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HIStalk Interviews Nora Lissy, Director of Healthcare, Dimensional Insight

February 7, 2019 Interviews No Comments

Nora Lissy, RN, MBA is director of healthcare for Dimensional Insight of Burlington, MA.

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Tell me about yourself and the company.

I’ve been a registered nurse for over 30 years. I started out as a clinician, with the majority of my time spent in the emergency room. I then got interested in hospital operations and working with the operational folks and leadership. As healthcare evolved, I evolved with it and got into analytics, understanding numbers and outcomes. I used Dimensional Insight’s system in three different organizations in three different roles and found that I loved what I was able to do with it. I came on board with the company in 2013. I help organizations understand their information, their data, and to get the right data to the right people so that they can act upon it.

Do health systems underuse nurses and other clinicians in using data to make decisions?

Yes. Our president likes to talk about the “data gene,” which some people have and some don’t. Every organization definitely has pearls — not only nurses, but lab and rad techs who actually understand the global picture. There’s always one person in every department where everybody knows that if you need an answer, you go to them. Those people are usually data-driven to begin with, just naturally.They do get underutilized, or shall I say mis-utilized. They have their regular job, and then when they have a chance, we’ll  have them do reports and stuff like that for us. But some very strong care providers are also analytical and would be helpful in pushing forward the analytics process.

BI and analytics tools triggered a buying frenzy. What was the result?

Like you said, it was a frenzy. Everyone felt like they had to get it. Many people are influenced by pretty pictures, or they go down a path and they’ve got someone who’s caught their interest.

What I’ve noticed in working with customers and in the literature is that sometimes customers take on too much. BI is a journey. When an organization tries to do 15 projects at the same time, it’s inevitable that none of them will get finished. A project gets started. Then it’s like, OK, this is cool, we can use that same tactic over here. They start big project B before finishing big project A, with the same people working on both. Now you’ve pulled them in two different directions and nothing gets finished.

The successful ones that I’ve seen have stayed within the guidelines of their strategic plan. Some people feel it takes too long to get that done, but you need to have a plan, a path you’re going down. Not just say, “We’ve got BI and we can do everything.” Every tool can, but you have take the steps and do it and close the loop before you go to the next one.

I’ve worked in organizations that had four or five BI tools, so they had four or five reporting teams. They still had the same problem — my BI tool says this, your BI tool says that. They never really got together and said, what do we say as an organization?

Does BI get the credit way down the line when the decisions it influenced finally produces positive, measurable results?

I think so. What I’ve seen is that there’s a big fervor at first. Everybody gets it, they see stuff, and they go wow.  But a BI install suddenly provides access to a lot of information. That’s the other “aha” that gets you. We have all this data and we don’t know what to do with it. We had none, now we have too much. How do we core it down to what’s going to be meaningful to us?

That’s where I think the BI tool can come into play, to help us focus on what we need to focus on because we have so much out there. Healthcare is just loaded with data, and more comes in every day. We want to use these complex business rules and these algorithms, but we could have obtained the same answer if we had just used a quicker approach.

Health systems have all this new data, multiple teams, and a mix of acquired health systems and practices using different systems and different terminologies, plus trying to decide whether to centralize the analytics function. Do these factors make it tougher to do analytics right?

Absolutely. It’s an absolute challenge, everything you just said. You might have a hospital organization that has been using an embedded BI tool for years. Then all of a sudden they acquire, or they’ve been acquired. They decide that they don’t want A, or they really want B. Then you have to go through a conversion of what they’ve done. Aside from just the acquisition process, you have to work on linking and cross-walking different EMRs or even the same EMR implemented with different approaches.

I’ve worked in two organizations that had four or five reporting teams. We were chasing our tails. Who do you believe? Who has the loudest voice this month or with this leadership? The people who really need the BI, the operational and front-line people, throw up their hands and say, “I don’t even know what I’m getting any more, so I don’t even care.” You look at who is using the BI and there’s little utilization. The people we’re trying to help don’t even get all the information they need because there are too many competing answers.

I find that the best success is when you bring in not only stakeholders, which is your leadership, but also the people that you’re expecting this data to help. They need to be a part of the process. You can’t just put this together and say, here you go, you’re on your own, take it and run with it. You have to bring them into the process so that they understand the value they’re getting. It’s one thing bringing a BI tool in, but what’s the value I’m going to get from it? Is it just one more report that I have to go through, or will it give me value and make my day better?

My experience is that the people who use analytics the most are department managers and directors instead of C-level executives who don’t even have computers on their desk. Should the C-suite be involved or pay more attention to what data is available and how it’s being used?

I would say that over the last two or three years, I’m seeing more and more C-suite involvement. I have a couple of customers that if the information isn’t available when the CEO comes to work, he or she is calling and saying, where are my numbers? So I am seeing more senior suite involvement.

There are two types of BI – the “how are we doing” numbers for the C suite and then the operational things, which are near and dear to my heart. The things that I had to do as a clinician or as a manager of clinicians. The things that I needed to arm them with. We can give that to them. Before, we would have to go through 15 reports to try to figure it out. It’s making their life easier.

There are so many rules and regulations coming out in healthcare. I have to remember to dot my I and cross my T. Maybe if I had a queue list to tell me that these are the three things I have to worry about, that would make my life easier.

It’s like anything else you do in life. It’s a daunting task if you have a room full of garbage and you have to decide where to start. You have to pick at it and say, I know I’m going to keep the stuff over there. That’s one fewer thing I have to worry about. From a BI perspective on the operational side, they see their page with their three things and they’re all green and they’re good. If one is red, they have to go focus on that. It’s helping them get through their day-to-day operational side.

We haven’t quite gotten the value from BI because healthcare and the operational side of things are complex. When I say operational, I’m thinking about your clinical folks. Was the assessment done in 24 hours? When was the last time case management saw these patients? There are standing operating procedures that are in place that if something goes wrong, we might stop and take a look at it. But generally speaking, it just goes along day by day until the holes in the Swiss cheese line up and you realize you should have been seeing this. But life’s busy in the hospital. We need to provide actionable information to the day-to-day providers so they can prevent the harm.

What new data elements are available for that alerting and trending analysis and how are they being used to impact individual patient care instead of just giving executives a stoplight report?

It’s more the capacity of how BI itself is evolving and how data is being pulled. The old world of BI was SQL queries. Now you’re getting into columnar databases that allow for a faster retrieval and for more data to be viewed at one time. That technology allows you to cipher through millions of rows of data. 

Think about it from a lab perspective. When I was at a healthcare organization in North Carolina, I worked with a clinical pharmacist to identify the five or six high-risk drugs that they wanted to have insight into. Then we got a tickler every time the lab values changed. We added the information to their hourly census, so that when the lab values came in and the patient was on this particular medication, they would see the trend before it got to a critical point. They would see that it’s been rising for the last two days by 0.2 percent each time, so we had better keep an eye on it.

It becomes more useful with the ability to visualize and manage more data at one time. I have another organization whose pharmacists use it to look at critical medications. They bring in over 40 million rows of data to use their work queues to improve their movement from IV antibiotics to PO antibiotics so they can lower cost, improve patient care, and hopefully get the patients out of the hospital sooner than later.

The BI approach uses technology to highlight exceptions to the defined desired values, while the machine language approach would be to throw a lot of data at the system to identify new problems or opportunities that humans have missed. How do those approaches co-exist?

Machine learning has a way to go, in my opinion. Someone still has to feed that machine some kind of algorithm, and it has to know what it’s looking for. Some are more sophisticated and can do patterning and I think that will become invaluable over time. It’s not mature yet, where physicians believe that it shows them what they expect. But it will be an invaluable asset as it continues to grow and as we continue to understand how all the data fits together.

Why have we stopped hearing the most overused term on the planet, “big data?”

Because everything is big data. It was just a catch phrase. I don’t know where it started, and then all of a sudden, it just went away and no one is even saying it any more. This may sound ignorant, but it’s the same thing when we talk about AI and machine learning. What do we mean by AI and machine learning? What concept do people have of that? What are the developer’s concepts? What do its potential users think? It raises the same kind of question as the term big data.

Do you have any final thoughts?

I really enjoy what I do now because I get to work within my passion in using analytics to help providers — who need it more than anybody else – and to help the operational folks with their daily operational process that is very difficult. There’s a lot of expectation that the people on the front line will get things done, remember all these rules, and do all these things. As we move forward in analytics, we will hopefully be able to make that life easier for them and help them focus on getting back to taking care of the patient.

HIStalk Interviews Terry Edwards, CEO, PerfectServe

February 6, 2019 Interviews No Comments

Terry Edwards is founder, president, and CEO of PerfectServe of Knoxville, TN.

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Tell me about yourself and the company.

I started PerfectServe in the late 1990s after spending a few years in a technology company called Voice-Tel, which was one of the early pioneers in interactive voice messaging. At that company, I saw the need to improve communications in healthcare and later started PerfectServe. The company started in managing communications in the physician’s office, extending later into managing nurse-to-physician communication in the hospital and acute care environment while still doing the physician work. We evolved that over the last several years into one of the most comprehensive communication platforms in the industry.

How will the mid-January acquisition of Telmediq, the top-rated secure communications vendor, change your business?

PerfectServe was acquired by the Los Angeles private equity firm K1 Investment Management in the middle of last year. That was part of the plan to get our early venture investors out. They had been invested in PerfectServe for a long time and stood behind the company. We were able to give them a successful exit.

With that, we were also able to clean up PerfectServe’s balance sheet and to gain the backing we needed to execute on a broader strategy. As you and I have talked about in the past, the industry in which we operate is that outside the realm of the EMR, the technologies are fragmented. We started to see this just in the fragmentation of communications alone. But in addition, other technologies that are adjacent to communications could be part of a more comprehensive platform.

We surveyed the landscape and saw the opportunity to consolidate some of the stronger players within our category. Telmediq was at the top of that list. It had capabilities that we did not have, such as in the contact center and call center space as well as in nursing mobility. We thought those would be valuable to our customers. While there’s overlap in what both companies do, Telmediq was doing some things better than PerfectServe, and PerfectServe was doing some things better than Telmediq. By bringing these two together, we believe we’ve created the leading communications platform in the marketplace.

How important is it for a CEO to work with investors who can help take the company to the next level or help it clarify its acquisition and positioning strategies?

K1 is a growth investor. There are different kinds of private equity firms and different business models. Some will find slower growth opportunities with companies that might be growing five or 10 percent a year, then put two of them together and then take out costs and try to drive synergy.

K1 is a growth company where they are looking to invest. They are about building leaders in the category. As they evaluated PerfectServe, one of the opportunities was that PerfectServe could be the cornerstone of a much larger and broader care team collaboration product offering strategy. That led to the opportunity to acquire Telmediq.

We just announced two other acquisitions. Lightning Bolt Solutions, which is in the physician scheduling space, and CareWire in the patient communications space. Our broader strategy is to build the care team collaboration platform of the future. We will do this through both acquisition — and integration of the acquisitions — as well as organic development. That takes capital to do well, which is why we have K1 at the table with us.

Was the death of pagers greatly exaggerated?

[laughs] They are dying a slow death, but there’s a long tail.

Consumers seem to be using phones more often for texting more than for making phone calls or sending email, and now they are using speech recognition to drive that messaging. How is that  impacting healthcare communication?

I’ve been amazed to watch the adoption of texting as a mode of communication. When we started PerfectServe, everything was voice driven. In fact, the first version of the PerfectServe platform was purely an interactive voice response platform. All the communications were voice driven and interacting with the keypad.

We first entered the acute space in 2005. Due to the nature of the platform, 100 percent of the communications we were processing were over the phone, either as a live call or sending a page or text message. The text messages could be as an alphanumeric page or SMS and they were all system generated.

We later introduced our web interface and then our mobile interface. With mobile came texting. We started to see texting rise.

About 18 months ago, we introduced a new user object so that nurses could authenticate in the same way as our physicians. With that, we were able to facilitate bidirectional communication. A nurse can send a text to a doctor via the secure platform, then the doctor can reply. In our newest hospital environments, 90-plus percent of all the communication that’s running through the platform is text, and it is secure text, which has been fascinating to see. It’s convenient and that’s the benefit.

What is being done to make communications part of the overall workflow?

Gartner has classified us in the category of clinical communication and collaboration, or CC&C. They gave it that name to help communicate to hospital buyers that communication is more than just secure texting. Secure texting is a component of a broader communication strategy.

But as we’re looking at this — and I think it’s consistent with how Gartner is looking at this – the clinical communication platform is a core component or pillar of a broader care team collaboration platform. It needs to encompass the communication modalities of secure texting, paging, SMS messaging, email notifications, and voice calling, whether it’s a cellular, voice over IP, or landline. You have to have this omni-channel communications component.

The key to PerfectServe since Day One has been our workflow capabilities. We are automating a communication workflow to make sure that we can connect the initiator – a nurse or a doctor or some other caregiver — to the person they need to reach, who can then take action at that moment in time. Workflow is a component of this.

As you think about workflow, there’s not only the algorithms around routing, but also call schedules. PerfectServe as well as Telmediq built call schedules into our platforms, but they were limited to the schedules specific to a communication workflow. Medical groups, for example, have scheduling needs that are broader than that, that go across the whole workforce. That is where Lightning Bolt comes into play.

These adjacent technologies move beyond communications to staff scheduling, referral management, rounding, and integration into other technologies like alarms, alert systems, nurse call, and interactive patient care. Our vision is to build the most comprehensive care team collaboration platform, either by building or acquiring technologies that make sense to be a part of it, and then integrating with those that are adjacent but outside the domain, such as nurse call.

How have the communications needs of health systems changed as they acquire hospitals and practices?

I don’t think they are changing, but the expansion is enabling them to put in stronger governance structures to drive higher levels of standardization. One of our clients, Advocate Health Care in Chicago, has been a model in terms of saying, these are the parameters upon which we’re going to communicate with you. We’re going to have these minimum standards around fail-safe notification processes and escalation and things like that. This starts to move the organization away from letting doctors do it however they want, which might be might be efficient for them but not for nurses or colleagues who need to reach them.

What do you as a CEO do during the HIMSS conference?

[laughs] It’s usually a pretty packed schedule. I will spend a little bit of time in our booth, and that’s unstructured. But for the most part, I’ve got meetings scheduled, a mix of customer meetings, new prospect meetings, analyst meetings, and sometimes meetings with folks in the financial community. It’s usually a pretty intense time, one of those events that I look forward to, but that I also hope to never attend again.

Do you have any final thoughts?

I’m excited about where PerfectServe is. Not just for me personally or our company, but for our customers. I’ve been in this space for a long time and I’ve seen a lot of things. There’s this bigger vision that I started to see about three or four years ago and it is here now. PerfectServe and our customers have the opportunity to deliver even greater value than I envisioned. I’m excited about that and excited about the future.

HIStalk Interviews Jason Krantz, CEO, Definitive Healthcare

January 28, 2019 Interviews No Comments

Jason Krantz, MBA is founder and CEO of Definitive Healthcare of  Framingham, MA.

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Tell me about yourself and the company.

Definitive Healthcare was started in 2011. Our goal is to be the premier provider and the single source of truth for all data on healthcare providers. In the last seven or eight years, we’ve grown significantly. We have about 320 employees today. We offer detailed information and analytics on every single provider in the US and Canada.

Why did HIMSS sell its HIMSS Analytics business and how did Definitive Healthcare end up acquiring it?

HIMSS Analytics has tremendous data assets around technology, infrastructure, and contracts. The match with Definitive is about being a good shepherd of that data. By combining that information with all of the proprietary data that we have around affiliation, quality of care, and now our commercial claims database, we’re able to provide a complete picture for our clients that will give them a competitive edge.

Those clients include companies that are marketing into the healthcare provider market as well as providers themselves that are looking to expand their networks and understand where they can continue to grow their business through physician referral, analytics, and new affiliations. We offer a powerful solution to help advance the industry forward.

HIMSS is keeping the Adoption Model business and the consulting around that, right?

That’s correct. They’re going to continue to provide the EMRAM and the consulting around it. We will focus on the data business and the detailed provider information for both the vendor community and the provider community.

How have mergers, affiliations, and network agreements changed the demand for information as the market gets more complicated than just single hospitals and health systems?

“Complicated” is the operative word. As this industry continues to evolve and health systems become these extraordinarily complicated organizations that are big businesses in their own right, all the participants in this industry need to have access to data that can help them decipher what’s happening. Where are patients going for care? How do all these facilities interact with each other?

More and more, we’re helping our clients understand where there is patient overlap or leakage from one hospital to the next. Our clients are trying to solve that for providers, while the providers are trying to figure on their own how they can continue to protect their business and deal with new payment models. The complexity helps our business over time.

Will these larger corporate entities impose a corporate standard for systems such as EHRs and revenue cycle?

The speed at which mergers are taking place certainly makes that difficult from a technology standpoint. Health systems by and large have the strategy of moving to a corporate standard, but it takes time. Technologies that help these systems talk to each other become increasingly important.

The other important corporate standard is around decision-making for medical devices and pharmaceuticals. Health systems are trying to create standards across their entire organization. That’s good for healthcare. Standard therapies help patients overall and help understand new therapies that come to market. The move to control everything within their network continues, even though it is complex with the technology infrastructure.

Where will the three main inpatient EHR vendors look for opportunities now that the market is saturated?

They are doing some pretty interesting stuff, such as starting to work with insurance companies and different types of facilities such as treatment facilities. Epic is the largest EHR that works within the clinical trial space, which is an interesting way of growing for them. You’ve got all this rich patient data that needs to be collected in one fashion and Epic does well in that market. We’re rolling out a clinical trial product to address the needs of the pharmaceutical companies and medical device companies that we serve, but also the technology companies that want to get a piece of this robust market.

Even though they’re relatively saturated within the hospital and the health system market, these tangential areas are exciting growth areas for them. They open up a new opportunities in life sciences, insurance, and other areas.

Are drug and device manufacturers more interested in using the information that a typical hospital or practice would collect?

Absolutely. Data from EHRs has grown so much and become more standard over time. It’s a tremendous opportunity for improving the quality of care by analyzing that data, getting newly available information and at a larger scale across larger patient populations. There’s a massive interest in getting access to that data from the pharmaceutical side.

What kind of information could a mid-tier hospital software vendor get from you that would help them understand their potential market?

We have data on every single provider in the US — clinics, physician offices, imaging centers, hospitals, and IDNs — and the affiliation of all these facilities. It’s important to know whether they are owned by a health system or are standalone. We have the technology infrastructure data that allows understanding what each of those facilities are using. That data has become stronger through our acquisition of the HIMSS Analytics business. We also have information around the quality of care provided and the Medicare penalties or incentives that each of these facilities is achieving.

All of that is important for these organizations that want to elevate the conversation with their prospective clients. Rather than going in to talk about their product, they can go in and talk about what’s happening at the facility or the health system — the problems they’re seeing in their market and how that compares to other facilities they have. They can use that data to bring their product to life and show those prospective clients why their product can help meet the needs of that organization right now. Making your team smart and targeted to understand the business problems of the hospitals and facilities is an important value-add that we bring to our clients.

How do you see the company changing as it grows?

Our goal is to continue our product innovation. We have grown, mostly organically, over the last seven years at a rate of something like 175 to 200 percent per year. We continue to grow by selling more of what we have. We have a very good product of extremely high quality that covers the market really well.

We are also innovative in what we roll out to clients. In the last year, we’ve been more innovative than in the first six or seven years of our existence. We rolled out a commercial claims database that gives our clients access to data on about 210 million patient lives. We have over two billion claims. This allows our clients to understand diagnoses and procedure utilization rates by facility, provider, or physician. We’re rolling out a clinical trials database, and later this year, we’ll also be rolling out a database with specialty pharma data.

Our goal is to continue to stay on the forefront of new trends that are happening within the marketplace. Each time we do this, we open up a brand new market that we haven’t sold to before. Clinical trials opens up a multi-billion dollar industry for us. Commercial claims gives us access to all of these new markets we haven’t sold to before that need to understand what’s happening in the commercial market. All of this innovation helps us continue to grow.

Over time, we’ll continue to pull in more information, maybe from EHR systems as you mentioned, to help clients analyze that data. That’s potentially something down the road. We’ll start to get into more of health economics and outcomes research. That’s a great market for us. We see the runway as being extraordinarily long. We’re going to continue to grow at the pace that we’ve been used to over the last five to seven years.

Who are the prospects for the all-claims database and how can you correlate that information with your other databases to provide new insights?

Most of our client base is interested in the commercial claims data. Certainly some core markets are life sciences, providers, and tech firms. We take this data, where you can see this utilization by facility and physician, and make it extremely powerful by combining it with all of our proprietary data. Now you can start to do things like roll that data up at the IDN level. What does an IDN look like for knee replacements or other procedures or diagnoses? You can also combine it with things around the quality of care analytics that we provide.

Our clients take this claims data that’s valuable on its own, but we bring it to life and make it an actionable piece of information that they can use to define a new drug launch or develop their markets and create a go-to market strategy for whatever product they might have.

Do health systems use your information for competitive purposes?

We have lots of health systems as clients. They’re using our data to develop their networks, which of course is competitive to some extent. They are looking to develop new physician relationships based on referral patterns. They’re using our data to find merger and acquisition opportunities. We help analyze leakage outside of the system, Our clients are interested in understanding that. They can start to fill those gaps, because any time care is delivered outside of their system, it’s harder to provide the quality of care at the cost that they want to provide it.

How do you see the company’s future over the next five or 10 years?

It’s about continuing to expand our product offering. We have a big team of people that are being highly innovative in thinking through what the trends are within the industry. We can help our clients meet those trends head-on and stay in front of them. Access to our data and our analytics gives our clients a competitive edge. This market is moving fast. To be competitive, our clients need to stay ahead of the trends and we need to help them do that.

Over the next five to 10 years, we’re going to continue to evolve, add new product offerings, and potentially do more acquisitions as the market continues to expand so that we can provide the best data to our clients to meet their needs.

Do you have any final thoughts?

We’re a fast-growing company and there’s a lot of responsibility that goes along with that. We invest a tremendous amount from our company in terms of helping our employees grow as individuals and also to give back. We launched the Definitive Cares program about two years ago, where we have 100 percent of our employees doing a community service project throughout the year. They earn days off by being part of this program.

It’s an important part of our culture because healthcare is about helping people and servicing people. We want to bring that into the fabric of our culture. We help over 30 charities every year. We have a 100 percent volunteer rate within it. As a company, we gave over 3,000 individual service hours during the working day. All of that is important. My final thought is that continuing to give back is important to all corporations. We try to live that on our own.

HIStalk Interviews Sean Carroll, CEO, Arcadia

January 23, 2019 Interviews No Comments

Sean Carroll is CEO of Arcadia of Burlington, MA.

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Tell me about yourself and the company.

I am a 32-year veteran of healthcare IT over six companies, all focused on some aspect of healthcare data. Some of those companies were service-oriented businesses, some have been technology focused, and one or two have been a combination of both.

I’ve been on an explicit mission over my career to be part of tangible progress in the evolution of healthcare. I firmly believe that progress must be founded in healthcare data as at least as one of the major levers that has to be pulled. I’ve been at Arcadia for five and a half years. I’m glad to be here because Arcadia has the capabilities and positioning in the market to be an instrumental player in that necessary transformation of healthcare. We are seeing that with our customers.

The company is positioned as a population health management company, specializing in delivering population-level analytics in care management to enterprise-class customers. We serve enterprise provider organizations and nationally branded, recognized health plans. We also have a nice partnership business. Since we last talked in mid-2015, the company has experienced significant expansion and growth, elevating itself to 50 million patients and 50,000 providers in our platform. We have continued to maintain top rankings and positioning with all of the analysts who track this market since we emerged in the KLAS report in the end of 2016.

What changes have you seen since 2015 in population health management, value-based care, and the availability and harmonization of EHR data?

It has evolved a lot. One of the positive developments in the ultimate transformation of healthcare is that the commitment to value-based concepts has remained steadfast, even with all of the crosswinds that we all face every day politically and from other influential angles. That’s been a positive trend of staying in that direction.

The market has, without a doubt, matured in many ways in the last three to four years. Organizations that are pursuing technology or services that support value-based care transformation have probably been through one or two tries at implementing something. They have some battle scars and they’re smarter about what they want. Vendors who support them in this effort also have learned a lot about what it takes to be an excellent provider of technology or value-based care services to support these transformations. It’s hard work and the market has come to understand that.

A lot of companies and investors have jumped into population health management technology. What changes have you seen as companies have developed a good or bad performance track record?

The vendor landscape has changed the most in that time frame. Some organizations have fallen down or fallen out of the market. Investors and operators are learning that the economics of providing population health technology require substantial investment and substantial time for that business model to mature, all while simultaneously delivering a high-quality customer outcome. It takes a unique bond among investors, customers, and vendors to make it all work. We have seen that ourselves and with competitors who don’t have those elegant relationships and therefore have struggled or failed to be successful in the marketplace.

KLAS’s recent population health management report commends Arcadia and a couple of other vendors for being good at offering customers strategic guidance as well as technology. How does a health system move from the vague idea of becoming involved in population health management to then developing a strategy and looking at technology?

The organization first typically organizes, within themselves, the right core team to drive that agenda. It becomes a focused strategic element that is driven by a population health executive, title notwithstanding, who has a clear vision of what they’re trying to achieve.

Population health management has a number of entry points. Priorities can be set in a lot of ways. Sometimes we see an absence of priorities or clear priorities, but the organization has good leadership, good governance, and an understanding the foundational elements of successful population health implementation. That’s the starting recipe for how organizations come together. Where we come in on the strategic side is helping them, once they have or are implementing the right set of tools on the right data asset, determine how they might focus. These are very specific, on-the-ground efforts, given the outcomes we’re seeing through the data and the tools that we avail to them to explore that data. It’s a tactical strategy.

Are health systems and insurers interested in improving an individual’s long-term health beyond simply reducing their own short-term cost and risk?

That gets to the heart of what we believe is exemplary population health management. It starts with a clear economic mandate. We’ve shifted our business with all of our capabilities to focus on making our customers economically successful first, in terms of proper execution in their risk contracts, so that they have the opportunity to make other investments in population health management outside of that. We’ve learned in the past five or six years that there’s a lot of things to chase in population health for the good of population health, but sustained financial success is the bridge to sustained successful health management of a population.

Would an insurer approach population health management differently than a large health system?

I would say no at the highest level, but obviously they have different business mandates than providers. We’ve been able to foster the notion between health plans and provider organizations that a properly-positioned, highly-usable, high-quality data asset in the marketplace — where the population at large is visible in every sense of the word from a data perspective — serves all parties, both in their own strategic designs and in the broader design of what we all want for healthcare.

We talked last time about the number of provider organizations that either don’t have a data strategy or are knowingly or unknowingly using bad data to drive their decisions. Has that improved?

It definitely has improved. Everyone understands now that data is important. Not everyone has prioritized it at the top of the list of their value-based care strategy, which we would recommend be the case. We last talked that it was still, in many cases, a challenge to get some organizations to understand why clinical data was an enhancement for them in the context of a data asset. That really is no longer the case.

How do you position and differentiate the company?

A lot of the data work that we do demands a certain quality level that is informed by tenure. We have been working at data harmonization for longer than most organizations in the space, probably by an order of magnitude. Some of that shows up in KLAS reporting in terms of the types of enterprise customers who choose Arcadia. We hear a lot that that’s because of our experience. Outcomes, as in the tangible and referable results from the deployment of our technology over time — improvements in risk coding, reductions in total cost of care, dozens of other outcomes — we focus on seeing that our customers can not only deliver those for themselves, but are eager to talk to other customers about that. Referenceability is a crucial, crucial item for us.

From a market perspective, we’re the only vendor that serves both health plans and providers. That has continued for us since the beginning. That position in the market is important since we believe in this concept of density of market, where providers and health plans in given markets are working together to advance population health. We approach the market a little bit differently in that regard.

Do you have any final thoughts?

We are enthusiastic about where the market is. We feel fortunate to be in the category of leader in advancing progress in managing population health. We’re equally excited about the nature of the market, which has settled out with some really good companies trying to advance this important goal for healthcare.

As a company, we’re excited about our ability to deliver what we believe is the most important thing for the next phase of advancement in this marketplace, which is both speed to value and lasting value for customers. If companies like Arcadia can continue to deliver that to the pioneer organizations that are trying to advance healthcare by better population health management, then everyone will benefit. We’re excited to be in the top category of companies that are delivering against that.

HIStalk Interviews Eric Widen, CEO, HBI Solutions

January 21, 2019 Interviews No Comments

Eric Widen is co-founder and CEO of HBI Solutions of Palo Alto, CA.

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Tell me about yourself and the company.

I have a long background in healthcare, over 25 years now. I’ve worked and focused on solving problems in healthcare, typically using data. We started HBI Solutions with a more sophisticated bent on using data and data science techniques to solve problems in healthcare. That focus has been on predictive insights on patients and populations, so that population managers and even individuals can understand insights into their health that they wouldn’t know otherwise. We use data science methods to do that.

What are the implications of predicting the outcomes of patients who may not even know they have a problem, as you did in applying machine learning to EHR data to identify people likely to eventually have chronic kidney disease?

That’s the million-dollar question. The punch line is, what do you do once you know this information? Our clients are focused on low-hanging fruit from a risk standpoint. They’re working closely on readmission rates for acute settings.

We have two flavors of risk models. One is the acute setting, where our insights predict what could happen before and immediately after discharge. It’s typically an acute team or a post-discharge transition and care team that is focused on things like readmissions, and inside the hospital, sepsis and mortality.

The other models are population-based models. You want to predict what’s going to happen in the future to patients who are healthy at home. The chronic kidney disease, CKD, model that you referenced is one of those. But by and large, organizations are largely focused on utilization and cost as the starting risk models. They target patients that are at risk for ED visits, inpatient visits, or high costs, then proactively enroll them in care programs.

Our more savvy clients are starting to get into disease models. CKD is one of them. But more common use cases involve risk of mortality, which was the subject of a paper we published. We’ve had organizations looking at the risk of death for a patient in a future 12-month period and proactively teeing up discussions about end-of-life and palliative care. We have a heart clinic focusing on getting patients who are at elevated risk for a heart attack into the clinic more frequently than they would otherwise.

We said in our mid-2016 conversation that CMS’s excitement about preventing readmissions would probably end up being more tactical than strategic, not really changing outcomes as much as pushing costs around. What have we learned from trying to fix a problem with what might be a blunt instrument?

A key performance indicator that is put into place by regulatory agency that includes penalties and economic implications always tends to have unintended consequences. With a laser focus on something like readmission rates, you’re looking only at a 30-day window post-discharge. The health of those people continues forever after that.

It’s more appropriate to understand all the risk for an individual. Not only within that 30-day transition and care period, but also for the next year and multiple years after that. You get people into more of a comprehensive risk management program to bend the cost curve longitudinally over time and to take care of all the patient’s risks via care management, not just the 30-day readmission risk. Day 31 and after is as important more important than those 30-day windows.

CMS, Joint Commission, and others have come up with ideas that sound naturally good, but without having data behind them. How should those organizations use the same data science as your customers?

It’s not there yet, obviously. The other unintended consequence is the administrative burden that is bestowed upon clinicians and healthcare organizations to meet these quality markers. It’s a heavy burden and a heavy lift and it doesn’t always lead to high-quality care.

Our philosophy as a company is that we purposely didn’t start with regulatory measurement, or any of those, as a focus of the company. We do those things because organizations have to do them. But our philosophy is around two markers — are we reducing the cost to manage patients and are we getting patients healthier?

As the risk goes down for things like readmission rates, utilization of the ED, mortality, or for having a heart attack, patients are actually getting healthier and moving towards an improved outcome. We’ve had clients use our risk scores as a marker to graduate people from care programs. As their risk goes down, they’re getting healthier and they no longer need an aggressive care management approach. They are closer to self-managed care.

I don’t know how this will affect how a regulatory agency thinks about care, but we have progressive organizations thinking about care in that way. Keeping their eye on the ball on a couple of important markers that are really getting people healthier. As people get healthier, they use fewer resources over time. We’re starting to get into the measurement of the cost effectiveness of this approach.

In healthcare, however, spending money to improve someone’s health today might mean someone else gets the payoff decades letter when the patient has changed jobs or insurers.

There is that kick-the-can-down mentality a little bit in the commercial markets. However, Medicare is the largest payer and people consume the most of their costs and incur most of their diseases as they stay in those programs longer. With managed Medicare, Medicare Advantage, and Medicare HCO plans, you get more of a longitudinal outlook on patients. They stay in the same plan or program. We’re targeting those types of organizations, where those incentives are aligned, because it’s a better fit.

I have seen in the commercial space exactly what you’ve described, the “it’s not our problem” approach. They are more focused on short-term risks, more interested in what could happen in the next 6-12 months instead of the next 5-10 years for that patient.

What is your most impressive customer outcome?

It’s a mix. Organizations that have been with us the longest have shown good longitudinal outcomes in reducing ED visits and readmissions. That was their largest focus, and remains their focus, because they can put their arms around that and put in programs to bend those curves.

We can look to the future for graduating people from care programs, Then we can develop, for example, more mental health-based risks. Getting people to that point of self-help to lower their rate of suicide and opioid abuse. That’s the next wave for us, as the way people think about care becomes more sophisticated. We’re not there yet. That’s our future direction.

Beyond Medicare, the VA has the incentive to pay attention to long-term patient outcomes and to implement mental health programs. Have they expressed interest?

We’ve had several conversations with the VA through one of our partners, InterSystems, which has a long relationship with the VA. We have the ability to deploy into existing technologies as smart engines behind the scenes. We can work with any workflow platform. We plan to work with the VA in the future, but nothing is in place yet.

What data elements do you wish you could get but can’t?

Our approach is to give us whatever data you have and we’ll generate the best insights on your population or on you as an individual. As we look to the future, we’re starting to work with more partners. We’ll announce this as time goes on, but these partners have access to different types of datasets. We have worked with what’s generally available in the electronic medical record and in claims systems. We’ve added outside data sources that we can get from the federal government, like social determinants and things we can add in at the ZIP code and Census Tract level.

We’ve been pitching ourselves as a population health program, but as we look at the future and getting more towards the consumer, we’re starting to work with different datasets that would allow us to develop new diagnostic screening and/or risk tools. Developing tests that don’t exist today. We could, with a mass spectrometry partner, develop analysis of proteins, lipids, and metabolites within the blood itself. It’s new data that hasn’t been harnessed, other than in research settings at a very small population level of tens or hundreds of patients.

We’ve been analyzing millions of patients in a lot of our datasets. As we work with these new partners, they’re looking to secure large population samples in tandem with EHRs in the US, but more globally. Our metabolic makeup changes at a detailed level as we exercise or enter new nutrition programs. You can measure that on a day-to- day or week-to-week basis and pick up these signals. This is really new and interesting to us. It’s the same repeatable process around machine learning that we apply to other datasets. But getting into this, we can start developing new tests in the market.

An example is a newborn screening test, where researchers who work at HBI have, in the academic setting at least, identified for every pregnant woman their likelihood of pre-term. If you’re more likely to deliver pre-term, then you will enter a different care program. Any obstetrician or pregnant woman would want that test. We want to develop tens or hundreds of those types of tests.

Another example of high-throughput analysis of mass spectrometry is diabetics whose glucose and A1C markers are “normal.” We can find that 20, 30, or 40 percent of that “normal” population is actually at risk by measuring the proteins and the metabolites within the blood. This is a new direction for HBI. It doesn’t take away from our current direction, it’s just a new channel that we’re going after. It enhances population risk management, but individual risk markers will be a more meaningful focus for us.

How can we separate the real deal from the posers in the HIMSS19 exhibit hall, where every vendor will suddenly claim that their old products are now powered by machine learning, AI, and analytics?

We pride ourselves on being a no-BS company, rolling up our sleeves and working with clients to get them better technology to make the doctor’s job easier and to get patients healthier. We’ve always taken that as a focus. We can differentiate by giving you a list of physicians who are using our technology, pointing to research papers, and putting you in touch with care managers who are using our product daily to the health and outcomes of patients. A lot of vendors don’t have those three in place.

Do you have any final thoughts?

We have been focused on US problems and issues, which have their own government and regulatory components that drive how you think about entering the market here, But if you take a general view of how to use technology to get patients healthier at a lower cost, it’s relevant to US. There’s no shortage of studies on how upside-down the US is on outcomes and cost.

But it’s relevant across the globe as well. Other countries are getting richer and eating more poorly. People there with more disposable income want access to more types of healthcare. It’s a global problem as well. It’s important to think about how technology applies not only in the US, but globally. That’s our approach in developing solutions that are relevant to people.

HIStalk Interviews Kevin MacDonald, CEO, Kit Check

December 17, 2018 Interviews No Comments

Kevin MacDonald is co-founder and CEO of Kit Check of Washington, DC.

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Tell me about yourself and the company.

I’ve been doing RFID and helping various parts of all kinds of different supply chains for 20 years. I started with Sun Microsystems, did a consulting company, and then I started Kit Check in 2011. A friend of my wife was a pharmacist. She was on crash cart duty and having an awful time. I said, boy, there’s an awfully difficult and hard to manage supply chain for drugs inside the hospital, not to mention outside. I think we can make the pharmacist’s life better and more efficient while making the drug spend cheaper and the end result safer.

How are hospitals using Internet of Things and RFID?

You typically hear about RFID in hospitals for tracking things that you don’t want to throw away, like capital equipment and people. Real-time location systems are kind of expensive. We focus on things that you actually do throw away, consumables such as, in this case, drugs. There’s a great ROI there. We are approaching 500 hospitals now and growing very quickly. We are thrilled that we’re now tracking more than one new medication every second, but there’s still a lot of room to grow.

The potential benefit in labor savings and medication tray dispensing accuracy is obvious, but how would a hospital pharmacy use your system to manage a drug recall or manufacturer shortage?

Imagine you have 150 carts across the hospital. Something is recalled. You’re going to send a tiger team of pharmacists around, taking hours or probably days for many people to open up and check each individual cart. Our system knows every single vial and every single place. We know exactly where to go to address recalls, where you do and don’t need to go. That multi-day process goes down to a matter of minutes, unless of course the recalled drug is absolutely everywhere, in which case you need to go to all the carts anyway.

As we’ve expanded to so many hospitals, we have a system where if two hospitals enter a recall, we scan everyone else’s inventory. We say, hey, you have a drug that was identified as recalled by other hospitals. We’re often ahead of both FDA and RASMAS in recalls.

Do you see other potential for network-effect type usage beyond a single hospital?

There are things around benchmarking. Everyone is constantly trying to figure out, what do I put in a crash cart? What do I put on the anesthesia floor? It’s typically a discussion or a debate rather than a fact-based situation. We can bring data about both what’s in your hospital as well as what others are doing. That makes it a clearer debate.

With controlled substances, the more data we have in the system across hospitals, the more we can learn additional patterns of how people divert medications. We can then make everyone smarter along the way. It’s incredible how many ways people find to divert controlled medications. Having more and more hospitals on the system allows them to get smarter and smarter every day.

How does your Bluesight for Controlled Substances improve on software provided by drug dispensing cabinet vendors?

The biggest difference is that it takes in multiple data sources and then layers on workflow to do 100 percent closed-loop auditing so that it is comprehensive. It also brings in data from the EHR and other systems and then layers machine learning and AI on top.

Dispensing cabinet reports can tell you that a nurse dispenses twice as much fentanyl as another nurse, but there might be a good reason for that. Perhaps they’re doing a cardiac surgery case in the OR. We can look at all patterns, including locations, waste buddies, and time between events, whether it’s dispense-and-admin or dispense-and-return. We understand the situations that are riskier.

At the core, we’re doing three things – identifying potential risks, adding workflow to make it actionable, and making it comprehensive by enhancing dispensing cabinet information with data from EHRs and other sources, such as time and attendance systems.

At least two nurses have confessed to killing dozens of inpatients using ADC-dispensed drugs, yet weren’t caught for years even though the correlation to specific drug withdrawals or the number of codes called on their work shifts seemed obvious after the fact. Is that business case for your system even though it’s hopefully a rare event?

It’s not easy to prevent, for sure. It is prevalent. Studies have shown that as many as 8 percent — one in 12 nurses, anesthesia providers, and pharmacists — will end up diverting controlled substances. If you take a trip to the hospital and touch a lot of different folks, you have a pretty high probability that some of them are diverting.

That goes along a spectrum. Typically, someone starts out slowly. They were playing soccer or something on the weekend and got injured, then decided to do a little pain relief. It slowly builds and gets out of control. Any given hospital at any given time almost certainly has diverters. If they aren’t finding them — which, by the way, most aren’t — there’s risk to patients.

Software vendors are claiming that their old products are suddenly using machine learning and AI when they’re actually just running queries. Is your system actually independently learning from the data it sees?

Over time, it’s learning individual patterns and behaviors as well as group patterns and behaviors. At the macro level, we look at several trends across all hospitals. We add in, for example, a waste buddy report, pain score report, or something like that across hospitals. A 100-bed community hospital is very different from an 800-bed academic center. Even between academic medical centers, the practice habits are going to be different.

We learn the practice habits at that facility and for groups of people. If you are a NICU nurse, your patterns will be different from an anesthesiologist or investigational radiologist. We learn over time what is a normal pattern and what is an abnormal pattern, We’re also looking at individuals to see if their behavior is changing over time and learning what is normal for them.

Unlike some other things where it’s just, “Let’s take a bunch of data and run some reports,” there actually machine learning and AI happening here.

That would require the system to also know when someone was positively identified as a diverter so it would know it predicted correctly. Is that information provided to the system?

We call it an investigative workflow. We identify the folks who are more risky. We’ll never say that someone is absolutely diverting, because there may be something strange that happened that caused them to spike on whatever the set of tools are.

Once the hospital starts an investigation, we give them the capability to drill in transaction by transaction. They can start conversations with management. They can then go further in the investigation workflow and escalate up to the time where someone is engaged with HR, rehab, or potentially criminal proceedings. But hospitals usually try to help their providers recover instead of instituting criminal proceedings.

We end up learning when all of these things happen. We also see patterns that we’ve seen elsewhere that we might highlight more, or other things that we want to take a look at and then apply to the rest of the hospitals in the dataset.

Your company has gotten pretty big, but it sits between EHR vendors and tray and drug dispensing technology vendors, both of which provide information your product needs even though they may have similar offerings. Are you concerned that being successful might cause those big companies to take action in developing a competing product or cutting off access to their information?

Our advantage is that we are big enough to have a good-sized engineering team, but we’re small enough to be nimble. We release new code and new functions every two weeks. Those large vendors are often on an annual cycle. It just takes forever. You need constantly update the patterns and the data feeds you’re looking at.

We think we’re well positioned, and in terms of the data we need, it’s fairly standard. We can do an HL7 interface, but most folks end up pulling standard reports out of both their EHR and their dispensing cabinets that they end up using for other purposes. I guess those companies could try to do something anti-competitive, but for the most part, we’re just using what’s already out there.

One of the most anti-competitive actions they could take would be simply to whip out their large checkbook and buy you out.

We’ve got a lot of room to develop. Our core is helping hospitals do those three things that we talked about — saving money on drug spend, being safer and more compliant, and being more efficient. Those all come down to having visibility at the item level. We started in the procedural spaces, where the hospitals were blind. Even if they had a dispensing cabinet, typically the dispensing cabinet counts were way off. We got almost perfect visibility in a place where they were blind.

We now have added the nursing floors and the other areas by our learning controlled substances. Over time, we’re going add more and more tools that help the hospital automate things, and again, do those three things. We are venture backed and we’re going to grow and become a bigger company, but we’ve got a lot of growing to do in the mean time.

How has the company changed in moving from a business that you personally bootstrapped, sweating those first sales because hospitals take forever to make decisions, to become a significant, venture-funded player?

It ha created a lot of opportunity. My co-founder and I were cold-calling. Neither of us had worked with hospitals. Honestly, knowing now how bad the hospital sales cycle is, I’m not sure that we would have started the business.

Having scale really helps. With the venture rounds, our investors have been super supportive. They believe in what we’re doing.

We’ve been able to build a decent-sized engineering team. Compared to the dispensing cabinet vendors of the world, I think the amount of engineering that we’re putting on software is bigger than some of the publicly traded guys. We can hire amazing people because we’re doing important work. It’s easy for people to get behind that important work as we grow. That’s the most interesting thing about scale.

We were at the American Society of Health-System Pharmacists Midyear conference recently. It was really cool to see all the customers out there. We’re not, as one director of pharmacy called us years ago, two nerds in a metal box any more. We’ve got scale and products and we’re solving important issues for the pharmacy. We’ve proven that. We do a good job at it.

Do you have any final thoughts?

We’re super excited to be helping our hospital partners, and going forward, not even just hospital partners. We’re working on getting drugs already tagged to the hospital and being able to have full traceability in the supply chain to allow those hospitals, again, to be safer, be more efficient, and lower their drug spend.

HIStalk Interviews Peter Butler, CEO, Hayes Management Consulting

October 31, 2018 Interviews No Comments

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

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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

October 29, 2018 Interviews No Comments

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

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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

October 24, 2018 Interviews No Comments

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

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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

October 17, 2018 Interviews No Comments

Rizwan Koita is CEO of CitiusTech of Princeton, NJ.

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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

October 3, 2018 Interviews No Comments

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

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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

August 27, 2018 Interviews No Comments

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

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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

August 13, 2018 Interviews No Comments

Rich Berner is CEO of MDLive of Sunrise, FL.

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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

August 8, 2018 Interviews 2 Comments

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

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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

July 30, 2018 Interviews No Comments

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.

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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

July 25, 2018 Interviews 2 Comments

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

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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

July 23, 2018 Interviews No Comments

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

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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.

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Reader Comments

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