, which invests in tech companies. HIMSS is indirectly and directly competing with almost every one of their members. It’s confusing. They’ve done a brilliant job.

You wrote some funny stuff about the HLTH conference. That would not have emerged if everyone was happy about what’s going on with HIMSS. There is demand because HIMSS is this incredibly successful organization that seems like it has to grow. It doesn’t know how to stay put, so it has to acquire other conferences, do partnerships, and acquire a research company or whatever HIMSS Analytics is now. I heard many vendors say they’re not really comfortable now because HIMSS was a partner — an expensive partner, but a partner — that offered value, but now it’s encroaching into their business.

Do you have any final thoughts?

Disruption is the name of the game, far more than ever. I don’t necessarily mean technology disruption, it’s more organizational. The lines are blurring and they’re going to blur even more to where entities become indistinguishable from one another. You’re seeing hospitals launching vendors. You’re seeing vendors looking at coming up with their own healthcare organizations. You’re seeing insurance companies do different intermediaries, buying up provider organizations all over the place.

We just did research around the frustrations that physicians and nurses are dealing with. We looked at key disrupter stuff, such as Amazon or others coming in, and what hospitals and clinics plan to do about it. We found out that 48 percent of healthcare organizations have active plans to acquire other healthcare orgs, get acquired, or do a merger in the next few years, which is enormous. The level of disruption we’re seeing just within provider M&A is enormous.

I would not be surprised if you start seeing massive investments in the life sciences and drug companies into provider organizations to help shrink clinical trials and to get more access to that information. You’ve seen what Intermountain is doing. We did a huge amount of research around the generic drug company they are launching. That never happened before. That’s a seismic event. I don’t think the drug companies are going to sit back and go, OK, fine, whatever. This is a signaling of all the lines blurring and everything coming together.

It’s almost like the old company store model, where the town is owned by the company that puts up the road, hires the police force, and runs the stores. I’m going to go on record as saying that you’ll have a single entity that is a drug company, a provider org, a vendor, and a payer. You’re seeing it coming together and it’s crazy. It could be awesome crazy or it could be really bad crazy, but as we’ve triangulated all of the enormous amounts of data that we’re collecting, it’s heading that direction. I don’t know when that will happen, but it will be super fun to watch.

HIStalk Interviews Jeremy Pierotti, CEO, Sansoro Health

Jeremy Pierotti is co-founder and CEO of Sansoro Health of Minneapolis, MN.

Tell me about yourself and the company.

I grew up in Madison, Wisconsin. I went to school out East, then worked in healthcare policy in Washington, DC after college. I then moved to Minnesota for graduate school. Despite promising my wife that we would be here for only two years, that was 1996, and we’ve been here in Minnesota for 22 years.

We started the company in 2014. We knew that the next generation of digital health solutions would require data liquidity. We thought we had an innovative way of providing advanced data exchange between health IT applications. I had no actual skills since I’m not a physician and I can’t code, so when I showed my partners how to move a PowerPoint slide backwards and forwards, they told me I should be CEO.

How widely are APIs being used in healthcare?

We’re seeing them adopted at an accelerating pace. We’re excited by it. I’ve always believed that in healthcare, we adopt treatment technology eagerly and deploy it pretty rapidly. New information technology has been adopted more slowly. But now we are counting on digital health solutions to help us deliver better outcomes with lower costs, higher patient satisfaction, and higher provider satisfaction. Recognition is now widespread that this will happen only with secure, seamless exchange of data between applications. In manufacturing, retail, logistics, and financial services, that’s all done through APIs. We are seeing more rapid adoption of that in healthcare, too.

Do EHR vendors make it easy for customers to integrate their products with those sold by other companies?

To some extent, yes. Most of the major EHR platforms have API or developer programs. Some are more robust than others. It depends on the business strategy of the company and the other demands that are on the company. A lot of regulatory requirements have been placed on EHR vendors over the last 10 years. That has consumed a lot of engineering and product development time within those teams.

Our goal at Sansoro is to provide a universal API so that great developers and great healthcare software companies can write to a single API standard. Then we will handle the nuances of getting the data out and putting the data back into the EMR. As a developer, you don’t have to learn the different APIs and the different integration approaches of each vendor.

I saw you your site that Emissary doesn’t update EHR tables by scripted inserts or updates, but instead uses the vendor’s back-end service to preserve their validation logic. What are the use cases for updating the EHR database and do other methods do direct database updates?

I don’t know whether other companies are doing direct table inserts. Our team is a collection of experienced health IT personnel who know how to create safe application. We’ve all been working with health IT for 20, or 30 years per person. Our approach has been to use the back-end services to make it a safer process. We also get to take advantage of the work that’s already been done by the EHR vendor in terms of the updates.

Examples of what we allow for writing data to the EHR would be discrete observations, documents, and notes. Pretty straightforward stuff, but important. In most provider systems, the EHR is the system of record, so it’s important to get key data into the EHR itself. That’s the operating system for a provider.

Our secret sauce is doing the hard work of mapping the data structures of all of the different EHRs that we support into a unified data model. That’s the holy grail. That’s why we can provide a single API in which an engineer can read data from different vendor platforms and write data back to different vendor platforms without having to know the nuances and differences between those vendor platforms.

What are the most-request API integrations and also the most-desired that aren’t yet available?

We see three common use cases across our customers and prospects.

One is pretty simple. We want to pull patient charts. We typically will have to do an extract, run a database report, or send personnel into the clinic or hospital to print out the chart or print it to a PDF. Being able to pull that chart for quality reviews, medical necessity reviews, and release of information — just being able to pull the basic patient chart — is a standard need and use for our APIs.

The second is for advanced analytics. Basic patient chart information, but with additional information. What clinic or department was this patient in when this procedure was performed? What is the provider’s background? Then combine historical information with real-time information to create a dashboard back to the provider in real time, with insight about the possible best treatment for this patient or how the patient’s condition is improving or deteriorating. Real-time analytics, pulling both historical data and data that’s up to the minute from the EHR or from other data sources to provide those exciting insights for clinicians for administrators.

The third and broadest use case involves workflow improvement. Probably 200,000 prior authorizations are submitted every day in the United States. You print out a bunch of information from the patient’s chart, fill out a prior authorization cover sheet by hand, and fax it into the payer. Then the payer has a person who adjudicates that prior authorization. Often, the the approval will be snail-mailed back to the provider. Not really up to 21st century speeds.

Workflow improvement is using our integration platform to listen for orders, determine if those orders require a prior authorization based on the patient’s insurance, and if so, grab only the data that’s needed from the chart to adjudicate that prior authorization, and then push the approval number back into the patient’s chart. All without any further human intervention. Once the provider places the order in the EHR, the rest happens automatically. That’s a great workflow improvement that saves hours for every prior authorization request.

Another great workflow improvement involves unified communications. Lots of companies provide communications tools that augment the EHR tools, whether it’s Vocera, Voalte, PatientSafe Solutions, or Spok. There’s a pretty good list of vendors that have great tool sets. Enhancing those tool sets to send those messages to the right clinician with appropriate context. Here’s a lab result for the stat order you placed, but in addition to this lab result, we’re going to include the last three results for that same lab test so you can put this result in context. Also, here are the patient’s most recent vital signs and here’s the medication list.

As a provider, you’re not getting a call from the lab with the lab result and then having to log into the EHR to find all that information manually. Instead, it’s delivered to you on your smartphone. As a clinician, that saves you a lot of time and allows you to make a decision faster about the appropriate treatment for that patient.

The FHIR standard is even further entrenched now that Apple is using it to populate Health Records. How does FHIR fit into the overall needs for interoperability?

We believe in a “FHIR and more” approach. Our integration platform, we believe, provides the most complete and comprehensive integration on the market today. But we understand that there’s a role for FHIR.

The challenge with any standards group is that it takes time to develop those standards, and that’s totally understandable. The other thing we’ve seen is that those standards are a paper-based or an electronic specification, but they don’t always get implemented in the same way by each vendor. You can look for a single FHIR resource and find that different vendors implemented it in different ways. You would need a different code base for using the same FHIR resource from one vendor to another.

We believe that FHIR has an important role and Apple has shown that you can do some interesting things with it. We’re working with customers that may be able to use FHIR for some of their needs, but they have other needs as well. We are able to provide APIs that fulfill needs that the FHIR working groups haven’t gotten to yet or that haven’t been deployed by the vendors yet.

There is no “one size fits all” solution for data exchange. We know from our growth over the last few years and from the continued interest that we have from new customers that there’s a demand for FHIR and more.

Do you have any final thoughts?

The next generation of software that will be part of the digital health revolution demands data liquidity. When you have free flow of data, it’s fascinating what you can accomplish.

The easiest analogy that I draw is to the smartphone. As a platform integrating your location and the ability to send messages, the smartphone has enabled whole categories of industries to develop. Take ride-sharing, for example. That never would have been developed.

As we start to break down the barriers among health IT applications and create the ability for them to exchange data, we’re going see a similar explosion in the creativity and innovation around health IT software. We are excited to be able to support that. For all of us, it will mean a better patient experience, lower costs, and better outcomes. That’s what we’re all trying to achieve.

HIStalk Interviews Mudit Garg, CEO, Qventus

Mudit Garg, MSEE, MBA is co-founder and CEO of Qventus of Mountain View, CA.

Tell me about yourself and the company.

Qventus is an AI platform. We work with hospitals and health systems to help them manage their day-to-day operations. I’m one of the founders and CEO of the company. My background for the last 10-11 years has been in healthcare operations, specifically in lean process improvement. I’m proud of that. I started a few technology companies and spent time at McKinsey & Company’s healthcare practice. I’m an engineer by background.

How can data and dashboards be made useful to frontline people as they are making operational decisions?

That was one of the biggest prompts to start the company. The first time I walked into a hospital, I was struck by two things. One, how the managers and caregivers did whatever it took to provide care. Second, maybe because they cared so much and because the system was dependent on them doing these heroic acts day after day, the system itself never developed. My perhaps biased view in the beginning was that data could help folks be more prepared and to require fewer of these heroic acts.

We are comfortable in the conference room thinking all we want about dashboards and information, but in the moment when people are busy, nobody has any time to do something about it. Nobody logs into a dashboard. Nobody has time to read through a graph or a report and understand it. That was the earliest insight into the way of using data that we learned from.

We started talking a lot about what was needed in 2013. We said, what makes it so hard in healthcare operations? Typically the answer came back as, half my patients are unscheduled, we don’t know how long they will stay in the hospital, and the resources they will need is unknown. Predicting would be great.

It’s an often-used buzzword, but we started using machine learning tools back in 2013. My co-founder and I both had a background in it. We started predicting.

But we learned that predictions by themselves are sometimes counterproductive. While an average manager doesn’t have time to stare at a dashboard, they also don’t have time to interpret a prediction. A nurse we worked with at that time said, I don’t have time to figure out 30 percent chance do this, 40 percent chance do that. If my GPS said it’s a 30 percent chance to take a left, 40 percent chance take a right, I would toss it out the window. I have more load than I do while I’m driving. Just make it simple.

The goal of the product is not to expose more data, but to take those things that a really good manager would do. A really good manager in an emergency department anticipates. They say, things are getting really bad, I had better have my lab manager start doing X or start prioritizing these things. I had better tell the house supervisor to prioritize some beds. By doing those things two, three, or four hours in advance, they can get ahead of the situation. But that only happens when they have a calm environment where they have the time and capacity to look ahead and solve those problems.

Our product’s goal is to take away that mental load — the data processing, the evaluation of options — and to offer a suggestion in the moment as a message, discussion, or into the workflow in some way.

Hospitals usually have some internal expert they call in when they have a problem, but are lost when that person isn’t available. It would seem that once a hospital has formalized the decision-making process, it would be easier to then enhance it.

Absolutely. An excellent manager has to look at data and make sense of it. That depends on that manager’s time. What judgment they apply depends on that manager’s experience. All those things create inconsistencies.

But in that ED example I gave, the system would be saying, it’s Monday after Thanksgiving. The patients in the waiting room are much sicker. Dr. Smith is working and he tends to he tends to order more labs, but our lab is really slow right now. Based on all of this, we will run out of capacity in the next three hours.

Then the hospital can connect those subject matter experts. Gather the lab manager, house supervisor, and charge nurse and say, “Here is something that we see. We suggest you do this.” Let them have a workforce huddle on that discussion topic and do something about it well before the problem becomes bad.

Who would typically serve as the internal champion of that kind of real-time monitoring?

The executive sponsor often ends up being someone like a chief operating officer or a chief nursing officer. But the internal champion often comes from the lean groups in the hospital. They are the ones who have seen the day-to-day problems, are trying to improve them, are trying to build a system around them, and are connected enough to the day-to-day problems. They can be good champions. Oftentimes department heads will see these challenges, such as the medical or nursing director of the ED.

Those are the internal champions who want this to become a part of the system. The executive sponsors typically are the chief operating officer or the chief nursing officer, who are day-to-day focused on these problems and who jump in to help when things don’t go well.

What is the physical and operational manifestation of how your product gets used in a average hospital?

The ideal end state of the product is that there is no physical manifestation. The ideal end state is that it is invisible, like a really good assistant or someone who is helping you have the insight. It just disappears into the background and brings in the right information at the right time. That’s why it is like virtual air traffic control.

The product has three parts. The most important one brings the insight into the moment. It tells you, this patient in room 434 is likely to get admitted. We don’t have an admit order. We probably won’t have one for the next three hours, but let’s start preparing the bed. Or, this patient is likely to leave without being seen, or that we’re going to have a bad situation with this patient. It’s processing these insights in the background and delivering them in the moment — on a Vocera device, on a secure messaging device, or whatever the right mechanism might be.

Our system provides situational awareness, a sort of mission control. It can be in the break rooms or the huddle rooms, where people can have meaningful information displayed to help them understand the situation. Some of these nudges can be shown at that same place.

The last part is being able to understand the data to see where changes need to be made. An average department will get insight in the moment when they need to do something.

As hospitals centralize and and have larger deployments, there is an interesting role to play for a centralized place. In General Stanley A. McChrystal’s book “Team of Teams,” he talks about how the traditional image of command-and-control came to fail. The military started it, but in the most recent war, we struggled with that approach. They had to rebuild it and dismantle the command-and-control approach. He talks about the importance of spreading shared consciousness throughout the frontline people who are experiencing the situation and who have the most knowledge in the moment.

Our job is to spread the context, consciousness, and best knowledge to the people in the moment who are about to make that decision. While there’s a role to play for the central manifestation in escalation and awareness, the ideal situation is one where the information and the shared consciousness is going to the front lines. That’s how our product works.

Your site allows looking up any hospital’s efficiency index as calculated from publicly available information. What metrics might improve in using your system?

Our product is in 60 or 65 hospitals. Patient flow is a big use case — in the ED, inpatient, and OR. Length of stay, as you can imagine, is a really important metric, because it’s one of the most important measures of affordability and survivability for an organization to be profitable on Medicare patients. Length of stay is a big one on the inpatient side.

Length of stay is important in the ED, but so is patient satisfaction. The number of patients who are leaving without being seen is important.

On the operating room side, they look at efficiency — how much time it takes to turn a room, how many of the rooms are being used, whether supplies are being used appropriately, and how well patients are being informed throughout.

Then we have use cases for pharmacy and outpatient clinic access. In pharmacy, how to manage the drug spend. In outpatient access, how can the health system, with the resources it has, provide patients with quick access to care?

These metrics are beneficial regardless of the payment mechanism or the healthcare system’s economic model. As an example, one hospital freed up about a million minutes of patient wait time in their ED when they deployed the system. That helps them provide care to more patients in the community with the same resources. That lowers the cost, helps the hospital, and helps the patients. Regardless of the economic model, it helps both the health system and the patient.

Where do you see the company’s future being?

I grew up in India. We have in the US healthcare system the best clinicians, some of the best equipment, some of the best therapies. What’s holding back the potential of our system is oftentimes is the ability to execute on the processes day-to-day consistently and reliably, without placing an excessive burden on the people who provide it. If we can do that, if we can create a mechanism where it doesn’t take the heroic effort to provide that consistency and reliability, we can do that across every aspect of delivery of care. Whether it’s your experience in the unit, how well informed you are, your billing, or your staffing. Whether its in the emergency centers, in urgent cares, or in outpatient clinics.

My hope is that we can provide the infrastructure to allow for consistent, reliable execution of the clinical practices we know. Managing the logistics around delivery of care so that the human connection, and the calm that we can provide to people while delivering the care, is feasible. That’s my hope. I’m hopeful that we’ll be able to play a meaningful role in bringing that about.

HIStalk Interviews Eric McDonald, CEO, DocuTap

Eric McDonald is founder and CEO of DocuTap of Sioux Falls, SD.

Tell me about yourself and the company.

My background is computer science and mathematics. I founded the company about 15 years ago. We have created an electronic medical record, practice management system, and strong business analytics solution for the on-demand space. That’s also known as the urgent care space, but it is morphing and changing into more what we call on-demand care.

What does that on-demand marketplace look like and how is it changing?

It has been known historically as the urgent care space. The term “urgent care” gives the impression that the patients’ needs are urgent. But realistically, this space is all about convenience and delivering a service to an on-demand society. Over the last half-decade to a decade, we have become more of an on-demand society. This part of healthcare has realized that and shifted its services to meet those needs. Not just in offering convenience and walk-in services, but also with the services themselves.

Historically, people thought of urgent cares as being urgent only and not offering primary care or other services. But now urgent cares are doing that. We’re seeing this shift to more of on-demand care versus urgent care. We’re seeing pediatricians and primary care docs move into this on-demand space and change their business model. Those things have led DocuTap to recognize that this is broader than just urgent care. It’s about being a technology company focused on on-demand care.

Who owns these on-demand centers? How many of them are operated by health systems?

Historically there has been a division between retail care — CVS’s MinuteClinics — and the tried-and-true urgent cares. In the urgent care world, about 25 percent are owned by health systems, Over the last half-decade, that has shifted by two to three points one way or another, but it hasn’t dramatically changed. You have seen a larger presence by corporations, larger chains like MedExpress, American Family Care, NextCare, or FastMed. Those continue to grow to take a larger percentage, probably 40 percent of the market.

The remaining urgent cares are provider owned. An ER doc decides to throw up a shingle and do it himself, and he’s maybe got one to three clinics. Or primary care docs who have changed their model to be more of an on-demand care as a hybrid between primary and urgent care.

That makes it tough to identify how many urgent cares are out there. Some clinics are primary care during the day, and then from 5:00 until 9:00 p.m., they become an “acute care urgent care.” By definition, it’s probably not an urgent care, but it really is. A number of these facilities are at times acting as an urgent care. You also have clinics or facilities that don’t offer x-rays or do laceration repairs, which are the basics that you would expect to have in urgent care.

The high-end number is about 10,000 urgent cares across the country. If you’re looking at a tried-and-true, pure-play urgent care, it’s probably 7,500 to 8,000 locations. That does not include retail clinics like MinuteClinic, which has been separated from urgent care because of their limited scope of service. They don’t have x-ray. They’re not going to manage a laceration. If you fracture something, they will not be taking care of those needs. But those would be expected in a visit to an urgent care. 

Retail clinics are limited in scope to sore throat, cough, earache, and maybe your flu shot. You got a half a dozen things that are going to be common in retail, which is different from urgent care. Having said that, I believe that will potentially shift over the next five years.

What are the technology needs of an urgent care center?

One of the challenges with a hospital-based system is that they are built to manage every specialty, every service. It’s one solution fits all, which means that it’s going to be clunkier. It’s hard to develop software that works well for every specialty. I learned early on that the best way for the company to be successful is to find one niche and be the best in it. When it comes to urgent care, it’s all about speed. How do you get patients in and out as fast as possible? When all we do is urgent care, it makes that simple.

When you start looking at the additional services that an urgent care needs — such as their revenue cycle management services, like billing services — there are some intricacies with urgent care that a hospital system is going to ignore, which impacts their revenue. We have robust data analytics, and when you’re dealing with consumers, you need to understand some of those consumer trends.

The marketing aspect plays into this. The urgent care space is consumer focused, whereas orthopedics and cardiologists aren’t. The tools that we deliver need to have a consumer play in ways that others don’t. When we talk about patient engagement, it will be very different than an oncologist or an ortho.

What kind of information exchange with other providers is typical for an urgent care center?

Interoperability, where you’re downloading information into the urgent care, is usually less important, because they’re usually acute visits such as for a sore throat or fracture. It’s less important for those providers to be aware of what’s going on. What’s important is that we get the information from this acute visit back into the health system or the mother ship. The most common interface is pushing data from our software back into systems like Epic or Cerner.

Having said that, there are situations where the hospital or health system is willing to let us pull that down as a patient walks in the door, but we wouldn’t ever keep those in sync. We would wait for a patient to walk in and do it on an on-demand basis.

How are urgent cares broadening their services?

One of the biggest buzzwords and the most important item within urgent care is patient experience. At the very onset, being able to remotely register from your phone, put your name in the queue, and wait at home or wherever you need to be instead of in the waiting room. The system will automatically text you when it’s your turn to be seen. You essentially walk right on back. Being able to remotely register and take a picture of your insurance card and driver’s license does it all for you and enhances that experience.

Our clients are embracing those items to enhance the experience. When that patient walks in, they’re going to be able to get in and out of that clinic in probably 40-50 minutes, under an hour for sure. The services that are rendered can be anything from acute-related items — sore throat, earaches, fractures – to proactive preventative items related to their care. Diabetic care, an annual physical, and “primary care lite” services. You’re going to see more moms that are using urgent cares as their pediatricians. Whether it’s pediatric care, primary care lite, or truly urgent fracture-related or lacerations stuff, you’ll see all of those happening within urgent cares.

How do you see the market and your company changing in the next 3-5 years?

We have to be very nimble. We have to assess our clients’ needs every year and shift as quickly as we can and stay ahead of them. That is hard to do because they are also quick and nimble. Many of our clients are backed by venture capital or private equity firms, which means that they’re growing quickly. They’re going to change their business models quickly if needed. It’s a tough niche to be in because it’s constantly changing and it’s changing quickly.

Do you have any final thoughts?

We got lucky. Sometimes people think that it’s crystal ball-ish, but in reality, we picked an amazing niche within healthcare. It will be fun to see how the urgent care space continues to evolve and changes how healthcare is delivered. It will push other specialties to be more consumer focused and to pay more attention to an enhanced patient experience.

Five or 10 years from now, we will look back as a healthcare industry and see that the urgent care space — which will be referenced as on-demand care — has changed how providers interact with their patients. There will be a higher expectation to offer an enhanced patient experience. Patients will have more control than they have had historically. I couldn’t be more proud of the niche we’re in, what it’s doing for healthcare, and DocuTap’s role in it.

HIStalk Interviews Dan Burton, CEO, Health Catalyst

Dan Burton is CEO of Health Catalyst of Salt Lake City, UT.

Tell me about yourself and the company.

Health Catalyst was founded by a couple of folks from Intermountain Healthcare. We provide a data platform that’s really good at aggregating data from lots of different sources. We analyze the data and we have a layer of analytics apps that pinpoints opportunities for improvement clinically, financially, or operationally. Then we provide clinical, financial, and operational expertise to go after those opportunities.

What led to the Medicity acquisition and what synergy do you expect to see?

We have deep roots and connections to Medicity going back to the company’s founding. Former Medicity President Brent Dover joined Health Catalyst a number of years ago, as did the former head of sales and other management team members. Like us, they are headquartered in Salt Lake City.

What Medicity does is complementary to what we do. The data asset that we have amassed is rich, especially on the acute care side, with about 100 million patient records. But it’s lighter than we would like on the ambulatory side, which is Medicity’s strength. They have about 75 million patient records, largely coming through the ambulatory space. Adding that data asset and the transactional capabilities of being effective in moving data to lots of different places felt like an important complement to the ability of our platform to meet the needs of our clients.

From a mission orientation perspective, the folks at Medicity are focused on using data to improve outcomes. That’s why we exist. We felt like from a data asset perspective and from a mission perspective, it lined up well.

How much of the information that a provider organization needs to meet today’s challenges exists outside their EHR?

The province of Alberta, Canada did a study about two years ago to try to answer that question. Their conclusion was that to effectively run population health for their province, only about 8 percent of the relevant data existed in the EHR. We think that’s about right, and our experience with our clients is similar. The EHR is an important source of data, but we have many clients that need to pull information from 50 or 100 additional sources. We also have clients that have four or five EHRs whose information needs to be brought together into a single source of truth.

What is the level of provider analytics maturity and what are the higher achievers accomplishing that the lower achievers are not?

We are still in the very early innings of analytics prowess or analytics maturity. Even our most advanced clients are still facing some of the same challenges that the rest of the client base that we work with seems to face.

One is a talent shortage. It’s hard to find great data scientists and great analysts in competing with Silicon Valley, with Google, Microsoft, Amazon, and many other tech companies. We’ve seen a real gap in our clients being able to staff the kind of analytics talent that they would like to have. That’s one of the reasons that our analytics expertise, our services offering, has exploded over the last three years. We’ve been fortunate to compete pretty well for talent against Silicon Valley, so we can bring that talent to bear.

It’s not surprising that our industry is early in developing analytics capabilities. It has taken us a long time to transition from paper to electronic data. Without electronic data, there was nothing to analyze. Since we’re early relative to other industries in that transition, it follows pretty naturally that we would be early in developing significant analytics prowess.

The best conference speaker I’ve heard was Billy Beane from the Oakland Athletics at your Healthcare Analytics Summit a few years back, who in “Moneyball” used analytics rigor to find market inefficiencies that could be exploited by an underfunded baseball team. Do we have a Billy Beane-like provider who is taking the culture in a new direction in ways that everybody else is missing?

The analogy is important, including the cultural change required and the doubts he had to overcome from within his organization. We experience a lot of the same in healthcare. But we see some of our most innovative health systems choosing to face the truth from the data, to realize that they have significant inefficiency and significant variation. There’s a lot of vulnerability, for example, in facing patient injury elements, but that’s a necessary step to transform and dramatically improve.

We are also seeing an interesting uptick in innovative openness to being data-driven, coming maybe from outside of the traditional provider segment of the healthcare ecosystem. I think that pattern will continue for a decade or more, where you will see innovative employers thinking differently about how they utilize the data they can collect on the health of the population that they care about most, which is their employees and their loved ones.

We think data and analytics have an important role to play through many different vectors, including the traditional delivery mechanisms, but it will play a role in non-traditional ways, too.

Health Catalyst spent a lot of money to create the Data Operating System. What does it offer that a data warehouse doesn’t?

A lot of value can still be realized from the concepts that were breakthrough for us a decade ago, like a late-binding data architecture. In many ways, that has become a more common practice in healthcare, which is great for the entire industry since it still offers value.

What we saw a number of years ago — and I’ll credit Dale Sanders, our head of technology, for seeing this before many others — was that there would be an explosion in the number of potentially relevant data sources. Specific use cases exist where having access to data sources such as genomics and social determinants of health data leads to much better decisions and dramatically improved outcomes, both financially and clinically.

That explosion in potentially relevant data sources requires a much more scalable data platform. A traditional, on-premise data platform using 10-year-old technology just can’t handle that level of scale. We feel that the right combination is a more modern technology stack that takes advantage of the best Silicon Valley thinking coupled with deep healthcare domain expertise.

We made a bet a few years ago to invest $200 million in this next-generation Data Operating System data platform to support that need to scale. We’re early in enabling our clients to realize the return on that investment, but we’re not super early. We’re seeing more and more interesting use cases where you bring in non-traditional data sources and you have compute power through an Azure-based, cloud-based, scalable technology infrastructure that you just couldn’t achieve in the old model.

Analytics is often applied to address clinical quality and outcomes, but health system cost pressure is increasing. What data tools do organizations use to manage costs?

A cost focus and a precise ability to measure cost at a granular level will become a central focus over the next five years. The low-cost providers will be the survivors, and those who are going to be low cost have to first understand their costs.

There are real challenges, partly because we are not systematically collecting all the data needed to answer the question of, what are my precise costs on a given day, with a given provider, in a given location, with a given procedure? There is data that needs to be collected at a very specific level, but that isn’t being collected today.

We’ve spent a good deal of time over the last five years developing a Pareto version of precise activity-based costing for healthcare, where you get 80 percent of the precision benefit with about 20 percent of the effort. It’s hard to do precision-based costing all the way. It’s incredibly expensive to collect all of that data in every case. We hypothesize an 80/20 rule that we’re finding actually exists. We co-developed this with UPMC.

My opinion is that five years from now, every surviving health system will be collecting all of that data and analyzing it very carefully to identify the hundreds and even thousands of cost-savings opportunities. The health systems that execute most flawlessly against those improvement opportunities will be the health systems that thrive and survive. Those that don’t pay attention are very much at risk.

Health Catalyst is on everybody’s list of health IT companies that are expected to go public next. I know you can’t talk about that specifically, but what does it take to prepare a company for growth?

It’s very hard to do. That’s probably appropriate. To become a successful publicly-traded company requires that size and scale be in place and to have predictability to the business model and the revenue. There needs to be stability in the client base and a significant Net Promoter Score or satisfaction level. In our opinion, there needs to be a culture that is built to last and team members who are deeply engaged in the company’s mission and the success of a client.

That’s a model that we have tried to follow in the event of a scenario where our board decides that going public would be the right path for our company to pursue. We have obviously chosen to raise capital from investors, so we understand that those investors eventually need liquidity and a return on their investment. One way that can happen is through the public markets.

One element that the leadership team really likes is the opportunity to remain as Health Catalyst for the long haul. That’s very important to us, and an appealing element of the public company path.

In any regard, preparing to be a successful public company overlaps significantly with preparing to be a scalable, independent, sustainable company as well. For a number of years, we’ve been trying to prepare ourselves to be the latter, and by preparing for the latter, you are also preparing for the former.

Do you have any final thoughts?:

It’s an exciting time to be in healthcare. It’s a time of transition, which can evoke feelings of nervousness and anxiety for good reason. But it also represents a real opportunity to think about things differently. Data and analytics provide us with visibility we’ve never had about what we should change and what we should do differently so we can see the industry transform. It’s a great thing to be a part of. It’s a meaningful activity to get up in the morning and work hard to fulfill.

HIStalk Interviews John Talaga, EVP/GM, OnPlan Health

John Talaga is co-founder and EVP/GM of OnPlan Health of Bannockburn, IL.

Tell me about yourself and the company.

I’m a co-founder of OnPlan Holdings. I co-founded HealthCom Partners, which was acquired by McKesson in 2006. We developed introduced PatientCompass, which was the first online account management tool for hospitals.

OnPlan Health addresses the market shift to high-deductible health plans. Co-founder and CTO David King and I created OnPlan to help hospitals settle balances with patients with high out-of-pocket costs. The business also supports and serves higher education, which has similar challenges to healthcare.

Premiums and deductibles are rising and few people in America have enough savings set aside for even modest unexpected expenses. What’s it like on the front line of health systems?

The shift has hit the boardroom. Over the last couple of years, the level of executive presence on the rev cycle side has increased. You have VPs of revenue cycle and chief revenue officers that you never had in the past. When you hear the term “third payer” — the patient being the new payer — it’s real. Hospitals are having to deal with so much of the self-pay that it’s as much as commercial and Blue Cross, in many cases.

The front lines are asking, what do we do about it? A lot of technology has poured in and has been invested in. Companies are offering automated payment plan functionality, front-end collection at point of service, and scheduling. It’s a form of retail-ization — trying to collect as much as they can up front, but also trying to automate and reduce the cost that it takes to collect on the back end.

You have this new focus of, “The old way of doing things is no longer good enough. We don’t have the staff to be able to do that.” Companies are turning to outsourcing early outs. Some are turning towards financing. But those solutions are expensive and they disintermediate the patient, so they are looking at technology that allows them to work on their own to prevent having to place accounts with those options.

Is the financial conversation that might precede the medical conversation awkward for both the patient and the provider?

It’s a very different environment when you talk about the doctor’s office versus the health system and the hospital. Where my company spends the most time is in the health system, where physicians are part of the health system and are connected to a hospital with the higher cost.

In the doctor’s office environment, there still is an expectation that you’re going to pay for your service. We know what it costs, typically. There’s nothing emergent that comes from that visit. They will bill on the back end and typically patients have the money to pay that.

It’s the surprising bills that come with services that cost more, typically coming from a service that involves the hospital. The patient doesn’t have budget and sometime doesn’t even realize what they signed up for — what their employer provided them for a health plan — until the bill comes. They wonder, why am I getting a bill for $2,500 when I have insurance? Reality sinks in.

It’s this surprise factor that’s difficult on the financial side. Setting those expectations has been a big priority of hospitals. We’re going to do an estimate for you and this is approximately what you’ll owe. They try to collect as much as they can up front, but that expectation carries through after adjudication of the balance.

Is the approach the same for patients who are unable to pay versus those who are simply unwilling to pay?

The expectation is that 80 percent of the patients are willing to pay. They just have to understand what it is they owe. Then they have to have the means.

The introduction of revenue cycle analytics has been positive. Though analytics can be used from a propensity-to-pay perspective to identify the patient’s ability to pay, but also to determine how how much means they have to cover a specific balance. Analytics isn’t just directional. It’s getting to the point where, this patient owes this balance, they have this much left on the deductible, so here’s what they can afford.

That technology is done on the front end. But now more hospitals are also doing it for self -pay as well. How should we approach this patient? What should we offer them to pay as opposed to just asking for the full balance knowing that they’re probably not going to be able to pay it and they may end up in collections? Propensity-to-pay has evolved into revenue cycle analytics.

Those unwilling to pay is going be a difficult one to solve. Those are probably for the collection agencies, simply because you’ve got a different problem than somebody who just doesn’t have the means.

What do health systems do in that case where someone hasn’t made progress on their previous payment plan obligation?

The analytics only go so far. It gives you the profile of this patient at the moment. Hospitals are now taking it to the next level to automate processes and policies to avoid the traditional one-on-one negotiation. In the past, payment plans were set up on a phone call. Somebody who needs help seeks it out and agrees to a payment arrangement.

Now companies are using analytics to provide a payment plan offer proactively. We give them an installment offer that they’re able to pay. And if they’re able to pay that, let’s give them the ability to self-activate without having to call us. That could be by going online or mobile to activate the plan or even writing a check based on what they’re willing to do a payment plan for.

If they take the call center mostly out of it, like 70 percent of those payment plans that are activated, the next step is whether the patient stays on that plan. The rules are in place. You have to make your payments. You can’t miss two payments or you’re going be terminated from your plan. Those patients will be treated differently the next time they come in for service.

It’s working the analytics visibility to the staff, putting it into automation so that they don’t have to do hand-to-hand combat, if you will. But then also being able to utilize what happened when the patient presents themselves back in the office.

Is discounting the initial price for someone who has to pay cash a significant factor in creating the payment plan?

For revenue cycle leaders, the goal is still to get someone to pay in full. The goal isn’t to get them on a plan. But for a segment of patients, that’s the only way they’ll be able to pay. The discounting usually comes in after uninsured discounting, when a patient has a balance after insurance or they owe a patient responsibility. They’re driving incentives such as, you can get on this payment plan and we’re willing to do this for you. But if you pay us in full in the next 30 days, as a prompt pay discount, we’ll take 5 or 10 percent off.

What they’re doing instead is driving discount incentives, mainly post-service, to try and get them to pay off their balance as opposed to getting on a plan. The plan itself should be enough of incentive to pay over a time that makes sense for them.

On the front end, if the analytics are there, they will offer some deeper discounting to be able to get them to pay in full. But again, what you’re seeing is payment plans being set up off the estimates. It’s easier to say, you owe $1,000. Do you want to pay $1,000, or do you want to pay a portion of it? How about we set you up on a plan for $100 a month? Then when your insurance pays, we will adjust your balance and your $100 a month will continue until the end of the term. It’s easier for a consumer to accept that as opposed to just paying some dollars towards a cost they don’t know yet.

I assume it’s not in the best interest of either the provider or the patient to turn a bill over to collections,.

That comes across loud and clear in terms our business and how we position ourselves to serve hospitals. They’re trying to reduce bad debt and the amount of placements that they send to bad debt collections, But also even to their pre-collect, early out vendors. Even though early out vendors are first party, you have hospitals that are turning them over at Day One.

The big concern is, if I’m using this outsource vendor, they’re collecting and I’m paying for balances that maybe the patient would have automatically paid with a payment plan. If I can get some automation in place, then maybe I only have to place accounts that are expensive to early out at a later time. If I’m placing accounts at Day 60 and I’m trying to collect on my own internally before Day 60, then how can I collect as many as I can by settling on payment plans before I have to turn them over to a collections agency?

The whole idea of turning patients over to a collections agency is perceived negatively. They’re trying to keep engagement and patient loyalty so they will come back to the health system. To do that, they want to have that direct interaction with them without having a collection agency asking them to pay their bill.

Do you have any final thoughts?

The revenue cycle leaders are trying to reduce the pain points of increased self pay, so there’s a resurgence of patient financing. You hear about these recourse options for essentially getting a loan to pay off their bills. In terms of financing, the revenue cycle leaders are debating whether to sell their receivables. Where it’s falling is that if they can get more of the functionality and tools with analytics and automation in their system to do it themselves, with the reserves they’re willing to fund for these balances, then they only use financing on the back end for those balances that need long terms. That is the direction that is becoming more acceptable with these leaders, as opposed to one or the other.

HIStalk Interviews Jeremy Schwach, CEO, Bluetree Network

Jeremy Schwach is CEO of Bluetree Network of Madison, WI.

Tell me about yourself and the company.

I’m Minneapolis-St. Paul-born, so I’ve got those Midwest roots. I was born to an accountant and a microbiologist, and unfortunately, I didn’t get either of those skills, so I was forced into business. I found myself at UW, where I started my first company out of my dorm room. It was a bus company. That went pretty well and whetted my palate for the entrepreneurship journey. It didn’t really run in the family, but I had a very good support structure. I had supporting parents and they said failure was OK, which pushed me out of my comfort zone.

I got the first company running. Then I found this weird little software company out of Verona right out of UW. After a brief stint living in South Africa, I moved back to Wisconsin and started my career at Epic. I was there for about six years. After living out my non-compete at a large health system and understanding how hard it is to deliver healthcare, I jumped into this next entrepreneurial thing with co-founders and started Bluetree.

We today are about 250 or so people. We’re not that great at marketing, so people don’t know this, but we’re about 60 percent staff augmentation, specifically in the Epic space. But about 40 percent of what we do is what we call solutions, which is more around strategy. Clients come to us to ask, “We’ve got all this data coming into Epic. Can you help us make sense of it and maybe pull payer data in?” Or, “We know we can do a lot more and make our physicians more productive. Can you guys help us do that?”

Where we’re a little bit different is that we focus on Epic because we know it so well. We like to come in and help with figuring out what the plan is, the strategy, but then we get our teeth into actually getting it done. We always say that ultimately we want our result to be that we delivered something tangible that worked well for our client.

How do you differentiate yourself in that market where there are a lot of competitors?

We didn’t actually want to be a consulting company. We raised a little bit of friends and family. The problem we were trying to solve was that having worked at Epic– and about 40 percent to 50 percent of us came from Epic — we looked out in the wild and saw all of these different consultants, but there weren’t a lot of great consultants.

We thought technology could solve that, so we started as a matchmaking platform. Luckily I failed many times in life, so I knew after that didn’t work, there was still a path forward. We were trying to solve this quality problem. We built this matchmaking platform and went out to clients and said, “You can find the specific skill sets within Epic that you need. Everybody’s going to get reviewed Amazon ranking style. Pretty soon you’ll start to see who all the great people are.”

Potential clients said, “You kids know nothing. It’s a good idea. The transparency and quality problem is a real problem for us. But we’re not going to social network our way to consultants. Sometimes we need 10 people. If things are going great, we want to just pick up the phone and call you. For all those reasons, we’re not going to use your silly platform. But here’s all our needs.”

That was 2013. We learned pretty early on that the market wasn’t ready for a tech platform, but that this consulting thing could probably work. We just said, if we’re going do this like everybody else, let’s stick to our guns on the core quality piece in this area that we know really well called Epic. That was the differentiator.

With some dumb luck on timing, we grew really quickly post the big implementation boom, after everybody had Epic live and had to figure out, what do I do with this super powerful machine now that it’s up and running? Clients started saying not just, “Do you have a strong hospital billing person?” but also, “Our AR over 90 is spiking,” or, “We’ve got to figure out how to build managed care dashboards.” The questions started to change. That was the impetus for the shift to a more outcome-based strategy or solutions.

Half our company comes from the provider space, knows the business of healthcare, knows what it’s like working in a health system. Half of us come from Epic, so we know this tool really well and we’ll be able to maximize the power of it. That’s how we differentiate and have been able to continue growing over the last six years.

Sometimes hospitals only care about getting someone who holds a specific certification. How much of what you learned from your original iteration of letting customers rate their consultants did you apply to the way that you hire and place consultants at Bluetree?

It’s the big reason that we stuck around in the Epic space. We constantly have questions about, should we help Cerner clients or Meditech clients? What we found is we know the Epic space so well that we can use our network and feedback from our clients to help differentiate who’s the rock star. They say in service work that a great person is 10 times better than the median. That is precisely the reason we’ve stayed focused in the Epic niche. We feel like we’re able to differentiate that quality piece.

How has the Epic consulting market changed in the past two or three years?

Again, a lot of life is just dumb luck. Not a lot of people know this, but the only reason I picked Epic out of UW is because they were going to pay me $1,000 extra over Maytag. I very easily could be servicing Home Depots right now.

In terms of our trajectory, we found our footing in 2013 and 2014. There was still a lot of implementations, but you had some really big players that specialized in implementations. Therefore, a lot of our early clients had Epic live and were figuring out what to do next. We got a little bit lucky in that we were on the end of that wave, perhaps the downward slope, as optimization, the next level wave, took off. All of our growth is in what we call solutions. It’s managed services. It’s everybody trying to figure out, how do we do this thing much more cost effectively?

Epic is a really robust, big system. Five years ago, we weren’t seeing that a lot of clients were ready to outsource a lot of that. Now I think the opposite is happening. We see that growing pretty quickly. Then it’s all this stuff, all the buzzwords you read about. We’re on the ground working with clients to figure out, how do we make physicians — happier is not a great word — but how do we ensure that they’re able to get their work done the way that they perceive that they used to? What we’re finding on that particular front is that it’s not about squeezing in extra patients. Physicians are documenting and then going home and having dinner with their kids and then documenting again before they go to sleep. A lot of what we’re doing now is, we might not be able to squeeze in extra patients, but we can help you get more efficient. You’ve got this amazing system that frankly you’re probably not using to the best of its abilities. It’s those types of conversations that now make up the majority of what we’re doing.

What interesting things are you seeing clients do with the wealth of Epic data they’re suddenly sitting on?

Man, I wish I had a lot of cool stories. A lot of what we’re seeing is more foundational. You go live with Epic. You have a massive amount of data. As users start to get comfortable with the data, they start to ask the right questions. From there, you have to figure out, what’s the strategy so that we can iterate fast enough? A lot of our work is around that basic foundation. A lot of clients have data warehouses. They also have Caboodle. Many of them have visualization tools. A lot of our work is around the strategy of, how do we make sense of all of these tools? How do we help you iterate faster?

I don’t know if this is cool yet. I think the outcomes are going to be really cool, but even getting payer data back into the warehouses, back into Epic, is a relatively new thing. We’re seeing more and more clients start to work with payers who, perhaps not overly surprisingly, don’t all want to give up their claims data. Part of the work is figuring out how to work with the payer to get the data back, and then once it’s in Epic, that’s the opportunity to start using it. We’re seeing a lot of foundational type of stuff happening.

What are the most impactful things that you learned from working at Epic that affect how you do business now with your own company?

This perhaps isn’t controversial, but I cannot think of a place I’d rather start than Epic. We’ve grown from zero to well over 250 employees in five and a half years. I truly believe that without learning a lot of those fundamental lessons that I learned and we learned at Epic, I don’t think we would have been able to do it.

First and foremost, Epic does such a good job training their people. It’s not just training, but it’s giving people opportunity. One of the best technical people I worked with at Epic was a philosophy major. Epic just found a smart person and said, “We can use this raw talent and mold it.” I really respect that philosophy. We see some of our clients taking a similar philosophy — hire a lot of really smart people, regardless of whether they’re healthcare or not, and then introduce them to healthcare and train them on their processes and allow them to fail and learn. Epic was just so good at that.

I think the other thing they did pretty well is that the talent bar stayed high at Epic. That’s probably easy when you’re a small company, but it gets progressively harder as you grow. You have to be laser focused and deliberate about keeping that quality bar high. Epic used to say, get those A players. Get the best people. Those best people will figure anything out, regardless of the problem. Then those A players will find other A players, and you’ll be able to scale that way. You’re going to make mistakes. You’re going to hire B’s, and that is OK, but you have to fix the mistake. You have to grow those people, Because if you don’t, those B players make mistakes and hire C’s, the C’s hire other C’s, and pretty soon the A’s are looking over at the C’s and saying, “Why am I doing all this work?” and they leave.

Epic did such a good job training and was focused on giving people opportunity. Then they did a fabulous job, mostly through culture, of keeping the strong people there. I was there for about six years and it was just a remarkable experience.

Do you have any final thoughts?

Can I use this time to promote something unrelated? I don’t get a lot of opportunities. There’s a great non-profit I’m associated with called Year Up. They’re a workforce development program in about 15 cities. They’re trying to bridge the opportunity divide. There’s a lot of really talented urban, young adults who have raw talent and are looking for work. There’s a lot of companies with open, entry-level positions. They do a good job facilitating those connections. It’s about a year-long program where they’re taking these talented young adults and training them up to start a career in corporate America. There’s a big focus on finance and software development in certain regions, and there’s a push for healthcare. Northwell in New York uses Year Up interns and one of the Sutter hospitals uses them. There’s just an amazing opportunity to get really smart young people trained up in healthcare and do good while doing it.

If I get to reach any health systems that are interested, they should feel free to contact Year Up directly or reach out to me and I’ll connect them.

HIStalk Interviews John Birkmeyer, MD, Chief Clinical Officer, Sound Physicians

John Birkmeyer, MD is chief clinical officer of Sound Physicians of Tacoma, WA.

Tell me about yourself and the company.

I’m a general surgeon and a health services researcher by training. I spent most of my scholarly life focusing on the phenomenon of variation in surgical performance and outcomes.

I am chief clinical officer of Sound Physicians, which is a national physician practice focusing on hospital-based position practices. I also serve on the advisory board for Caresyntax, which is a technology company that specializes in big data integration and offers a variety of tools for helping improve the performance of operating surgeons.

What causes surgical variation how much does it affect outcomes?

If you think about it, there’s no reason to be surprised that surgeons would vary in their performance, skill, and ultimately outcomes any more than tennis players, golfers, or musicians. It’s a pretty fine skill. Surgeons just vary in the degree to which they ultimately master it.

If you look at the scientific literature, depending on what procedure and what specialty you’re talking about, there is, give or take, a three- to five-fold spread in surgeon outcomes and costs. At the end of the day, that has enormous implications for both public health and healthcare costs, particularly as you consider that 40 or 50 million surgical procedures get done in the US alone every year. There’s a very deep and complex body of research that aims to understand what drives observed variation in surgeon outcomes.

Part of it, depending on the procedure, is driven by environmental factors and attributes of the hospital at which a surgeon is practicing. Certainly there’s aspects of the team — the skill and competence of anesthesia and critical care — that ultimately drive how well a surgeon’s patients do. However, my own work, as well as that of others, has shown that a lot of that variation is driven by the intrinsic ability of the operating surgeon. While technical skill and proficiency isn’t the only type of surgeon attribute that varies, it’s the most important and the most obvious.

My hospital experience is that surgeons are fiercely autonomous and aren’t all that interested in having others get involved in their work. How much of the issue of variation is based on surgeon psychology?

There’s no doubt that there’s a stereotype associated with surgeons, which is partly true and partly reinforced by how important surgeons are to the economics and to the smooth running of any hospital. I think part of what you’re describing about surgeons is something that is not specific to surgeons, but it’s a paradigm that’s applies to all physicians. There’s this general assumption that if you’re smart and if you do four,  five, or up to seven years of post-medical school training, then you’re good to go. You’re at the flat part of the curve with regards to your abilities in your mastery of the craft.

Given how complex surgery is, and even given the scientific literature, it’s clear that surgeons continue on the learning curve for many, many years after they finish their training. My belief is that surgeons could be so much better than they are if they adapted a philosophy of deliberate practice and continuous learning and if they increasingly started to harness some of the empirical tools that are being brought to bear in many other disciplines.

Your video study of procedures found that some surgeons have easily observed poor technique, yet no surgeon thinks they are a less-than-average performer. How much of the surgical process is based on defensible, concrete standards?

Perhaps it’s not a surprise, given the stereotype associated with surgeons, that most surgeons think they’re above average. There’s no doubt that part of what made my own research feasible was the willingness of surgeons to supply videos of themselves operating, probably under the assumption that their peers could learn from watching them. We all know that it’s just a fact that in any sample, that half of all the members will be average or below average.

The things that surprised me about that particular study in The New England Journal of Medicine were, number one, just how stark the differences were in both technique and skill. Number two, it was amazing to me just how immediately obvious those variations in skill were. Not just to professional observers — surgeons watching each other operate — but if you show those 20 videos to lay observers who don’t know anything about surgery, they can almost just as easily segregate the best from the worst. In fact, there’s great research that’s recently been published showing that crowdsourcing by lay observers gets you basically to the same ratings as professional ratings by surgeon peers. Finally, I was really shocked by just how powerfully related surgeon skill was to various outcomes that are relevant either to patient outcomes or to cost.

As I watch all of those videos, as somebody who’s himself a practicing bariatric surgeon, there was not a single surgeon whose technique was outside of the standard of care. Nobody was violating accepted professional standards for how to do that procedure. It just speaks to the fact that our standards are fairly loosey goosey, to the extent that we have a very imprecise estimate of what’s optimal technique and what’s not. It also speaks to the fact that it’s not so much the technique that a surgeon deploys as it is the fidelity or the precision in the skill by which that technique is deployed.

The surgeons who contributed their videos were self-selected, which probably means that you were not seeing the worst surgeons in the US. Beyond observing voluntarily donated videos, what data elements or analysis would allow assessment of all surgeons?

You’re absolutely right that in my study, that was a self-selected group of surgeons. But it was also a group surgeons that had the luxury of being able to choose their best case. Nobody sent me videotapes of cases gone sour. They basically sent me what they thought was typical in sometimes their best work. Imagine what it would look like if it was just a random sample of everybody in all cases.

I’m sure that, for many procedures, if you really did have the universe and the entire library of all of their cases, that there’s a significant minority of surgeons that half the peers would say, “This person should not be operating or should not be doing procedures as complex as this.”

The second part of your question was about what’s a scalable strategy for vetting and providing feedback to all surgeons, not just this highly selected group of volunteers. That’s what’s attractive to me about technology approaches. Such a high percentage of surgical procedures these days, particularly those that are most complex and are the highest stakes from the perspective of patients, are done videoscopically, which means that there’s a real-time video recording of what’s going on in the surgical field and at the tips of the surgeon’s instruments.

What’s really exciting to me is to leverage all of that rich data infrastructure and convert the real-time video information to digital, empirical information that gives surgeons real-time feedback about how they’re doing relative to techniques and maneuvers that ultimately lead to the best outcomes. Google and Uber may ultimately get us to a self-driving car — with all of the externalities, in all of the craziness that has to be accounted for — and can help the car or the driver make better decisions. 

I don’t think it’s a huge stretch, given how reproducible certain types of procedures are, that machine learning based on digital video-based information could do the same thing. With regard to not only providing digital analysis and giving a surgeon a report card about how well he or she did with that case that just ended, but also giving real-time information that could help those procedures be better in the first place. Like the angle of attack, how much random motion there is, the amount of force that’s being applied either to the instrument or to the tissue. All of these things that we measured holistically and by human judgment in my study could, in my belief, very readily be replicated in a much more powerful way using the data technology.

Every surgeon wants to do a good job, but nobody likes to judge or be judged by peers. Doctors are competitive enough to want their numbers to look good. Will the procedure data be acted on through self-policing or will hospitals need to get involved?

I think the answer is both. At the end of the day, there needs to be more rigorous procedures for doing two things. One, identifying and policing that small subset of surgeons that really should not be operating, or at least should be operating with a less-complex scope of practice. Number two, finding ways to make all surgeons better. In other words, not just worrying about the bad apples on one tail of the distribution, but finding a way to shift that whole performance curve to the right and make everybody better via the data-informed practice.

With regards to self-policing, there’s a whole bunch of discussion underway about the role of the American Board of Surgery and similar boards for using that as a part of the board certification. Hospitals are increasingly insisting that new surgeons submit videotapes of themselves operating as part of their hospital credentialing process. Those are all fairly important but low-tech approaches to identifying that small number of surgeons who just are not ready for prime time.

What’s most exciting to me is how you make everybody better. Certainly there are practical and sociological barriers to making everybody better purely via a paradigm of person-to-person coaching. Not just because that’s expensive, because surgeon time is expensive, but also because a lot of surgeons just are reluctant to be taught or coached by their peers. They think they’re done and it’s an admission of inferiority to accept that kind of coaching when you’re well-established in your practice.

That’s what’s so appealing to me about the more anonymous, confidential, data-driven performance feedback that I believe is eminently feasible now with both robotic surgery and other types of videoscopic surgery. There still is a lot of work to be done in terms of exactly what that feedback would look like and how to get that feedback in real time to surgeons as they’re operating in a way that does not distract them from what they’re doing, but improves what they’re doing. I think it’s really exciting. I don’t think that it’s 15 years from now. I think we’re getting very close.

As an informaticist, could the expanded information about how a patient’s surgery was performed be connected to other existing data to look at whether the surgical technique contributed to patient outcomes?

If I were chunking this up into three informatics needs, all of which need to be present to some degree to get to the outcome that I was describing earlier, I’d say that number one is there needs to be continued advances in how we collate, curate, and link very heterogeneous, very complicated sources of data that ultimately allow us to link empirical information from the procedure itself to the late outcomes of surgery. Most of which don’t occur during the operating room — they occur the next day or the next week or the next month. If you can’t link measurable aspects of skill in the procedure itself to outcomes later, you just simply don’t have all the data that you’d need for that system to learn.

Once that data platform is in place, there need to be both statistical and probably machine learning-based tools that allow you to identify a subset of high-leverage maneuvers or skills that the surgeon is deploying and to be able to measure them and link them to outcomes in the most parsimonious way.

Obviously there’s a thousand potential micro processes that a sophisticated algorithm could pick up during the course of an operation. Machine learning could help us identify the most important four, five, or six levers and avoid information saturation with the surgeon by focusing on just a small number of levers to get better. It’s much the same way when you take a golf lesson. It’s generally a bad idea for the pro to tell you 14 different things that you should be doing different on your golf swing. You typically do it one or two changes at a time. I think there’s some aspects of that muscle memory in operative surgery as well.

Finally, there is a technology need to not only identify what optimal practices are, but ultimately to get them in the hands of the surgeon in real time, allowing them to modify the course of the procedure as it is being performed. As I think about it, there’s really two ways that that could happen. One way is simply a dashboard in the corner that blinks red when something is sub-optimal and allows the surgeon to self-correct. The second option would be something akin to autopilot, whereby for certain parts of the procedure, you’re letting the technology take over and letting the surgeon guide it and override it exactly as if you’re flying a plane or you’re driving a self-driving car of the future.

What is the prevalence of robotically-assisted devices in the OR and how is that field progressing?

That field is progressing really, really fast. The vast majority of community hospitals, at least those with at least 100 beds, have at least one robot. At the hospital that I was most recently associated with before I joined Sound Physicians, there were four robots that were used virtually around the clock in thoracic surgery, general surgery, urology, and OB-Gyn. It’s really been staggering to see how quickly robotic surgery has started to take over many of the biggest surgical disciplines.

There’s lots of reasons why that is. While we’re collectively on this big learning curve, it also creates this huge opportunity for digital technology to not only make it feasible to conduct more operations through minimally invasive techniques, but also to create this new opportunity for us to do those procedures better than we had in the past.

What steps would you take if you were personally facing a significant surgery?

Unfortunately, surgical patients have very limited publicly available information on which to choose a surgeon. I’m hoping that that may change sometime in the future as a corollary to what we’ve been talking about.

Right now, if I needed some procedure, I would stick with the tried and true techniques for identifying best surgeons. The first is that for whatever type of procedure I need — particularly if it’s one that is complex and/or high-risk — I would learn which surgeon had the highest volumes and specialized in those types of procedures. Both volume and specialization are hugely correlated with better outcomes with most procedures.

Second, I would ask my primary care physician about the reputations of surgeons for the sub-specialties that attach to the procedure I needed. There’s scientific evidence showing that traditional things like the surgeon’s pedigree — in terms of medical school and training — are very poorly correlated with outcomes. Hospitals are small enough places that a physician’s reputation is usually much better than not having that information at all. Even though it’s imperfect, it certainly will help you surface and help you avoid that small number of surgeons that are known to have poor skill or poor outcomes.