Weekend ‘Must Read’: Are Big Tech/Big Pharma’s health tech promises nothing but a dangerous fraud?

If it sounds too good to be true, it isn’t. And watch your wallet. In 14 words, this summarizes Leeza Osipenko’s theme for this article. It may seem to our Readers that Editor Donna is out there for clicks in the headline, but not really. Dr. Osipenko’s term is ‘snake oil’. It’s a quaint, vintage term for deceptive marketing of completely ineffective remedies, redolent of 19th Century hucksters and ‘The Music Man’. Its real meaning is fraud.

The promise is that Big Data, using Big Analytics, Big Machine Learning, and Big AI, will be a panacea for All That Ails Healthcare. It will save the entire system and the patient money, revolutionize medical decision making, save doctors time, increase accuracy, and in general save us from ourselves. Oh yes, and we do need saving, because our Big Tech and Big Health betters tell us so!

Major points in Dr. Osipenko’s Project Syndicate article, which is not long but provocative. Bonus content is available with a link to a London School of Economics panel discussion podcast (39 min.):

  • Source data is flawed. It’s subject to error, subjective clinical decision-making, lack of structure, standardization, and general GIGO.
  • However, Big Data is sold to health care systems and the general public like none of these potentially dangerous limitations even exist
  • Where are the long-range studies which can objectively compare and test the quality and outcomes of using this data? Nowhere to be found yet. It’s like we are in 1900 with no Pure Food Act, no FDA, or FTC to oversee.
  • It is sold into health systems as beneficial and completely harmless. Have we already forgotten the scandal of Ascension Health, the largest non-profit health system in the US, and Google Health simply proceeding off their BAA as if they had consent to identified data from practices and patients, and HIPAA didn’t exist? 10 million healthcare records were breached and HHS brought it to a screeching halt.
    • Our TTA article of 14 Nov 19 goes into why Google was so overeager to move this project forward, fast, and break a few things like rules.
  • We as individuals have no transparency into these systems. We don’t know what they know about us, or if it is correct. And if it isn’t, how can we correct it?
  • “Algorithmic diagnostic and decision models sometimes return results that doctors themselves do not understand”–great if you are being diagnosed.
  • Big Data demands a high level of math literacy.  Most decision makers are not data geeks. And those of us who work with numbers are often baffled by results and later find the calcs are el wrongo–this Editor speaks from personal experience on simple CMS data sets.
  • In order to be valuable, AI and machine learning demand access to potentially sensitive data. What’s the tradeoff? Where’s the consent?

Implicit in the article is cui bono?

  • Google and its social media rivals want data on us to monetize–in other words, sell stuff to us. Better health and outcomes are just a nice side benefit for them.
  • China. Our Readers may also recall from our April 2019 article that China is building the world’s largest medical database, free of those pesky Western democracy privacy restrictions, and using AI/machine learning to create a massive set of diagnostic tools. They aren’t going to stop at China, and in recent developments around intellectual property theft and programming back doors, will go to great lengths to secure Western data. Tencent and Fosun are playing by Chinese rules.

In conclusion:

At the end of the day, improving health care through big data and AI will likely take much more trial and error than techno-optimists realize. If conducted transparently and publicly, big-data projects can teach us how to create high-quality data sets prospectively, thereby increasing algorithmic solutions’ chances of success. By the same token, the algorithms themselves should be made available at least to regulators and the organizations subscribing to the service, if not to the public.

and

Having been massively overhyped, big-data health-care solutions are being rushed to market in without meaningful regulation, transparency, standardization, accountability, or robust validation practices. Patients deserve health systems and providers that will protect them, rather than using them as mere sources of data for profit-driven experiments.

Hat tip to Steve Hards.

Symptom checker K Health gains $48 million Series C (NY/Tel Aviv)

While we’re on the subject of symptom checkers (Babylon Health below), K Health, a competitor in the US HQ’d in NYC, but also based in Tel Aviv, announced today their win of $48 million in a Series C funding round, led by 14W and Mangrove Capital Partners. Lerer Hippeau, Anthem (also a partner), Primary Ventures, and others participated. Their total funding is $97 million since November 2016. The new funding, according to Crunchbase News, will be used to scale the model, expand primary care to mobile devices, and expand to international markets. 

K (as they call themselves) concentrates on three areas. One is an AI-powered symptom checker that uses millions (they state) of anonymized medical records to provide a virtual consult. According to Crunchbase, the medical records came from Israel’s second-largest HMO, Maccabi, over 20 years. The app questions the user based on previous answers. K contrasts it to static protocols, or rules-based symptom checking. The second is to provide a primary care visit via text for $19/visit (or unlimited for $39/year) with free follow-ups over two weeks. The third is mental health, specifically treatment for anxiety and depression, a growing area both online and via mobile. The $29/month fee covers unlimited doctor visits and delivered prescription medication, excepting meds that require blood testing.

The symptom checker is available throughout the US and primary care in 47 states. According to Crunchbase’s interview with CEO Allon Bloch, they recently passed their 3 millionth user and are now available in Spanish. The company has grown in the past year from 80 to 200 people. Originally, the company linked to New York-based providers, but moved away from that to the primary care/text model. Their overall goal is to provide affordable diagnoses that are a lot more accurate than ‘Dr. Google’ and that steer the patient to the right care.

Should Babylon Health be serious about expansion to the US, they will be running up against K Health, as well as competitors such as 98point6. In the hybrid app-and-physical model, there are Carbon Health and One Medical. Also Mobihealthnews 

The confusion within TEC/telehealth between machine learning and AI-powered systems

Defining AI and machine learning terminology isn’t academic, but can influence your business. In reading a straightforward interview about the CarePredict wearable sensor for behavioral modeling and monitoring in an AI-titled publication, this Editor realized that AI–artificial intelligence–as a descriptor is creeping into all sorts of predictive systems which are actually based on machine learning. As TTA has written about previously [TTA 21 Aug], there are many considerations around AI, including the quality of the data being fed into the system, the control over the systems, and the ability to judge the output. Using the AI term sounds so much more ‘techie’–but it’s not accurate.

Artificial intelligence is defined as the broader application of machines being able to carry out tasks in a ‘smart’ way. Machine learning is tactical. It’s an application that assumes that we give the machine access to data and let the machine ‘learn’ on its own. Neural networks in computer design have made this possible. “Essentially it works on a system of probability – based on data fed to it, it is able to make statements, decisions or predictions with a degree of certainty.”, as stated in this Forbes article by Bernard Marr.

CarePredict has been incorporating many aspects of machine learning, particularly in its interface with the wrist-worn wearable and its interaction with sensors in a residence. It gathers more over time than older systems like QuietCare (this Editor was marketing head) and with more data, CarePredict does more and progressed beyond the relatively simple algorithms that created baselines in QuietCare. They now claim effective fall detection, patterns of grooming and feeding, and environment. (Disclosure: this Editor did freelance writing for the company in 2017)

In wishing CEO Satish Movva much success, this Editor believes that using AI to describe his system should be used cautiously. It makes it sound more complicated than it is to a primarily non-techie, senior community administrative and clinical audience. Say what you do in plain language, and you won’t go wrong. AI for Healthcare: Interview with Satish Movva, Founder & CEO of CarePredict

 

Are AI’s unknown workings–fed by humans–creating intellectual debt we can’t pay off?

Financial debt shifts control—from borrower to lender, and from future to past. Mounting intellectual debt may shift control, too. A world of knowledge without understanding becomes a world without discernible cause and effect, in which we grow dependent on our digital concierges to tell us what to do and when.

Debt theory and AI. This Editor never thought of learning exactly how something works as a kind of intellectual paydown of debt on what Donald Rumsfeld called ‘known unknowns’–we know it works, but not exactly how. It’s true of many drugs (aspirin), some medical treatments (deep brain stimulation for Parkinson’s–and the much-older electroconvulsive therapy for some psychiatric conditions), but rarely with engineering or the fuel pump on your car. 

Artificial intelligence (AI) and machine learning aren’t supposed to be that way. We’re supposed to be able to control the algorithms, make the rules, and understand how it works. Or so we’ve been told. Except, of course, that is not how machine learning and AI work. The crunching of massive data blocks brings about statistical correlation, which is of course a valid method of analysis. But as I learned in political science, statistics, sports, and high school physics, correlation is not causality, nor necessarily correct or predictive. What is missing are reasons why for the answers they provide–and both can be corrupted simply by feeding in bad data without judgment–or intent to defraud.

Bad or flawed data tend to accumulate and feed on itself, to the point where someone checking cannot distinguish where the logic fell off the rails, or to actually validate it. We also ascribe to AI–and to machine learning in its very name–actual learning and self-validation, which is not real. 

There are other dangers, as in image recognition (and this Editor would add, in LIDAR used in self-driving vehicles):

Intellectual debt accrued through machine learning features risks beyond the ones created through old-style trial and error. Because most machine-learning models cannot offer reasons for their ongoing judgments, there is no way to tell when they’ve misfired if one doesn’t already have an independent judgment about the answers they provide.

and

As machines make discovery faster, people may come to see theoreticians as extraneous, superfluous, and hopelessly behind the times. Knowledge about a particular area will be less treasured than expertise in the creation of machine-learning models that produce answers on that subject.

How we fix the balance sheet is not answered here, but certainly outlined well. The Hidden Costs of Automated Thinking (New Yorker)

And how that AI system actually gets those answers might give you pause. Yes, there are thousands of humans, with no special expertise or medical knowledge, being trained to feed the AI Beast all over the world. Data labeling, data annotation, or ‘Ghost Work’ from the book of the same name, is the parlance, includes medical, pornographic, commercial, and grisly crime images. Besides the mind-numbing repetitiveness, there are instances of PTSD related to the images and real concerns about the personal data being shared, stored, and used for medical diagnosis. A.I. Is Learning from Humans. Many Humans. (NY Times)

News roundup: docs dim on AI without purpose, ‘medtail’ a mall trend, CVS goes SDH, Kvedar to ATA, Biden ‘moonshot’ shorts out, and Short Takes

Docs not crazy about AI. And Dog Bites Man. In Medscape‘s survey of 1,500 doctors in the US, Europe, and Latin America, they are skeptical (49 percent-US) and uncomfortable (35 percent-Europe, 30 percent-Latin America). Only 20 percent fess up to actually using an AI application, and aren’t crazy about voice tech even at home. Two-thirds are willing to take a look at AI-powered tech if it proves to be better than humans at diagnosis, but only 44 percent actually believe that will happen. FierceHealthcare

This dim view, in the estimation of a chief analytics and information officer in healthcare, Vikas Chowdhry, is not the fault of AI nor of the doctors. There’s a disconnect between the tech and the larger purpose. “Without a national urgency to focus on health instead of medical care, and without scalable patient person-centered reforms, no technology will make a meaningful impact, especially in a hybrid public goods area like health.” The analogy is to power of computing–that somehow when we focused behind a goal, we were able to have multiple moon missions with computing equivalent to a really old smartphone, but now we send out funny cat videos instead of being on Mars. (And this Editor growing up in NJ thought the space program was there to market Tang orange drink.) HIStalk.

Those vacant stores at malls? Fill ’em with healthcare clinics! And go out for Jamba Juice after! CNN finally caught up with the trend, apparent on suburbia’s Boulevards and Main Streets, that clinics can fill those mall spots which have been vacated by retail. No longer confined to ‘medical buildings’, outpatient care is popping up everywhere. In your Editor’s metro area, you see CityMDs next to Walmarts, Northwell Health next to a burger spot, a Kessler Health rehab clinic replacing a dance studio, and so on. The clever name for it is ‘medtail’, and landlords love them because they sign long leases and pay for premium spots, brighten up dim concourses, and perhaps stimulate food court and other shopping traffic. Of course, CVS and Aetna spotted this about years ago in their merger but are working expansion in the other direction with expanding CVS locations and on the healthcare side, testing the addition of social determinants of health (SDH) services via a pilot partnership, Destination: Health with non-profit Unite Us to connect better with community services. This is in addition to previous affordable housing investments and a five-year community health initiative. Forbes, Mobihealthnews

ATA announces Joseph Kvedar, MD, as President-Elect. Dr. Kvedar was previously president in 2004-5 and replaces John Glaser, PhD, Executive Senior Advisor, Cerner. He will remain as Vice President of Connected Health at Partners HealthCare and Professor of Dermatology at Harvard Medical School. A question mark for those of us in the industry is his extensive engagement with October’s Connected Health Conference in Boston, one of the earliest and now a HIMSS event. ATA’s next event is ATA2020 3-5 May 2020 in Phoenix–apparently no Fall Forum this year.

The Biden Cancer Initiative has shut down after two years in operation. This spinoff of the White House-sponsored ‘moonshot’ initiative was founded after the death of Beau Biden, son of Democrat presidential candidate Joe Biden. Both Mr. Biden and wife Jill Biden withdrew due to ethics concerns in April. According to Fortune, the nonprofit had trouble maintaining momentum without their presence. However, the setup invited conflict of interest concerns. The Initiative engaged and was funded by pharmas and other health tech companies, directly for Initiative support but mainly for indirect pledges to fund research. Most of these organizations do business with Federal, state and local governments. Shortly after the formal announcement, Mr. Biden the Candidate announced a rural health plan to expand a federal grant program to include rural telehealth for mental health and specialized services. Politico   But isn’t that already underway with the FCC’s Connected Care Pilot Program, coming to a vote soon? [TTA 20 June]

And…Short Takes

  • Philips Healthcare bought Boston-based patient engagement/management start-up Medumo. Terms not disclosed. CNBC
  • London’s Medopad launched with Royal Wolverhampton NHS Trust (RWT) in a three-year RPM deal. DigitalHealthNews
  • Parks Associates’ Connected Health Summit will be again in San Diego 27-29 August with an outstanding lineup of speakers. More information and registration here.

And in other news, Matt Hancock holds tight to his portfolio as UK Secretary of State for Health and Social Care in the newly formed Government under new PM Boris Johnson. Luckier than the other 50 percent!

 

 

Comings & goings: The TeleDentists go DTC, gains Reis as CEO; University of Warwick spinoff Augmented Insights debuts (UK); a new CEO leads GrandCare Systems

The TeleDentists leap in with a new CEO. A year-old startup, The TeleDentists, has announced it will be going direct-to-consumer with teledentistry consults. This will permit anyone with a dental problem or emergency to consult with a dentist 24/7, schedule a local appointment in 24-48 hours. and even, if required, prescribe a non-narcotic prescription to a local pharmacy. Cost for the DTC service is not yet disclosed. Currently, the Kansas City-based company has provided their dental network services through several telehealth and telemedicine service providers such as Call A Doctor Plus as well as several brick-and-mortar clinic locations.

If dentistry sounds logical for telemedicine, consider that about 2 million people annually in the US use ERs for dental emergencies; 39 percent didn’t visit a dentist last year. Yet teledentistry is just getting started and is unusually underdeveloped, if you except the retail tooth aligners. Several US groups are piloting it to community health and underserved groups, with Philips reportedly considering a trial in Europe (mHealth Intelligence). This Editor notes that on their advisory board is a co-founder of Teladoc.  Release

The TeleDentists’ co-founder, Maria Kunstadter, DDS, last week announced the arrival of a new company CEO, Howard Reis. Mr. Reis started with health tech back in the 1990s with Nynex Science and Technology piloting telemedicine clinical trials at four Boston hospitals, which qualifies him among the most Grizzled Pioneers. He also was business development VP for Teleradiology Specialists and founding partner of The Castleton Group, a LTC telehealth company, and has worked in professional services for Accenture, Telmarc and SAIC/Bellcore. Most recently, he started teleradiology/telehealth firm HealthePractices. Over the past few years, Mr. Reis has also been prominent in the NY metro digital health scene. Congratulations and much success!  

In the UK, the University of Warwick has unveiled a spinoff, Augmented Insights Ltd. AI will be concentrating on machine learning and AI services that analyze long term health and care data, automating the extraction in real time of personalized, predictive and preventative insights from ongoing patient data. It will be headed by Dr. James Amor, whom this Editor met last summer in NYC. Long term plans center on marketing their analytics services to tech providers. Interested parties or potential users may contact Dr. Amor in Leamington Spa at James@augmentedinsights.co.uk |Congratulations to Dr. Amor and his team! 

And in more Grizzled Pioneer news, there’s a new CEO at GrandCare Systems who’s been engaged with the company since nearly their start in 1993 and in its present form in 2005. Laura Mitchell takes the helm as CEO after various positions there including Chief Marketing Officer and several years leading her own healthcare and marketing consulting firm. Nick Mitchell rejoins as chief technology officer and lead software developer. Founders Charlie Hillman remain as an advisor and Gaytha Traynor as COO. Their offices have also moved to the Kreilkamp Building, 215 N Main Street, Suite 130, in downtown West Bend Wisconsin. GrandCare remains a ‘family affair’ as this profile notes. Congratulations–again!

AI and machine learning ‘will transform clinical imaging practice over the next decade’

The great challenges in radiology are accuracy of diagnosis and speed. Yet for radiology, machine learning and AI systems are still in early stages. Last August, a National Institutes of Health (NIH)-organized workshop with the Radiological Society of North America (RSNA), the American College of Radiology (ACR) and The Academy for Radiology and Biomedical Imaging Research (The Academy) kickstarted work towards AI. Their goal was to collaborate in machine learning/AI applications for diagnostic medical imaging, identify knowledge gaps, and to roadmap research needs for academic research laboratories, funding agencies, professional societies, and industry.

The report of this roadmap was published in the past few days in Radiology, the RSNA journal. Research priorities in the report included:

  • new image reconstruction methods that efficiently produce images suitable for human interpretation from source data
  • automated image labeling and annotation methods, including information extraction from the imaging report, electronic phenotyping, and prospective structured image reporting
  • new machine learning methods for clinical imaging data, such as tailored, pre-trained model architectures, and distributed machine learning methods
  • machine learning methods that can explain the advice they provide to human users (so-called explainable artificial intelligence)
  • validated methods for image de-identification and data sharing to facilitate wide availability of clinical imaging data sets.

Another aim is to reduce clinically important errors, estimated at 3 to 6 percent of image interpretations by radiologists. Diagnostic errors play a role in up to 10 percent of patient deaths, according to this report.

It is interesting that machine learning, more than AI, is mentioned in the RSNA materials, for instance in stating that “Machine learning algorithms will transform clinical imaging practice over the next decade. Yet, machine learning research is still in its early stages.” Radiology actually pioneered store-and-forward technology, to where radiology interpretation has been farmed out nationally and globally for many years. This countered a decline in US radiologists as a percentage of the physician workforce that started in the late 1990s and continues to today with some positive trends (Radiology 2015). Perhaps this distribution model postponed development of machine learning technologies. Also Healthcare Dive, RSNA press release  

Babylon Health’s expansion plans in Asia-Pacific, Africa spotlighted

Mobihealthnews’ interview with Ali Parsa of Babylon Health illuminates what hasn’t been obvious about the company’s global plans, in our recent focus on their dealings with the NHS. For its basic smartphone app (video consults, appointments, medical records), Babylon last year announced a partnership with one of Asia’s largest health insurers, Prudential [TTA 18 Sept 18], licensing Babylon’s software for its own health apps across 12 countries in Asia for an estimated $100 million over several years. Babylon has also been active in Rwanda and now reaches, according to their information, nearly 30 percent of the population. There’s also a nod to developments with the NHS.

Parsing the highlights in Dr. Parsa’s rather wordy quest towards less ‘sick care’, more ‘prevention over cure’, and making healthcare affordable and accessible to everyone ’round the clock:

  • Asia-Pacific: Working with Tencent, Samsung and Prudential Asia through licensing software is a key component of their business. By adding more users, they refine and add more quality to their services. (Presumably they have more restrictions on the data they send to Tencent than what they obtain in China.)
  • Africa: How do you offer health apps in an economically poor country where only 5 percent of the population has a smartphone? Have an app that works for the 75 percent who have a feature phone. Babyl Rwanda has 2 million users–30 percent of Rwanda’s population–and completes 2,000 consultations a day. Babyl also works with over 450 health clinics and pharmacies. The service may also be expanded across East Africa, and may serve as a model for similar countries in other regions.
  • UK and NHSX: About the new NHS-formed joint organization for digital services, tech, and clinical care, Dr. Parsa believes it is ‘fantastic’ and that “it is trying to bring the benefits of modern technology to every patient and clinician, and aims to combine the best talent from government, the NHS and industry. Its aim, just like ours, is to create the most advanced health and care service in the world, to free up staff time and empower patients.” (Editor’s note:  NHSX will bring together the Department of Health and Social Care, NHS England and NHS Improvement, overseeing NHS Digital. More in Digital Health, Computer Weekly.)

China’s getting set to be the healthcare AI leader–on the backs of sick, rural citizens’ data privacy

Picture this: a mobile rural health clinic arrives at a rural village in Jia County, in China’s Henan province. The clinic staff check the villagers, many of them elderly and infirm from their hard-working lives. The staff collect vital signs, take blood, urine, ECGs, and other tests. It’s all free, versus going to the hospital 30 miles away.

The catch: the data collected is uploaded to WeDoctor, a private healthcare company specializing in online medical diagnostics and related services that is part of Tencent, the Chinese technology conglomerate which is also devoted to AI. All that data is uploaded to WeDoctor’s AI-powered cloud. The good part: the agreement with the local government that permits this also provides medical services, health insurance, pharmaceuticals and healthcare education to the local people. In addition, it creates a “auxiliary treatment system for general practice” database that Jia County doctors can access for local patients. According to the WIRED article on this, it’s impressive at an IBM Watson level: 

Doctors simply have to input a patient’s symptoms and the system provides them with suggested diagnoses and treatments, calculated from a database of over 5,000 symptoms and 2,000 diseases. WeDoctor claims that the system has an accuracy rate of 90 per cent.

and 

Dr Zhang Qiaofen, in nearby Ren Zhuang village, says the system it has made her life easier. “Since WeDoctor came to my clinic, I feel more comfortable and have more confidence,” she says. “I’m thankful to the device for helping me make decisions.”

The bad part: The patients have no consent or control over the data, nor any privacy restrictions on its use by WeDoctor, Tencent, or the Chinese government. Regional government officials are next pictured in the article reviewing data on Jia County’s citizens: village, gender, age, ailment and whether or not a person has registered with a village health check. Yes, attending these health checks is mandatory for the villagers. 

What is happening is that China is building the world’s largest medical database, free of those pesky Western democracy privacy restrictions, and using AI/machine learning to create a massive set of diagnostic tools. The immediate application is to supplement their paucity of doctors and medical facilities (1.5 doctors per 1,000 people compared to almost double in the UK). All this is being built by an estimated 130 private companies as part of the “Made in China 2025” plan. Long term, the Chinese government gets to know even more intimate details about their 1.3 billion citizens. And these private companies can make money off the data. Such a deal! The difference between China’s attitude towards privacy and Western concerns on same could not be greater.  More on WeDoctor’s ambitions to be the Amazon of healthcare and yes, profit from this data, from Bloomberg. WeDoctor is valued at an incredible $5.5 billion. Hat tip to HISTalk’s Monday morning update.

A selection of short digital health items of potential interest

Editor Charles has taken time off recently from assessing mHealth apps to give us a selection of short news items and event notifications.

CE and FDA certification

This editor recently stumbled over the first list he’s ever seen of approved digital health medical devices. As of today there are some 151 products on there which is hugely impressive. One of the reasons for the relatively poor showing of CE certifications on the list is that there is no official list yet: latest forecasts for Eudamed, which will provide this, are Spring 2020 amid much uncertainty about whether enough Notified Bodies will be approved to certify to the MDR in time. Immediately spotted as a CE certification missing is Walk with Path’s Path Finder device for helping people with Parkinson’s to avoid a freezing of their gait (though CE certification is well hidden on their website) and doubtless there are others. Clearly the list points up potential benefits were it ever possible to harmonise the approval process across the Pond.

Longevity 

The first Longevity Leaders event took place on Monday, perhaps the first large event in the UK on that topic. Based on the enthusiasm of attendees, clearly it won’t be the last. Doubtless in due course it will fragment into a myriad of specialist topics though currently it is a fascinating combination of almost every medical/pharmaceutical and digital discipline, plus housing and a range of other considerations. Timescales varied widely too – for example I talked about the immediate benefits of digital health including keeping people in their own homes, thus minimising sarcopenia from being confined to a hospital bed and avoiding exacerbating dementia by a change of environment, whereas others spoke of how best to make DNA immortal and whether the first person destined to live to 1000 had already been born.

Clinical  Homecare

From the sublime (last item) to the The National Clinical Homecare Association‘s conference on 31st January, where this Editor also spoke on how digital health could help people to be treated in their own homes. Notable was the absence of any Twitter handle for the Association, no hashtag for the conference and just two people it seemed out of 250 using social media. Clearly there are huge opportunities here for digital health suppliers, particularly as so much of what was said by other speakers, and what was being shown in the exhibition was very much manually-intensive stuff: join the NCHA and start a revolution in clinical homecare! 

Recent developments in AI

Since this editor stopped active involvement in conference organisation for the Royal Society of Medicine it is encouraging to see that the younger generation has picked up the baton and is running even harder, such that the above event, on 26th February, has proved so popular that it has been moved to the largest (300 seater) lecture theatre at the Society, and on current sign-up rate will sell out.  Speakers from Babylon, Ada Health, DeepMind, Kheiron Medical, BenevolentAI, UCL Life Sciences & Alan Turing AI partnership, and many more will ensure that delegates gain a comprehensive understanding of how AI is being used across healthcare. Book here to experience the delights of the new RSM all-new website which makes signing up for an event so much easier than in the past. Fear not though: the RSM’s legendary low ticket costs are maintained!

Wayra and Novartis

A most exciting event this week was the announcement of the joint Wayra and Novartis health call now looking for their next cohort of remarkable start-ups to join their new programme called The Health Hub. This is built together with their new partner Novartis, one of the leading pharma companies. Their focus is on how healthtech can be used drastically to innovate long-term disease management. Apply here, by February 17th. Hat tip to Professor Mike Short for this item and other observations in this post .

Rewired Pitchfest

Early health tech entrepreneurs should consider taking part in the Rewired Pitchfest at the Digital Health Rewired Conference and Exhibition, Olympia London on 26 March. Sponsored by Silver Buck, this provides the opportunity for early stage digital health start-ups to showcase their disruptive ideas and prototypes to NHS IT leaders. Applicants will compete before a judging panel featuring investors and successful start-up founders. It’s a great way to gain significant exposure and make connections with a diverse range of UK digital health leaders…and the winner will be announced, and congratulated, by Matt Hancock himself! There is also the chance of winning a mentoring programme with the experts on the judging panel and PR features in Digital Health News. (Disclosure: this editor is on the Programme Committee of Rewired, as well as being a Pitch judge)

Punning headlines

It’s rare that a single item is worthy of its own paragraph on TTA these days however an exception must surely be made for one of the few punning headlines to be found in digital health, especially as it’s for such an old – and until now undelivered – idea: “Smart toilet seat is flush with possibilities to monitor patients’ health”

News roundup: Virginia includes RPM in telehealth, Chichester Careline changes, Sensyne AI allies with Oxford, Tunstall partners in Scotland, teledermatology in São Paolo

Virginia closes in on including remote patient monitoring in telehealth law. Two bills in the Virginia legislature, House Bill 1970 and Senate Bill 1221, include remote patient monitoring (RPM) within their present telehealth and telemedicine guidelines and payment in state commercial insurance and the commonwealth’s Medicaid program. It is currently moving forward in House and Senate committees with amendments and. RPM is defined as “the delivery of home health services using telecommunications technology to enhance the delivery of home health care, including monitoring of clinical patient data….” Both were filed on 9 January. Virginia was an early adopter of parity payment of telemedicine with in-person visits. The University of Virginia has been a pioneer in telehealth research and is the home for the Mid-Atlantic Telehealth Resource Center. mHealth Intelligence

Chichester Careline switches to PPP Taking Care. Chichester Careline is currently a 24/7 care line services provided by Chichester District Council. Starting 1 March, PPP Taking Care, part of AXA PPP Healthcare, will manage the service. According to the Chichester release, costs will remain the same, technology will be upgraded, and telecare services will be added. Over the past 35 years, Chichester Careline has assisted over 1 million people across Britain. 

Sensyne collaborates with University of Oxford’s Big Data Institute (BDI) on chronic disease. The three-year program will use Sensyne’s artificial intelligence for research on chronic kidney disease and cardiovascular disease. Sensyne analyzes large databases of anonymized patient data in collaboration with NHS Trusts. BDI’s expertise is in population health, clinical informatics and machine learning. Their joint research will concentrate on two major elements within long-term chronic disease to derive new datasets: automating physician notes into a structure which can be analyzed by AI and integrating it into remote patient monitoring.  Release.

Tunstall partners with Digital Health & Care Institute Scotland. The partnership is in the Next Generation Solutions for Healthy Ageing cluster. Digital Health & Care supports the Scottish Government’s TEC Programme and the Digital Telecare Workstream. The program’s goals are to help Scots live longer, healthier lives and also create jobs.  Building Better Healthcare UK

Teledermatology powered by machine learning helps to solve a specialist shortage in São Paolo. Brazil has nationalized healthcare which has nowhere near enough specialists. São is a city with 20 million inhabitants, so large and spread out that when the aircraft crew announces that they are on approach to the airport, it takes two hours to touch the runway. The dermatology waitlist was up to 60,000 patients, each waiting 18 months to see a doctor. The solution: call every patient and instruct them to go to a doctor or nurse to take a picture of the skin condition. The photo is then analyzed and prioritized by an algorithm, with a check by dermatologists, to determine level of treatment. Thirty percent needed to see a dermatologist, only 3 percent needed a biopsy. Accuracy level is about 80 percent, and plans are in progress to scale it to the rest of Brazil. Mobihealthnews.

UK’s DeepMind loses Streams, health projects to Google Health

DeepMind loses its Health to Google. DeepMind, the London-based AI developer acquired by Alphabet (Google) in 2014, no longer has a Health division. This group will be absorbed by Google Health, now headed by ex-Geisinger CEO David Feinberg. The former DeepMind health team will continue to be headed by former NHS surgeon Dr Dominic King, who will remain in London along with about 100 reported staffers, at least for now.

DeepMind’s major health initiative is Streams, an AI-powered mobile app that analyzes potential deterioration in patients and alerts nurses and doctors, saving time. It also monitors vital signs and integrates different types of data and test results from existing hospital IT systems. Streams is currently deployed at Royal Free NHS Foundation Trust Hospital in north London for acute kidney injury. The rollout is expected to be made at Imperial College Healthcare NHS Trust, Taunton and Somerset NHS Foundation Trust and Yeovil District Hospital NHS Foundation Trust. It is expected that test partners will be found outside of the UK.

DeepMind’s other health initatives and research include fast eye disease detection, planning cancer radiotherapy treatment in seconds rather than hours; and detecting patient deterioration from electronic records.

Google Health is now expanding into products and research into digital technologies which was to be expected with Dr Feinberg on board. Currently, its revenue stream consists of advertising and search.

The remainder of DeepMind not engaged with health will remain independent. CNBC, DeepMind blog

Is Babylon Health’s AI on par with a human diagnostician? Claim questioned in ‘The Lancet’.

In July, Babylon Health released the results of their testing against the MRCGP (Member of the Royal College of General Practitioners) exam based on publicly available questions. As we reported at the time, its AI system passed the exam with a score of 81 percent. A separate test where Babylon worked with the Royal College of Physicians, Stanford University and Yale New Haven Health subjected Babylon and seven primary care physicians to 100 independently-devised symptom sets. Babylon passed with an 80 score.

Now these results are being questioned in a letter to The Lancet. The authors–a medical doctor and two medical informatics academics–argue that the methodology used was questionable. ‘Safety of patient-facing digital symptom checkers’  shows there ‘is a possibility that it [Babylon’s service] might perform significantly worse’. The symptom checking methodology was questioned for not being real world–that the data in the latter test was entered by doctors only, not by patients or other clinicians. While the authors commended Babylon for being open about their research, they felt there was an “urgent need” for improvements in evaluation methods. “Such guidelines should form the basis of a regulatory framework, as there is currently minimal regulatory oversight of these technologies.” Babylon promises a response and additional improvements, presumably from its $100 million investment in AI announced in SeptemberDigitalHealth (UK), Mobihealthnews

Pepper pays a first-ever robot visit to Commons on the future of AI and robotics on education, older adult care (UK)

[grow_thumb image=”http://telecareaware.com/wp-content/uploads/2018/10/103886629_mediaitem103886628.jpg” thumb_width=”150″ /]Pepper paid a visit to a House of Commons select committee on education and became the very first robot to meet with MPs. Accompanied by students from Middlesex University, where Pepper is part of an initiative on teaching primary school-level children, he made a short presentation about the future of artificial intelligence in education and older adult care.

Certainly his introduction has some historic value. Pepper bowed and then said in his rather high-pitched and somewhat Japanese-inflected voice: “Good morning, chair [Robert Halfon]. Thank you for inviting me to give evidence today. My name is Pepper and I am a resident robot at Middlesex University.”

Pepper used voice, gesture, and his embedded front tablet to explain about the role robots like him will play in education and healthcare. At Middlesex, final year students in robotics, education, psychology, and biomedicine like Joana Miranda, one of his two escorts, work with Pepper on projects such as developing numeracy skills in primary school students. According to BBC News, Tory MP Lucy Allan dryly noted that Pepper was “better than some of the ministers we have had before us”.

In healthcare for older adults, the Pepper robot developed by Softbank is part of a major research project funded by the EU, the Japanese Government and UK’s Horizon 2020. The objective of the three-year CARESSES program is to develop a culturally aware robot to provide care suited to a wide variety of individuals and reduce loneliness. Another desired outcome is to relieve pressure in hospitals and care homes by promoting independent living at home with a care robot.

The education committee is examining the “fourth industrial revolution” which impacts STEM education, school curriculum, and workforce skills (and reskilling). Videos on BBC News and Gevul News (YouTube) A tart take on Pepper versus PM Theresa May from The Guardian. (And no fainting, as Pepper did at CES earlier this year.) Hat tip to The King’s Fund weekly newsletter.

Connected Health Conference highlights (so far): FCC’s $100 million telehealth pilot, NIH’s ‘All of Us’, MIT’s social robots integrating AI

Expanding FCC connected health programs. FCC Chairman Ajit Pai in his keynote reinforced the agency’s interest and support of connected health initiatives, from rural to opioids. Most of the programs have a rural focus to bring broadband and telehealth/RPM to the ‘end of the line’ in underserved communities, something close to Mr. Pai’s heart as his parents were both rural physicians in Kansas..

  • This summer, the Connected Care Pilot Program was proposed and approved unanimously in August [TTA 9 Aug]. Funding for this is proposed at $100 million.
  • The spending cap for the rural healthcare program, which has been around since 1997’s dial-up days and now includes telemedicine and remote monitoring, was increased for 2017-2018 from  $400 million to $571 million, a 43 percent increase. The FCC has pledged to fully fund 2018 programs.
  • New initiatives were announced covering new uses for telehealth and remote patient monitoring:
    • Connected care at home via RPM as part of the Connected Care Pilot Program
    • Cancer care in partnership with the National Cancer Institute. The Launch program for rural and underserved communities aims to bring high-quality cancer care to where patients work and live through bringing together government, academia and community health providers.
    • For opioids, there are two programs. One is expanding the mapping broadband health platform to include critical drug use data. This will allow users to rapidly visualize, overlay, and analyze broadband and opioid data together at the national, state, and county level. The second is to launch a chronic pain management and opioid use challenge as part of the pilot program.  Mobihealthnews

A status report on NIH’s All of Us. Back in January as part of setting the stage for 2018, this Editor briefly mentioned the National Institute of Health’s massive All of Us program, part of the Federal Precision Medicine Initiative (PMI). All of Us needs almost all of us–their goal is to collect data on at least one million Americans for a major leap forward on data supporting population health. Dr. Dara Richardson-Heron, All of Us’ chief engagement officer, confirmed that over 100,000 participants have registered since the launch in May, with over 65,000 completing the full protocol. She mentioned that 75 percent of signups are from groups often underrepresented in modern medical research, with 50 percent from racial and ethnic minorities. The Mobihealthnews article ends on a ‘Debbie Downer’ note of doubting whether the program will reach enrollment goals, the cost will be justified, and whether the data will be kept private as promised.

MIT’s social robots may be the future of emotional support for wellbeing. MIT associate professor Cynthia Breazeal heads up the Personal Robots Group and is working on how to integrate AI into emotional robots for pediatric patients at Boston Children’s Hospital. The robots serve as a go-between child life specialists and the patient. The initial results were positive, with higher verbal scores (as a measure of engagement) than with stuffed bears or digital avatars. Professor Breazeal wants to extend the technology to older adults for wellbeing and engagement. Running against the conventional wisdom, their research found that older adults were more open to technology than the children. Following MIT’s work are companies like Hasbro and Embodied. Mobihealthnews.

The Theranos Story, ch. 57: was it Silicon Valley and Startup Culture bad practices pushed to the max?

[grow_thumb image=”http://telecareaware.com/wp-content/uploads/2018/07/Rock-1-crop-2.jpg” thumb_width=”125″ /]Theranos is now formally in California insolvency proceedings (note on their website). Creditors may have enough awarded to them to go down to the local pizzeria to buy a slice or two. Hard lessons indeed for creditors and shareholders. But aside from the drama yet to come in the trial of Elizabeth Holmes and Sunny now Shady Balwani, a/k/a the Silicon Valley Trial of the Century, are there any further lessons to be learned?

For those of us who have not been closely following The Theranos Story, David Shaywitz’s kind-of-review of John Carreyrou’s Bad Blood coupled with a thought piece in Forbes is especially appealing. Even if you’ve been tracking it closely like your Editor, it’s a good read. He posits that in three key areas, Theranos exhibited Startup Culture and Silicon Valley Ethics (or lack thereof) at the very extreme in these areas:

  • Secrecy: extreme compartmentalization, siloing, stratification, and rigid definition of roles that prevent information sharing. No outsiders in, or peer-reviewed research out.
  • Promises, promises, promises: a rosy picture to the point of delusion that masks real flaws
  • I Want To Believe: for various personal reasons, investors, press, and supports need to believe

Secrecy can and should work for companies in keeping proprietary information and competitive advantage intact. All startup and early-stage companies have to paint a positive picture in the midst of pitched struggle. The glass is always half full not empty even when the bank account is, but when the old ‘fake it till you make it’ becomes too strong, papering over the truth is the thing and the institutional absence of tough self-scrutiny (or a professional kicker-of-holes) prevents companies from fixing obvious problems–you get a delusional organization like Theranos edging gradually, then very quickly, into outright fraud. Finally, Theranos’ supporters had their own reasons for wanting to believe the technology worked. 

He goes on to state that the fraud that Theranos perpetrated was not only financial and in harm to health, but also in the hope that change is possible in healthcare delivery, we can challenge the way it’s always been done and win, and that technology can be empowering.

Will we, as a result, in Mr. Shaywitz’s words, take the ‘hit to hope’ to heart and become ‘excessively chastened and overcautious”? This Editor tends to be on the overcautious side when it comes to technologies such as IoT and AI because the potential for hacking and bad use is proven despite the hype, but far less so in challenging incumbents–even it it resembles tilting at windmills till they buy you.   

Will l’affaire Theranos change the Silicon Valley and Startup Culture for the better? Here is my ‘hit to hope’–that this excessively aggressive, conformist, borderline irresponsible, and secretive culture could change. This Editor doubts it’s even entered their leaders’ ‘deep’ thoughts, despite this best-selling book.

A more typical review of ‘Bad Blood’ is by Eric Topol, MD (!) in Nature–who certainly borrowed ‘The Theranos Story’ from this series of articles!