My post before HIMSS talked about how jazzed (not jaded) I was to be attending my 20^th HIMSS conference. Now that HIMSS18 is in the bag – what did I learn?

ML and AI

On Monday I presented the results of our AI survey at the Machine Learning & AI for Healthcare preconference event at the Wynn. Although there were a few hundred seats, the event sold out weeks in advance. A number of folks I knew who planned to buy a ticket at the door were shut out. So that’s a lesson – when it comes to attending hot topics, don’t procrastinate!

Keynote speaker Lynda Chin from the University of Texas compared using of AI to having a paralegal on your team – it’s someone intelligent that could pull resources together to help you make better decisions. She summed it up simply: “Machines serving humans, not humans serving machines.”

Many other speakers came from large health systems and spoke to important use cases:

• Kaiser Permanente: Colorectal cancer detection 1-2 years earlier with AI.
• UPMC: Game-changing pediatric readmissions prediction.
• Duke Institute for Health Innovation: Implementation of AI with thousands of input features.
• Stanford Health Care: Working with “small” vs “big” data.
• Brigham & Women’s: Costs of short-time cancellations vs no-shows.

It’s become a given that these leaders and their vendors use AI and use it well. My favorite from the above examples was Srinivasan Suresh, CMIO at Children’s Hospital of Pittsburgh of UPMC. His slide highlighted that, although he had no impressive AI or ML credentials, he was still able to use these kinds of tools successfully to predict pediatric readmissions due to seizures, asthma, and pneumonia, which led to more effective interventions.

HIMSS and health IT may be more of a cacophony than a symphony, but I’m glad to be in the orchestra.

Keynotes

AI and the cloud were key themes this year and have become mainstream topics. For our views on Eric Schmidt’s keynote about data, analytics, and AI, see our earlier HIMSS18 recap blog.

Glad I had teammates that made it into Seema Verma’s CMS keynote the next day – her announcement about patient data access, open APIs, and Blue Button 2.0 was welcome. You may recall the previous year, given the change of administration, there was little that CMS or ONC could say about anything. Although we’re seeing some progress, it doesn’t seem substantial enough to move the needle on value-based care.

Natural Language Processing (NLP)

A big part of my week was meeting with NLP vendors. Chilmark Research is close to releasing our major report on this topic, and it was great to get insights from more than a dozen vendors. Some of the smaller ones are highly focused on specific use cases (Health Fidelity and Talix on risk stratification; Clinithink on matching patients to clinical trials). 3M and its partnership with Alphabet’s Verily are a powerful combination on determining the “dominoes” of costs and care. Also of note: M*Modal’s virtual provider assistant and use of ambient devices, as well as Nuance’s partnership with Epic to add more conversational AI functionality. We are seeing voice assistant success paving the way to virtual scribes – those that can “whisper” in the physician’s ear will be most valuable to ensure that decision support is not bypassed by passive systems.

Interoperability

As John Moore posted in his earlier HIMSS18 recap, it’s sad (well, infuriating) that we still have to address interoperability. I attended two events held by the Strategic Health Information Exchange Collaborative (SHIEC), which has been successful in providing a rallying point for 60 HIEs and 40 vendors to share knowledge and provide comments to ONC regarding TEFCA and data exchange. But it only represents a fraction of the hundreds of private and public HIEs in the country, so there is still a long road ahead. A payer committee was a welcome sign that convergence was part of their agenda.

Sensors

At the opposite end of the interoperability spectrum, I attended a session by Houston Methodist on body sensors, where the distances are measured in inches and the signals are often so weak that temperature or motion (such as a kicking baby) are enough to throw them off. Sensor network fusion is the frontier – the more information you can capture from more places with more context, the better. For example, one of Methodist’s use cases was rapidly predicting a patient fall.

I also met with Somatix, a small vendor with a big idea we’ve been hearing about for years – using data from wearables to track more routine activities of daily living (some of which, like smoking, are harmful). The vendor is attempting to take this to the next level with more accurate gesture detection and predictive analytics so appropriate (and even real-time) interventions can be made using specific apps. As Brian Eastwood recently posted, we’re still waiting for wearables to provide insight. I didn’t sport a wearable at HIMSS18 (I broke two and lost another in 2017), but I’m on the lookout for a good, waterproof one.

Image Interpretation

Another key area of focus for us is the use of AI to interpret digital medical images. An impressive talk by University of Virginia and the National Institute of Health included use of speech recognition (using Carestream and Epic) to embed hyperlinks of AI-recognized areas of interest into reports for the EHR. The two-year effort showed productivity improvements of 3x over unassisted analysis and reporting.

A presentation by Entlitic claimed AI-enabled “superhuman” techniques able to detect lung cancer two years sooner than existing approaches. Their solution made it easy to compare an existing case to similar cases where timelines of data showed disease progressions. The company has 65 radiologists that label their training data, claiming only 1 in 4 that apply for the job pass their test. We’ll dive into detail about these kinds of advances in our Digital Medical Imaging Report scheduled for Q4’18.

Image Exchange

I spent time with Ambra, a major provider of image exchange solutions (others include Nuance and lifeIMAGE). Aside from the challenge of the size of medical images, it always surprises me how difficult it is to move them around and make them available despite good standards (DICOM). It was only recently that Epic, for example, addressed image exchange, and it’s not part of many HIEs. I’m glad to see we’re moving beyond the vendor neural archiving discussion and toward a focus on the cloud and useful exchange of images in clinician workflow.

Receptions

I also attended half a dozen receptions during the week. The biggest was sponsored by a large consulting firm. It was an evening of fun, but it reminded me of what was right and wrong about our industry and a conference in Las Vegas – who’s really paying that bill? My last reception was with BetterDoctor, which specializes in the quality of provider directory data. It always seemed ironic to me that the most regulated profession in the world has such a problem with accurate information (retirement, credentialing, locations, and so on).

My Ears Hurt

To rework my “I’m Jazzed” comment from the top with a music metaphor, HIMSS is more like a blaring of thousands of different instruments with each of the “sections” competing to be louder than the other – and the sounds of Vegas don’t help. There are many great musicians and an increasing number of duets (e.g., partnerships, ACOs), but we’re still playing off too many different pages. Adding to the problem is the conductor (the government) changing every few years.

It may be more of a cacophony than a symphony, but I’m glad to be in the orchestra. I hope you are, too.

Successful startups will define a problem and solve it, not just prove a concept

By many accounts, the digital health market remains strong. Both Startup Health and Rock Health reported substantial year-over-year upticks in VC funding announcements, at 44% and 31%, respectively. (Startup Health assessed $11.5 billion in global deals, while Rock Health looked at U.S. deals worth nearly $6 billion.) Digital health vendors had a heavy presence at this year’s Consumer Electronics Show as well.

Look a little closer, though, as investor lawsuits and lax evidence seem to suggest that strength might be starting to crack. Both startup incubators omitted the maligned Outcome Health from their assessments; the company, which received $500 million in funding last May, now faces fraud lawsuits from those same investors. The omission suggests that future digital health deals should expect additional scrutiny – but it also raises the question of how closely Outcome Health was scrutinized in the first place.

CES 2018 gave the healthcare industry solutions in search of real problems. Meanwhile, the stark reality of the flu in the United States presents a real problem that could benefit from a variety of tech-enabled solutions.

At the same time, the Startup Health and Rock Health assessments include Peleton, which with $325 million in funding received one the biggest deals of 2017. Peleton makes a $2,000 stationary bike and demonstrated a $4,000 treadmill at this year’s Consumer Electronics Show – monthly subscriptions to on-demand workouts not included. Peleton’s inclusion on a list of digital health vendors is, at first glance, a bit dubious:

Seriously – can we please stop calling a connected stationary bike #digitalhealth?
https://t.co/Mzn1E2PmK4

— Brian Eastwood (@Brian_Eastwood) January 5, 2018

Peleton’s treadmill was part of a long list of digital health demos at this month’s CES 2018. During the show, the contents of this list showed some promise – devices tracking sleep, wearables measuring biometric data, and voice assistants helping with everyday life. Under the bright lights of the Las Vegas Convention Center, the use cases were clear.

It didn’t take long for the lights to dim. Take these two research papers that came out days after SEC: One found “no statistically significant impact of remote patient monitoring on any of six reported clinical outcomes” – not the desired results. The other found the healthy and wealthy to be the most likely users of sleep tracking apps – not the desired demographic.

As for the voice assistants, a CNBC technology writer suggested that, at this stage, they are proofs of concept and not yet tangible products. LG and Samsung think it would be cool for you to if you could talk to your appliances – to get useful information, that is, and not simply to curse when your toast is burnt. Moen thinks it would be cool if you could talk to your faucet. It’s useful, sure, but it’s little different than what your smartphone already offers – and it doesn’t require replacing a refrigerator or bathroom faucet.

All these vendors face the same challenge that Apple faced in 2007 with the original iPhone: Convincing people that they need something before they really know what “something” is. The market’s just not there yet.

Outside the Las Vegas Convention Center, life (cough) goes on

While CES 2018 gave the healthcare industry solutions in search of real problems, headlines proclaiming that this year’s bad flu season is poised to get worse present a real problem that could benefit from a variety of tech-enabled solutions. With hospitalizations on track to top 700,000 in this flu season, and on the 100th anniversary of the outbreak of the flu epidemic that infected one-third of the world and killed 675,000 Americans, it’s not time to sit still.

A comprehensive and multi-modal approach could help healthcare rise to the occasion:

• Readily available and easily understandable educational material about flu prevention, shared months before outbreaks typically hit and distributed to patients through multiple channels, not just a portal message.
• Incorporation of flu prevention into wellness visit protocols, complete with a new CPT code that covers flu prevention (not just vaccination) as well as public and private payer reimbursement for virtual visits (outside of the chronic care management CPT code) that address flu prevention.
• Honest information about flu vaccines that addresses two facts: That healthy patients should still get shots, to protect those around them at greater risk (also known as herd immunity), but also that shots don’t protect against all flu strains.
• Alignment of provider, payer, and employer incentives for getting flu shots but also taking additional preventive measures, as tracked and measured through a wellness app, portal, bidirectional messaging, or other consumer-friendly means.
• Increased use of CDC and other government flu-tracking data, as well as social media data, in real-time predictive models to help health systems forecast when flu cases will pick up, coupled with automated alerts to affiliated practices about what to expect and what precautions to take.
• Broader integration of retail health, telehealth, and urgent care services with traditional health systems to ease the ED’s flu treatment burden – and to reduce the exposure of a flu patient with a compromised immune system to other diseases that present in the ED.

Some vendors have already taken up the task. Smart thermometer maker Kinsa is crowdsourcing its data, which the company says outpaces the CDC’s data releases by several weeks. Meanwhile, athenahealth has been tracking data from the practices on its network since 2013 – when a government shutdown left the CDC unable to track flu data on its own.

Emphasize problems, and the value of solving them

We do not present this punchlist of problems to suggest that digital health vendors should drop their sensors and algorithms and immediately pivot to the flu. Rather, they need to focus solution development on a specific problem and the value that they add to solving the problem. The unmet needs of flu prevention and treatment simply illustrate the breadth and depth of a single problem and the numerous ways that digital health can provide a solution to that problem.

Wearables, trackers, voice assistants – and, yes, even stationary bikes – could play a role in solving some of healthcare’s problems: Physical inactivity, health education and literacy, data collection, condition management, messaging, access to care, and a host of other issues.

The challenge for startups, as well as the investors that fund them and the incubators that advise them, is articulating a vision for how these solutions add value to healthcare as a whole. After all, if solutions fail to define their value, the market will define it for them.

Chilmark Research will continue to examine digital health this year, whether at industry events such as HIMSS18 or our own Convergence or through research projects on topics such as virtual care models. We look forward to conversations with those who have been bold enough to define their value.

After all, that’s what separates a proof of concept from a product, and that’s what will drive digital health investment in 2018 and beyond.