By MATTHEW HOLT

Okay, I can’t do it any longer. As much as I tried to resist, it is time to write about ambient scribing. But I’m going to do it in a slightly odd way

If you have met me, you know that I have a strange English-American accent, and I speak in a garbled manner. Yet I’m using the inbuilt voice recognition that Google supplies to write this story now.

Side note: I dictated this whole thing on my phone while watching my kids water polo game, which has a fair amount of background noise. And I think you’ll be modestly amused about how terrible the original transcript was. But then I put that entire mess of a text  into ChatGPT and told it to fix the mistakes. it did an incredible job and the output required surprisingly little editing.

Now, it’s not perfect, but it’s a lot better than it used to be, and that is due to a couple of things. One is the vast improvement in acoustic recording, and the second is the combination of Natural Language Processing and artificial intelligence.

Which brings us to ambient listening now. It’s very common in all the applications we use in business, like Zoom and others like transcript creation from videos on Youtube. Of course, we have had something similar in the medical business for many years, particularly in terms of radiology and voice recognition. It has only been in the last few years that transcribing the toughest job of all–the clinical encounter–has gotten easier.

The problem is that doctors and other professionals are forced to write up the notes and history of all that has happened with their patients. The introduction of electronic medical records made this a major pain point. Doctors used to take notes mostly in shorthand, leaving the abstraction of these notes for coding and billing purposes to be done by some poor sap in the basement of the hospital.

Alternatively in the past, doctors used to dictate and then send tapes or voice files off to parts unknown, but then would have to get those notes back and put them into the record. Since the 2010s, when most American health care moved towards using  electronic records, most clinicians have had to type their notes. And this was a big problem for many of them. It has led to a lot of grumpy doctors not only typing in the exam room and ignoring their patients, but also having to type up their notes later in the day. And of course, that’s a major contributor to burnout.

To some extent, the issue of having to type has been mitigated by medical scribes–actual human beings wandering around behind doctors pushing a laptop on wheels and typing up everything that was said by doctors and their patients. And there have been other experiments. Augmedix started off using Google Glass, allowing scribes in remote locations like Bangladesh to listen and type directly into the EMR.

But the real breakthrough has been in the last few years. Companies like Suki, Abridge, and the late Robin started to promise doctors that they could capture the ambient conversation and turn it into proper SOAP notes. The biggest splash was made by the biggest dictation company, Nuance, which in the middle of this transformation got bought by one of the tech titans, Microsoft. Six years ago, they had a demonstration at HIMSS showing that ambient scribing technology was viable. I attended it, and I’m pretty sure that it was faked. Five years ago, I also used Abridge’s tool to try to capture a conversation I had with my doctor — at that time, they were offering a consumer-facing tool – and it was pretty dreadful.

Fast forward to today, and there are a bunch of companies with what seem to be really very good products.

Nuance’s DAX is in relatively wide use. Abridge has refocused itself on clinicians and has excellent reviews, (you can see my interview and demo with CEO Shiv Rao here) and Nabla has just published a really compelling review from its first big rollout with Kaiser Permanente, Northern California in the NEJM no less. (FD I am an advisor to Nabla although not involved in its KP work). And others like DeepScribe, Ambience, Augmedix and even newcomers Innovaccer and Sudoh.ai seem to be good options.

If you take a look at the results of the NEJM published study that was done in Northern California using Nabla’s tool, you’ll see that clinicians have adopted that very quickly, with high marks for both its accuracy, and the ability to deliver a SOAP note and patient summary very quickly. And it has returned a lot of time to the clinician’s day. (Worth noting that independent practice Carbon Health has built its own inhouse ambient scribe and used it on 500K visits so far)

The big gorilla on the EMR side, Epic, has integrated to some extent with Nuance and Abridge, but many of the other companies are both working to integrate with Epic and are inside other EMR competitors – for instance Nextgen is private-labeling Nabla. At the moment, for basically everyone integration really just means getting the note summary into the notes section of the EMR.

But there is definitely more to come. For many years, NLP companies like Apixio, Talix, Health Equity and more (all seemingly bought by Edifecs) have been working on EMR notes to aid coders in billing, and it’s an easy leap to assume that will happen more and more with ambient scribing. And of course, the same thing is going to be true for clinical decision support and pretty soon integration with orders and workflow. In other words, when a doctor says to a patient, “We are going to start you on this new drug,” not only will it appear in the SOAP note, but the prescription or the lab order will just be magically done.

But is it reasonable to suppose that we are just paving the cowpath here? Ambient scribing is just making the physician office visit data more accessible. It’s not making it go away, which is what we should be trying to do. But I can’t blame the ambient scribing companies for that. And as I have (at length!) pointed out, we are still stuck in a fee-for-transaction system in which the health services operators in this country make money by doing stuff, writing it up, and charging for it. That is not going away anytime soon.

But given that’s where we are, I think we can still see how the ambient scribing battle will play out. 

Nuance’s DAX has the advantage of a huge client base, but frankly, Nuance has not been an innovative company. One former employee told me that they have never invented anything. And indeed, the DAX system was massively enhanced by the tech Nuance acquired when purchasing a company called Saykara in 2021, some years after that unconvincing demo back at HIMSS 2018.

So innovation matters, but the other issue is the cost of ambient scribing, which in some cases is nearing the cost of a real scribe. Nuance’s DAX, Suki, and even new entries like Sunoh seem to be around the $400 to $600 a month per physician level. Sunoh is offered by eClinicalworks and has some co-ownership with that EMR vendor. What’s amazing is that at the price quoted at HIMSS of $1.25 per encounter the ambient scribing tool would cost a busy family practice doc seeing 25 patients a day as much as the EMR subscription, around $600 a month.

Abridge has been quoted at roughly $250 a month, and Nabla seems to be considerably less expensive, around $120. But realistically, the whole market will have to compress to about that level because the switching costs are going to be very trivial. Right now, with most of them requiring a paste and copy into the EMR, it’s almost zero.

Which then leads to some more technical issues. How good will these systems become? (Noting that they are already very good, according to reviews on the Elion site). And what will happen to the way they store data. Most of them are currently moving the data back to their cloud for processing. But this may not be acceptable for health systems that like to keep data within their firewalls. For what it’s worth, Nabla, being from the EU and very conscious of GDPR, has been pushing the fact that its process stays on the physician’s local machine – although I’m not sure how much difference that makes in the market.

The other technical issue is the reliance on the large LLMs like OpenAI, Google, etc., compared to companies that are using their own LLM. Again, this may just remain a technical issue that no one cares much about. On the other hand, accuracy and lack of anonymization will continue to be a big issue if more generic LLMs are used. Now the fascination with the initial ChatGPT type LLM is wearing off, there’s going to be a lot more concern about how AI is using health care as a whole–particularly its tendency to “hallucinate” or get stuff wrong. That will obviously impact ambient scribing, even if mistakes may not be as serious as perhaps patient diagnosis or treatment suggestions.

So it’s too early to know exactly how this plays out, but it’s not much too early. In some ways, it’s very refreshing to see the speed at which this new technology is being adopted. As it is, the number of American doctors using ambient scribing is probably below 10%. But it’s highly likely that number goes up to 70%+ in very short order.

The problem that it is fixing for doctors is one that has been around for thousands of years and also one that has been particularly acute for the last twenty years or so. It’s almost like we’re in a period where the doctor suffering with having to  type up their notes in Epic–written up so eloquently by Bob Wachter in his book, “The Digital Doctor,”– is going to be a historical artifact that lasted for fifteen years or so. Maybe it’s going to be talked about nostalgically, like those of us who reminisce about having to get online with dial-up modems.

I’m pretty sure that the winners will be apparent in a couple of years, and that somebody, possibly Microsoft, or possibly the investors in big rounds at 2021 style valuations for Abridge or Ambience, may be regretting what happened in a couple of years. Alternatively, one of them may be a monopoly winner that soon starts printing money.

I suspect, though, that ambient scribing will essentially become a close-to-free product for all different types of business and that clinical care will not be much of an exception. That suggests that a company like Anthropic or OpenAI with close connections to the tech titans, Amazon and Microsoft, will end up becoming more of a feature for the tech giants. My guess is that they will be delivering that product for free probably also into much of clinical care, including ambient scribing. Of course, Epic may decide that it wants to do the same thing, which may leave its partners including Microsoft in the lurch.

It’s reasonable to expect that all aspects of life, including education, general business, consumer activity, and more, will find note-taking, summaries, and decision support a natural part of the next round of computing. For instance, anyone who has had a conversation with their contractor when renovating a house would probably love to have the notes, to-dos and agreements automatically recorded. It’ll be a whole new way of “keeping people honest”. Same thing for health care, I suspect.

But to be fair, we are not there yet. My dictation tool took this whole thing while watching a water polo game on Sunday. And I think you’ll be modestly amused about how terrible the original transcript was. But then I put that entire mess of a text  into ChatGPT and told it to fix the mistakes. it did an incredible job and the output required surprisingly little editing.

AI is getting very smart at working on incomplete information, and health care (as well as clinicians and patients) will benefit.

Matthew Holt is the publisher of The Health Care Blog and one upon a time ran the Health 2.0 Conference

For my parents, March, 1965 was a banner month. First, that was the month that NASA launched the Gemini program, unleashing “transformative capabilities and cutting-edge technologies that paved the way for not only Apollo, but the achievements of the space shuttle, building the International Space Station and setting the stage for human exploration of Mars.” It also was the last month that either of them took a puff of their favored cigarette brand – L&M’s.

They are long gone, but the words “Gemini” and the L’s and the M’s have taken on new meaning and relevance now six decades later.

The name Gemini reemerged with great fanfare on December 6, 2023, when Google chair, Sundar Pichai, introduced “Gemini: our largest and most capable AI model.” Embedded in the announcement were the L’s and the M’s as we see here: “From natural image, audio and video understanding to mathematical reasoning, Gemini’s performance exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks used in large language model (LLM) research and development.

Google’s announcement also offered a head to head comparison with GPT-4 (Generative Pretrained Transformer-4.) It is the product of a non-profit initiative, and was released on March 14, 2023. Microsoft’s helpful AI search engine, Bing, helpfully informs that, “OpenAI is a research organization that aims to create artificial general intelligence (AGI) that can benefit all of humanity…They have created models such as Generative Pretrained Transformers (GPT) which can understand and generate text or code, and DALL-E, which can generate and edit images given a text description.”

While “Bing” goes all the way back to a Steve Ballmer announcement on May 28, 2009, it was 14 years into the future, on February 7, 2023, that the company announced a major overhaul that, 1 month later, would allow Microsoft to broadcast that Bing (by leveraging an agreement with OpenAI) now had more than 100 million users.

Which brings us back to the other LLM (large language model) – GPT-4, which the Gemini announcement explores in a head-to-head comparison with its’ new offering. Google embraces text, image, video, and audio comparisons, and declares Gemini superior to GPT-4.

Mark Minevich, a “highly regarded and trusted Digital Cognitive Strategist,” writing this month in Forbes, seems to agree with this, writing, “Google rocked the technology world with the unveiling of Gemini – an artificial intelligence system representing their most significant leap in AI capabilities. Hailed as a potential game-changer across industries, Gemini combines data types like never before to unlock new possibilities in machine learning… Its multimodal nature builds on yet goes far beyond predecessors like GPT-3.5 and GPT-4 in its ability to understand our complex world dynamically.”

Expect to hear the word “multimodality” repeatedly in 2024 and with emphasis.

But academics will be quick to remind that the origins can be traced all the way back to 1952 scholarly debates about “discourse analysis”, at a time when my Mom and Dad were still puffing on their L&M’s. Language and communication experts at the time recognized “a major shift from analyzing language, or mono-mode, to dealing with multi-mode meaning making practices such as: music, body language, facial expressions, images, architecture, and a great variety of communicative modes.”

Minevich believes that “With Gemini’s launch, society has arrived at an inflection point with AI advancement.” Powerhouse consulting group, BCG (Boston Consulting Group), definitely agrees. They’ve upgraded their L&M’s, with a new acronym, LMM, standing for “large multimodal model.” Leonid Zhukov, Ph.D, director of the BCG Global AI Institute, believes “LMMs have the potential to become the brains of autonomous agents—which don’t just sense but also act on their environment—in the next 3 to 5 years. This could pave the way for fully automated workflows.”

BCG predicts an explosion of activity among its corporate clients focused on labor productivity, personalized customer experiences, and accelerated (especially) scientific R&D. But they also see high volume consumer engagement generating content, new ideas, efficiency gains, and tailored personal experiences.

This seems to be BCG talk for “You ain’t seen nothing yet.” In 2024, they say all eyes are on “autonomous agents.” As they describe what’s coming next: “Autonomous agents are, in effect, dynamic systems that can both sense and act on their environment. In other words, with stand-alone LLMs, you have access to a powerful brain; autonomous agents add arms and legs.”

This kind of talk is making a whole bunch of people nervous. Most have already heard Elon Musk’s famous 2023 quote, “Mark my words, AI is far more dangerous than nukes. I am really quite close to the cutting edge in AI, and it scares the hell out of me.”  BCG acknowledges as much, saying, “Using AI, which generates as much hope as it does horror, therefore poses a conundrum for business… Maintaining human control is central to responsible AI; the risks of AI failures are greatest when timely human intervention isn’t possible. It also demands tempering business performance with safety, security, and fairness… scientists usually focus on the technical challenge of building goodness and fairness into AI, which, logically, is impossible to accomplish unless all humans are good and fair.”

Expect in 2024 to see once again the worn out phrase “Three Pillars” . This time it will be attached to LMM AI, and it will advocate for three forms of “license” in operate:

1. Legal license – “regulatory permits and statutory obligations.”
2. Economic license – ROI to shareholders and executives.
3. Social license – a social contract delivering transparency, equity and justice to society.

BCG suggests that trust will be the core challenge, and that technology is tricky. We’ve been there before. The 1964 Surgeon General’s report knocked the socks off of tobacco company execs who thought high-tech filters would shield them from liability. But the government report burst that bubble by stating “Cigarette smoking is a health hazard of sufficient importance in the United States to warrant appropriate remedial action.”  Then came the Gemini 6A’s 1st attempt to launch on December 12,1965.  It was cancelled when its’ fuel igniter failed.

Generative AI driven LMM’s will “likely be transformative,” but clearly will also have its ups and downs as well.  As BCG cautions, “Trust is critical for social acceptance, especially in cases where AI can act independent of human supervision and have an impact on human lives.”

Mike Magee MD is a Medical Historian and regular contributor to THCB. He is the author of CODE BLUE: Inside America’s Medical Industrial Complex.

But having used their consumer version a few years back and been a little disappointed, I wanted to see what all the fuss was about. CEO Shiv Rao was a real sport and took me through a clinical example with him as the doc and me as a (slightly) fictionalized patient. He also patiently explained where the company was coming from and what their road map was. But they are all in on AI–no off shore typists trying to correct in close to real time here.

And you’ll for sure want to see the demo. (If you want to skip the chat it’s about 8.00 to 16.50). And I think you’ll be very impressed indeed. I know I was. I can’t imagine a doctor not wanting this, and I suspect those armies of scribes will soon be able to go back to real work! — Matthew Holt

By KIM BELLARD

Did you know we are living in the Zettabyte Era? Honestly, did you even know what a zettabyte is? Kilobytes, gigabytes, maybe even terabytes, sure, but zettabytes? Well, if you ran data centers you’d know, and you’d care because demand for data storage is skyrocketing (all those TikTok videos and Netflix shows add up). Believe it or not, pretty much all of that data is still stored on magnetic tapes, which have served us well for the past sixty some years but at some point, there won’t be enough tapes or enough places to store them to keep up with the data storage needs.

That’s why people are so keen on DNA storage – including me.

A zettabyte, for the record, is one sextillion bytes. A kilobyte is 1000 bytes; a zettabyte is 1000⁷. Between gigabytes and zettabytes, by powers of 1000, come terabytes, petabytes, and exabytes; after zettabyte comes yottabytes. Back in 2016, Cisco announced we were in the Zettabyte Era, with global internet traffic reaching 1.2 zettabytes. We’ll be in the Yottabyte Era before the decade is out.

People have been working on DNA storage for many years; I first wrote about it in 2016, when I speculated it might mean we could literally be our own medical record. We’re not at the stage of practical DNA storage yet, and we probably won’t be for many more years, but it’s hard to believe we’re not going to be there eventually. Unlike every other form of recording we’ve come up with, DNA can persist almost indefinitely, and, as long as there are intelligent species based on DNA, they’ll want to read it.

Most importantly, DNA can store a lot of data. As MIT professor Mark Bathe, Ph.D. told NPR: “All the data in the world could fit in the coffee cup that you’re drinking in the morning if it were stored in DNA.”

Mind. Blown.

What prompted me to write about this now was an announcement from Microsoft. Working with researchers from the Molecular Information Laboratory at the University of Washington, their paper demonstrated a “proof of concept” molecular controller that allowed them to write to DNA “three orders of magnitude” – that’s 1000x – denser. As the announcement said: “Ultimately, we were able to use the system to encode a message onto four strands of synthetic DNA, proof that nanoscale DNA writing is possible at dimensions necessary for practical DNA data storage.”

I’ll spare readers the detail of what they did – I don’t pretend to understand it – but the paper concludes:

we project that the technology will scale further to billions of features per square centimeter, enabling synthesis throughput to reach megabytes-per-second levels in a single write module, competitive with the write throughput of other storage devices…We foresee these assemblers being used in other areas like material science, synthetic biology, diagnostics, and closed-loop massive molecular biology experimental assays.

Similarly, the announcement concludes: “we foresee the technology reaching arrays containing billions of electrodes capable of storing megabytes per second of data in DNA. This will bring DNA data storage performance and cost significantly closer to tape.”

You can bet Microsoft is taking this seriously.

———

Lest anyone think only Microsoft is working on this, there have been several other promising developments in recent weeks. Interesting Engineering highlighted a few of them:

• Georgia Tech Research Institute researchers have developed a microchip that allows faster writing to DNA, and expect it to 100x faster than current technologies. Lead researcher Nicolas Guise told BBC that, since DNA can survive so long, “the cost of ownership drops to almost zero.”
• Northwestern University scientists have demonstrated a new “enzymatic system” that encodes three bits of data per hour. The NU announcement explains: “Our method is much cheaper to write information because the enzyme that synthesizes the DNA can be directly manipulated.” The researchers believe the technique could be used to install “molecular recorders” inside cells to act as biosensors; the possibilities are astounding.
• A team at China’s Southeast University used a new process to split content in sequences, rather than one long chain, while “downsizing” the instruments used. TechRadar speculates could lead to the first mass market DNA storage device. Professor Liu Hong told Global Times: “Now we are aiming at the combination of electronic information technology and biology, which might be used in various aspects including data storage and nucleic test for virus.”

Interesting Engineering may have missed the most interesting use yet: Business Insider India reports that Roddenberry Entertainment has created a NFT (non-fungible token) of Gene Roddenberry’s signature on the first Star Trek contract and is storing it on DNA implanted in a bacteria – “ the first-ever living ecological non-fungible token (NFT).”  The bacteria is currently dormant, but if revived it will duplicate the NFT as it reproduces (which sort of goes against what I thought NFTs were).

Somehow I don’t think that’s what the Microsoft researchers were intending DNA storage to accomplish, but, hey, anything for Star Trek.

As Professor Bathe told NPR, if cost/efficacy issues are solved – and they are well on their way – “Then, you know, the sky’s the limit in terms of just storing everything that we ever wanted to and ever will need to.”

———

It’s possible that DNA storage will never get fast enough or cheap enough to replace existing storage methods. It’s possible that some other new technique will emerge that will be even better than DNA storage (e.g., holographic storage?).  But we are DNA-based creatures and the possibility of using the technique that nature builds us with to store and manipulate the data we generate is irresistible. 

There already are DNA-based “robots” and DNA-based computers so, honestly, DNA storage doesn’t surprise me at all. We should be expecting molecular DNA recorders…and trying to anticipate what we do and don’t want them used for.

In the 21^st century, biology is computing, and vice-versa. DNA isn’t just our genetic history and future, but information that we can read and write in. We call it “synthetic biology” now but as the field grows and grows we’re going to forget the “synthetic” part, like “digital health” just becomes “health” (or “cryptocurrency” just becomes “currency”).

Life in the Yottabyte Era is going to be very interesting.

Kim is a former emarketing exec at a major Blues plan, editor of the late & lamented Tincture.io, and now regular THCB contributor.

By ADRIAN GROPPER, MD

US healthcare is exceptional among rich economies. Exceptional in cost. Exceptional in disparities. Exceptional in the political power hospitals and other incumbents have amassed over decades of runaway healthcare exceptionalism. 

The latest front in healthcare exceptionalism is over who profits from patient records. Parallel articles in the NYTimes and THCB frame the issue as “barbarians at the gate” when the real issue is an obsolete health IT infrastructure and how ill-suited it is for the coming age of BigData and machine learning. Just check out the breathless announcement of “frictionless exchange” by Microsoft, AWS, Google, IBM, Salesforce and Oracle. Facebook already offers frictionless exchange. Frictionless exchange has come to mean that one data broker, like Facebook, adds value by aggregating personal data from many sources and then uses machine learning to find a customer, like Cambridge Analytica, that will use the predictive model to manipulate your behavior. How will the six data brokers in the announcement be different from Facebook?

The NYTimes article and the THCB post imply that we will know the barbarians when we see them and then rush to talk about the solutions. Aside from calls for new laws in Washington (weaken behavioral health privacy protections, preempt state privacy laws, reduce surprise medical bills, allow a national patient ID, treat data brokers as HIPAA covered entities, and maybe more) our leaders have to work with regulations (OCR, information blocking, etc…), standards (FHIR, OAuth, UMA), and best practices (Argonaut, SMART, CARIN Alliance, Patient Privacy Rights, etc…). I’m not going to discuss new laws in this post and will focus on practices under existing law.

Patient-directed access to health data is the future. This was made clear at the recent ONC Interoperability Forum as opened by Don Rucker and closed with a panel about the future. CARIN Alliance and Patient Privacy Rights are working to define patient-directed access in what might or might not be different ways. CARIN and PPR have no obvious differences when it comes to the data models and semantics associated with a patient-directed interface (API). PPR appreciates HL7 and CARIN efforts on the data models and semantics for both clinics and payers.

Consider the ongoing news about the data broker called Surescripts and the data processor called Amazon PillPack. The FTC is looking into whether Surescripts used its dominant data broker position illegally in restraint of trade. Surescripts, in a somewhat separate action, is claiming that barbarian PillPack is using patient consent to break down the gate it erected for its business purposes. From my patient perspective, does Surescripts have a right to aggregate my prescription history and then refuse me the ability to share that data with PillPack without special effort? 

The possible differences between CARIN and PPR pertain to how the barbarian is labeled and who maintains the registry or registries of the barbarians. The open questions for CARIN, PPR, and other would-be arbiters of barbary fall into four related categories:

1 – Labels Only

• Labels like the CARIN Code of Conduct or the PPR Information Governance Label are self-asserted by the app or service provider and, like other consumer product labels, would be enforced by the FTC. Who designs the labels?

2 – Registries Only

• For deployment efficiency, the the apps and services may be listed in controlled registries. The app could be registered by the developer of the app or by the operator (including a physician) that wants to use the app. This option is relevant because apps might have options the operator can choose that would change the criteria for a particular registry. Will registries support submissions by developers, operators or both?

• Aside from labels, patients tend to infer reputation on the basis of metrics like the number of users and the number of reviews for an app. Do the registries list software operators along with the software vendors in order to promote transparency and competition?

• Do the registries allow for public comment with or without moderation?

3 – Labels and Registries Combined

• What should be the number of registries and would they require one or more of the available labels?

• A typical app store policy is a low bar to enable maximum competition and reduce disputes over exclusion. Consumer rating bureaus, on the other hand, tend to issue stars or checkmarks in a handful of categories in order to reward excellence. Is our label and registry design aimed at establishing a low bar (“You must be this high to be a barbarian”) or promoting a “race to the top” (such as 0-5 stars in a few defined categories)?

• To improve fairness and transparency, should the orgs that define labels be separate from the orgs that operate registries?

4 – “Without special effort”

• Opening the gate to their own records is an established right for both the patient subject or the barbarian designated by the patient. Making this work “without special effort” requires implementation of standard dynamic client registration features that current gatekeepers have chosen to ignore. Should regulators mandate support for dynamic client registration, for any and all barbarians, as long as the app is only able to access the records of the individual patient exercising their right of access?

It seems that the definition of a barbarian is anyone who aims to get patient records under the current laws and the explicit direction of the patient. The opposite of barbarians, whoever they may be within the gates of HIPAA, are able to get patient records without consent or accounting for disclosures by asserting “Treatment, Payment, or Operations” as well as the pretense of de-identification. Meanwhile, these HIPAA non-barbarians are able to sell off the machine learning and other medical science teachings as “trade secret intellectual property” in the form of computer decision support and other for-profit algorithms. This hospital-led privatization of open medicine will contribute to the next round of US healthcare exceptionalism. 

And as for the patients, no worries; we’ll just tell them it’s about patient safety.

Adrian Gropper, MD, is the CTO of Patient Privacy Rights, a national organization representing 10.3 million patients and among the foremost open data advocates in the country.

By JACOB REIDER

… all rumored to be in the mix to acquire athenahealth.

Nope.

Why not?

a) Apple doesn’t do “verticals.” It’s that easy. Apple sells products that anyone could buy. A teacher, a doctor, my mom. Sure – they have sold high-end workstations that video editors can use, but so could a hobbyist filmmaker. Likelihood of Apple buying athenahealth? ~ .01%

b) Cerner? Nah. While (yes) they have an aging client-server ambulatory EHR that needs to be replaced by a multi-tenant SaaS product (like the one athenahealth cas built), they have too much on their plate right now with DoD and VA and the (incomplete) integration of Siemens customers. Likelihood of Cerner buying athenahealth?  ~ 1%

c) Microsoft. Like Apple, it’s uncommon for MSFT to go “vertical.” They have tried it. (Who remembers the Health Solutions Group?) But the tension between a strong product-focused company that meets the needs of many market segments, and a company that deeply understands the business problems of health (and health care) is too great. The driving force of MSFT, like Apple, is to sell infrastructure to care delivery organizations. Owning a product that competes with their key channel partners would alienate the partners – driving them to AMZN, GOOG and APPL. Likelihood of Microsoft buying athenahealth?  ~ 2%

d) Salesforce. I’d love to see this. But it’s still unlikely. athenahealth has built a product, and they (now) have defined a path to pivot the product into a platform. This is the right thing to do. Salesforce “gets” platform better than everyone (aside from, perhaps, Amazon). But Salesforce has struggled with health care. They’ve declared n times in recent years that they are “in” to really disrupt health care, and with the evolution of Health Cloud, and their acquisition of MuleSoft, they have clearly made some investments here, but the EHR is not the “ERP of healthcare” as they think it is. (Salesforce’s success in other markets has been that they dovetail with – rather than replace – the ERP systems to create value and improve efficiencies.) The way that Salesforce interacts with the market is unfamiliar (and uncomfortable) to most care delivery organizations. So if Salesforce “gets” platform, and athenahealth wants to be a platform when it matures, could these two combine? It’s the most likely of the three, but I still see the cultures of the two companies (I know them both well) as very different, and not quite compatible. Likelihood of Salesforce buying athenahealth?  ~ 10%

e) IBM. yup. I forgot that one. Many recent acquisitions. This would fit. I don’t think it would work very well, but it could happen. ~6%

Others?

a) Philips.  They have enough $$, are getting into population health, have IoT “last mile” business alignment, and understand the need to migrate from FFS to value on a global scale.

b) Roper / Strata. Yeh – you didn’t think of this one! Roper owns Strata Decision.  Cost accounting fits well into the revenue cycle roots of athenahealth. Strata is getting deeper into the role that clinical activity (and deviations from best practice) plays in cost. Dan Michelson (Strata CEO) understands the EHR market incredibly well.

c) Amazon. Platform. ABC. 1492. I’ll say no more. If you don’t know what I’m talking about, LMGTFY.

d) Value Act. Elliott’s not the only big player that may have interest in owning this real estate.

I’m sure there are more. This will be interesting. athenahealth has a vibrant culture, fantastic people, a strong, devoted customer base, and an active developer community.  Remember:  this is a revenue cycle company, not an EHR company. The EHR is a new game they’re playing. It’s an important one, but Todd and Jonathan got into this business with the goal of solving business problems for their customers. That vision remains.  it turns out that a healthier population is (or should be) good for business, and an EHR is (for now) part of that picture. But as the needs of the market evolve, athenahealth will evolve. They’ve demonstrated this well, and this agility is what will cause them to be successful in the long-term.

Jacob Reider is CEO at Alliance for Better Health and former deputy director of ONC. This post was originally published at Docnotes, which is the oldest health care blog. Really!

Health Datapalooza is coming up quick at the end of April, so I sat down with Bruce Greenstein, CTO of HHS about why all of THCB’s health tech friends should attend. Plus, we get into what’s happening with the open data movement and how Bruce’s past-life at Microsoft is going to shape how he and HHS work with those consumer tech companies that are pushing harder and harder into healthcare.

Healthcare is very different from most other industries. It is fragmented, conservative, highly regulated, and hierarchical. It doesn’t follow most of the usual business rules around supply and demand or consumerism. An important aspect of my role at Microsoft is helping my colleagues at the company understand the many ways that healthcare is different from other “businesses”.

Having said that, there are a lot of things that healthcare could learn from a company like Microsoft or other technology companies. When someone asks me what it’s like to work at Microsoft, I often say what someone told me when I started at the company 13 years ago. Microsoft is like a global colony of ants, working independently and yet together but always “neurally” connected by enabling technologies. At any given moment, I can be connected to any one of my 100,000 fellow workers or tens of thousands of partners with just a couple of clicks or taps on a screen. I have tools that show me who’s available, what they do, what they know, and where they are. I can engage in synchronous or asynchronous communication and collaboration activities with a single member or multiple members of my team using messaging, email, voice, video or multi-party web conferencing. We can use business analytics tools, exchange information, review documents, co-author presentations, and collaborate with our customers and partners anywhere in the world from anywhere we might be. Our business moves, and changes, at the speed of light. It is the rhythm of the industry.

I sometimes wake up in the morning and think, “If only my clinical colleagues could avail themselves of similar tools and technologies how different could healthcare be?” I’ve been using information communications technologies in my daily work for so long that I almost take for granted that this is the way work is done. But I also know that in the real world of healthcare the journey is still quite different. That hit home again last week when I asked my mother’s family doctor for a copy of a report on an imaging study he had ordered. It took five phone calls to make something happen and my only choice was to receive the report via fax machine. Fax machine, really?

In my heart I know it is not totally as bleak as it seems sometimes. I could cite numerous examples of hospitals, health systems and clinics around the world that are using our latest technologies to improve health and healthcare delivery. I am well aware of the forces in retail health, specialty and concierge medicine, travel health, tele-health, mobile apps, wearable devices, sensors, remote monitoring, population health and health reform that are disrupting, and will continue to disrupt business as usual in the industry. That disruption can’t happen soon enough, although making significant changes to an industry as large and complicated as healthcare doesn’t happen overnight.

While we wait, I just want clinicians, managers, healthcare executives, and others who work in the healthcare industry to know that there are some readily available technologies that, even today, can significantly improve the way clinicians do their work and healthcare is delivered.