A Look Back at 2019

I've always been an optimist.   I believe humans are basically good and that the nice guy will win eventually.

After traveling 400,000 miles to 40 countries in 2019, helping government, academia, and industry, my view of the world has not changed.

Despite our focus on the negative 24x7 news cycle, 2019 has been the best year for humanity in history.

My best memories, looking back at 2019:

*Serving the Gates Foundation in South Africa and Northern India.  Experiencing the rollout of technology enabled platforms that reduced HIV disease burden and improved diagnosis/treatment of tuberculosis.

*Working with mayors and hospital presidents in China to create innovation centers in Shenzhen and Shanghai, enabling healthcare analytics platforms for population health and precision medicine.

*Helping government in Japan think about refinements to privacy policy that empower patients to be stewards of their own data.

*Discussing opportunities with government to enhance electronic health record and cloud adoption in Germany.

*Meeting numerous new colleagues in Northern Europe (Netherlands, Denmark, Norway, Finland and Sweden) while working together to harness past patient data for the benefit of future patients.

*Teaching National Health Service leaders in the UK (both England and Scotland) about a digital future that can transform workflow and the patient experience.

*Running courses with my Harvard colleagues all over the world to share lessons learned about technology policy and innovation.

*Mentoring the next generation of innovators in Massachusetts at Beth Israel Lahey Health and Mass Challenge Healthtech.

*Assisting with government policy development for data exchange as part of the Massachusetts Digital Health Council.

*Understanding the data needs of payers, providers, pharma, patients, and tech companies while defining the ethical uses of that data.

*Embracing a significant change for me personally - joining new colleagues at Mayo Clinic to build a global digital health platform for innovation. 

*Caring for 250 abandoned, abused, diseased, distressed, and unwanted animals at Unity Farm Sanctuary while building a self-sustaining community service destination for the Boston area.

In all these experiences, I saw forward progress as healthcare moved to the cloud, internet of things devices for health became mainstream and machine learning proved its value for diagnosis/treatment planning.   That even applies to Unity Farm Sanctuary where 103 internet of things devices help the staff deliver care.

Yes, I saw political unrest and divisiveness, the rise of populist movements, and a conservative shift in many governments.  To me, those were short term variations on a positive overall trajectory.    2019 set the stage for the next major leaps forward in digital health.

I'm honored to be a part of the 2020 journey that begins tomorrow.

Happy New Year!

Reinventing CDS Requires Humility in the Face of Overwhelming Complexity

Paul Cerrato and I have created a new book, Reinventing Clinical Decision Support, our first to be published about Platform thinking.   Although it is being published during my tenure at Mayo Clinic, it is not endorsed by Mayo Clinic and represents the personal opinions of Paul and me.  Below is the preface.

In our last book, on mobile health(1),  we wrote about the power of words such as cynicism, optimism, and transformation. Another word with powerful connotations is misdiagnosis. To a patient whose condition remains undetected, it is a source of frustration and anger. To a physician or nurse who has become a defendant in a malpractice lawsuit, it can likewise generate frustration and anger as they try to demonstrate that they did everything humanly possible to uncover the source of their patient’s symptoms.

The National Academy of Medicine’s report Improving Diagnosis in Health Care explains: “It is estimated that 5 percent of U.S. adults who seek outpatient care each year experience a diagnostic error. Postmortem examination research spanning decades has shown that diagnostic errors contribute to approximately 10 percent of patient deaths, and medical record reviews suggest that they account for 6 to 17 percent of adverse events in hospitals.”(2) An earlier report from the same group, To Err Is Human, came to a similar disturbing conclusion. The message between the lines of both reports is straightforward: Medical errors, including misdiagnoses, are often the consequences of being human. That same reality also comes across in a recent New England Journal of Medicine editorial: “The complexity of medicine now exceeds the capacity of the human mind.”(3)

Such complexity fosters humility—or at least it should. It requires humility for clinicians with years of experience successfully diagnosing patients’ ills to admit that they may be missing as many disorders as they catch. And the way the healthcare system is currently designed, that is a distinct possibility. When a patient is misdiagnosed by Dr. Jones, he often never goes back to him to say: You made a mistake, please try again. He is just as likely to move on to Dr. Smith in the hope that her diagnostic skills are more finely tuned. Humility is also required of clinicians to admit that the quantity of new research coming out in each specialty each year is so massive that it is virtually impossible for any one person to stay abreast of it. By one estimate, a new medical journal article is published once every 26 seconds, which translates to about 5,000 articles per day.(4)

Many diagnostic aids are now available to help address the epidemic of diagnostic errors we now face. Clinical decision support (CDS) systems, for example,are designed to help practitioners stay up to date on new developments without requiring them to spend their entire day reading the medical literature. Some CDS systems also offer symptom finders, decision trees, and other advanced features. But today’s digital tools only scratch the surface. Incorporating newly developed algorithms that take advantage of machine learning, neural networks, and a variety of other types of artificial intelligence (AI) can help address many of the shortcomings of human intelligence.

Fatima Paruk, MD, MPH, the chief medical officer at Allscripts, said it best: “[W]ith machine learning, clinical decision support can do so much more. We can transform systems laden with meaningless alerts to intelligent workflows and best practices driven by relevant patient history . . . Machine learning can enable clinical decision support based on multi-system analysis to understand which patients are at highest risk of a negative outcome, or to optimize treatment in real-time . . . Algorithms can parse available historical and current information to inform clinicians which patients are at risk for specific outcomes or deliver personalized treatment plans for patients with chronic conditions.”(5)

When will this next generation of CDS tools be available for clinicians in the trenches? When will we reinvent CDS? As the 8 chapters of this book point out, these tools are already emerging. Ignoring their value puts both clinicians and patients at risk.

This book begins with an examination of the diagnostic reasoning process itself, which includes how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods, cognitive mistakes such as availability bias, affective bias, and anchoring, and potential solutions such as the Human Diagnosis Project.

AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including the landmark Google study that demonstrated the value of deep learning in diagnosing diabetic retinopathy. Machine learning–enabled neural networks are also helping to detect melanoma, breast cancer, cancer metastasis, and colorectal cancer, and to manage severe sepsis. AI is even helping to address the opioid epidemic by reducing the number of pills being prescribed postoperatively. Each of these topics includes detailed references to the peer-reviewed medical literature.

With all the enthusiasm in the healthcare community about the role of AI and machine learning, it was also necessary to outline some of the criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed is the relative lack of hard scientific evidence supporting some of the latest algorithms and the “explainability” dilemma. Most machine learning systems are based on advanced statistics and mind-bending mathematical equations, which have made many clinicians skeptical about their worth. We address the so called black box problem, along with potential solutions, including educational tutorials that open up the black box.

This book devotes an entire chapter to commercial CDS systems, comparing legacy products to the latest software platforms. The evidence to show that these are having an impact on patient outcomes is mixed—an issue explored in depth in this book. On a more positive note, this chapter explores many of the innovative developments being launched by vendors such as DynaMed (EBSCO), VisualDX, UpToDate Advanced, and Isabel Healthcare.

The chapter on data analytics does a deep dive into new ways to conduct subgroup analysis and how it is forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs.

Any attempt to reinvent CDS also needs to tackle the outdated paradigm that still serves as the underpinning for most patient care. This reductionistic mindset insists that most diseases have a single cause. The latest developments in systems biology indicate otherwise and point to an ensemble of interacting contributing causes for most degenerative disorders. The new paradigm, which is being assisted by advances in AI, has spawned a new specialty called network medicine, which is poised to transform patient care at its roots.

Similarly, the current medical model relies too heavily on a population-based approach to medicine. This one-size-fits-all model is being replaced by a precision medicine approach that takes into account a long list of risk factors. And once again, this new paradigm is being supported by new technologies that help clinicians combine a patient’s genomic data, including pharmacogenomic test results, with the more traditional markers available in their electronic health record (EHR).

All these new developments would be useless if they could not be implemented in the real world. The final chapter outlines many of the use cases that have been put in place at Beth Israel Deaconess Medical Center (Boston) and elsewhere. These new programs are helping to improve the scheduling of 41 operating rooms, streamline the processing of patient consent forms before surgery, and much more.

Despite all these positive developments, it is important to emphasize that AI and machine learning will not solve all of healthcare’s problems. That will require an artful blend of artificial and human intelligence, as well as a healthy dose of emotional intelligence.

Finally, our enthusiastic take on digital innovation should not give readers the impression that AI will ever replace a competent physician. That said, there is little doubt that a competent physician who uses all the tools that AI has to offer will soon replace the competent physician who ignores these tools.


Paul Cerrato, MA
John Halamka, MD, MS

References
 1. Cerrato, P. and Halamka, J. (2019). Th e Transformative Power of Mobile Medicine.
Cambridge (MA): Academic Press/Elsevier.
 2. Balogh, E., Miller, B. T., and Ball, J. R. (Eds.). (2015). Improving Diagnosis in
Health Care. Institute of Medicine, National Academies Press.
 3. Obermeyer, Z. and Lee, T. H. (2017). Lost in Th ought: Th e Limits of the Human
Mind and the Future of Medicine. New England Journal of Medicine, vol. 377,
pp. 1209–1211.
 4. Garba, S., Ahmed, A., Mai, A., Makama, G., and Odigie, V. (2010). Proliferations of Scientifi c Medical Journals: A Burden or a Blessing. Oman Medical Journal, vol. 25, pp. 311–314.
 5. Paruk, F. (2018, December 4). HIT Th ink 4 Keys to Success with AI and Machine
Learning. HealthData Management. Accessed on December 18, 2018, from https://
www.healthdatamanagement.com/opinion/4-keys-to-success-with-ai-andmachine-learning

An Engineering Eye for the Tie Buying Guy

At the Mayo Clinic, patients always come first.  In my few days of volunteering, I picked up on some subtle ways that the culture supports patient-centric values.   Office areas are very utilitarian while patient care areas are well furnished and decorated.   Everyone is professionally dressed, regardless of their role.   For me, that means wearing a tie every day (and retiring my Dr. Martens).   Over the past 20 years, I've worn engineered black clothing in my travels around the world.   I've not worn a tie and long ago donated all the ties from my youth.   Admittedly, I do have a Harvard bowtie that I wore once for a meeting in a members only club that required a tie.   

So how does a person buy an appropriate tie in 2020?  Thick or thin, solid or textured, bright or subtle colors?   It turns out there is an engineering answer.   Here's a great overview  that helped me.

The width of a tie to buy in 2020 is a function of body size, lapel width and shirt collars. 

I'm 6'2" with a body mass index of 22.    I'm approaching 60 years old with measurements of 42" chest, 33" waist, 34" inseam.    That places me in the slim/tall category but not the athletic build category.

In 2008, I wrote this post about designing clothing based on the human three dimensional shape and the basics of materials science.   The lapels of all my current suits are 2 inches wide. 

My collars are thin and I don't want the tie fabric to protrude.

So for me, the acceptable tie width range based on my body type, my lapels, and my collars is 2.25-2.75 inches wide.

So what did I buy for my professional wardrobe?  A selection of 2.5 inch wide ties in charcoal, grey, and navy blue.

Each of them has some texture to stand out against my black and peat colored shirts.    It's likely that I will need a few white shirts as I transition to a full Mayo look.

Who knew that buying a tie needed a decision support system?

Mayo Clinic's First Platform

In my first few days volunteering at Mayo Clinic to meet colleagues, establish collaborations, and better understand the amazing patient services Mayo provides throughout world, I had the opportunity to tour the historic Plummer Building with Douglas Holtan,  chair of the Department of Facilities and Support Services.  Immediately, I realized the building is Mayo's first platform.

In my last post, I described a platform as a way to use knowledge and technology to facilitate connections, creating value in the process.

How could a building be a platform?

To understand that, you need to understand the past, provided to me by Matthew Dacy, creative and administrative director of the museum of Mayo Clinic.

Henry Stanley Plummer, M.D. (March 3, 1874-December 31, 1936) was a prominent internist and endocrinologist in the founding generation of Mayo Clinic. With his interests in medicine, engineering and the arts, colleagues considered him a "diversified genius" whose example remains an inspiration for innovators at Mayo Clinic.

He recognized the limits of the previous heterogeneous system in the Mayo practice. Each physician had his or her own ledger, limiting continuity of care when a patient had a return visit.  It was extremely difficult for multiple physicians to collaborate in the care of a single patient.

What did he do?

Dr. Plummer designed a  unified record and numeric registration system to benefit each individual patient while also accommodating a virtually limitless capacity of total patients in the system.

He created the record within the construct of the Mayo brothers’ philosophy that the needs of the patient come first and that a union of forces (diverse skills applied to shared purpose) would best serve patients.

He collaborated with allied health colleague Mabel Root and business manager Harry Harwick,  working with the  full blessing and support of Mayo brothers, especially Dr. William J. Mayo.

He sought technology best practices from other industries (pneumatic tubes from department stores, etc.) and installed them in the Plummer Building, which opened in 1928 and became the model for subsequent Mayo Clinic facilities, creating universal connectivity between those who produced information and those who needed it.  The system provided “just in time” access to information – as patients moved about the clinic between departments, the record would move via conveyor belts and drops, following the patient.

Here's a schematic illustration of functions and processes in the Plummer Building. Equally important, these systems are enveloped in stunning architecture with marble and other features from throughout the world.

Dr. Plummer standardized and optimized critical components, insisting on paper with high cotton content for durability, demanding precision paper thickness since large volumes would need to be stored and selecting official long-lasting “Mayo Clinic ink” that could be used in a wide range of fountain pens.  The end result was that information had durability, integrity, and availability.

He established strictly maintained institutional process and policies for record creation, dissemination and storage. As a result, very few  records were ever lost or misplaced.   The end result was that security and privacy were maintained despite the broader sharing of information.

He expanded the system as needed with additional cards and documents , using color coding and other techniques for ease of recognition and access.   If effect, he added new  "apps" to the healthcare information ecosystem.

This unified record platform with its universal connectivity, availability, integrity, security, and scalability had a symbiotic relationship with the comprehensive Mayo Clinic general exam, advancing the standards of diagnosis, treatment and prevention of illness.   It supported research, quality measurement, and population health.

Fast forward from 1928 to 2019 and you can see that first Mayo Clinic platform in the Plummer Building inspired the next Mayo platform which seeks to connect information producers with information consumers while insuring data integrity, security, and innovation agility.   It's an update for the digital age of the foundation laid by Dr. Plummer.

In my upcoming posts, I'll provide comprehensive detail about all the novel components of the new platform and the services that will cure, connect and transform healthcare throughout the world.

For me, the Plummer Building is the inspiration for the work ahead.

What is a Platform?

This month I'll deliver several keynote addresses.  In my presentations, I'll use terms such as platform enterprises, platform thinking, and platform strategy.  But what is a platform?

Is it just a collection of standards?   If so,  is a USB flash drive a platform, since I can transfer a file from my Chromebook to someone else's Macbook using it, in a low effort, low cost fashion?

Not exactly—in the USB example, there is no agreement about what file types are preferred, what data those files may contain and what security controls will be used to protect the integrity and privacy of the data.

In my view, a platform is a combination of technology (data standards, APIs, security controls), policy (who can do what for what purpose with what privacy controls), and process (what workflow is supported by what people and what automation).   In short, it is a way to use knowledge and technology to facilitate connections, and create value in the process.

For example, Unity Farm Sanctuary is entirely controlled with the Google Home platform. My locks, lights, thermostats, cameras, and mobile devices are linked via a set of APIs and security controls (OAuth). I can delegate rights to use selected devices for selected functions to authorized collaborators but the general public cannot gain access to my heat, light and power controls.     I use a combination of approaches to support device and workflow integration - Google Assistant routines, proprietary apps, and secure websites.     The end result is that I can monitor and manage the well being of 250 animals from my phone.

How does this apply to healthcare?

We know that the CMS Interoperability Proposed Rule and the ONC Information Blocking Proposed Rule  are likely to be finalized into active regulations. This means that in 2020 or 2021, hospitals and clinician offices will be required to exchange data via APIs to patient controlled apps. Increasingly healthcare must be a competent data business as well as an empathetic care delivery business. Supporting new regulations with point solutions will create a chaotic collection of heterogeneous user experiences and security vulnerabilities. Why not create a single, managed and well supported front door which enables quality, safety and efficiency solutions to be deployed more quickly?  That's Platform thinking.

The transition from a collection of products to a platform strategy is a journey.  How will technology services be delivered - via Google Cloud platform, Amazon Web Services, Azure, or other provider? How will access be granted, managed, and monitored? What workflows for what use cases will be supported and when? How will it be paid for? How will the effort be communicated so that all stakeholders understand privacy protections, ethical use of data, and possible participants in a platform ecosystem?

There are many questions to be answered while on the road to becoming a platform enterprise.  Over the past ten years, I've written nearly 2000 posts about Life as a CIO.   I feel the next 2000 posts about the platform transformation of healthcare, my dispatches from the digital health frontier,  will be even more important.

What's Next?

After nearly 25 years in Boston, I'm beginning a new journey at Mayo Clinic in the role of president, Mayo Clinic Platform.  Many colleagues have asked me about the transition.   

First, I have profound thanks for my mentors and collaborators in Boston.   I could easily fill an entire blog post with the names of hundreds of people who worked with me since 1996 on cloud services, mobile applications, machine learning, connected devices, and data standards.

Those innovations  made a positive impact on many people.    At Mayo, I believe I can scale the lessons learned in Boston to stakeholders around the world.  How?

As an adviser to many startups, incubators, and accelerators around the world, I've experienced the barriers and enablers to innovation.    Challenges include lack of standardized technology (APIs with sufficient data granularity and workflow integration),   policies (templates for security, privacy, risk analysis, ethical use of data, and communication),   and people (sufficient staffing to run pilots and focus on collaborators).  Launching a pilot can take 6 months just to work through approval processes.     Sometimes academic medical centers can take as long as 18 months to formalize a proof of concept project.   What if a Platform of technology, policies and people were able to radically shorten the time to evaluate emerging companies and created an "innovation factory"  for  collaboration?    That's how I think about the Mayo Clinic Platform opportunity.

Although I've visited Mayo many times, I've just scratched the surface in my understanding of the culture, capabilities, and colleagues.  A good way for anyone to understand what makes Mayo uniquely Mayo is to watch the Ken Burns documentary

How will I spend my first 100 days at Mayo?   Although I do not begin the role until January 1, 2020, I'm taking personal time off to volunteer at Mayo during December, meeting dozens of stakeholders at every level of the organization.   I need to listen to their hopes and needs for Mayo Clinic Platform projects.    There is a remarkable interim team leading the Platform today and they will guide me through the work to date, the critical decisions ahead, and the refinement of the strategic plan.    Together, we'll advance the strategy, structure, and staffing for the Platform.   Outstanding support teams in legal, development, compliance, IT, and public affairs will help.    I'll speak about our early decisions at JP Morgan and HIMSS.     Mayo CEO, Gianrico Farrugia,  will keynote the HIMSS conference .

Personally, I will live in an apartment in Rochester, Minnesota from Monday-Thursday, then return to Unity Farm Sanctuary for weekend animal care and farm maintenance.     The flights are easy (2.5-3 hours, 3 times per day on Jet Blue), and even with weekly commuting I may actually travel less in 2020 than in 2019 (400,000 miles in 40 countries).

During times of great challenge and change, I've blogged on a daily basis, sharing my successes and failures transparently with government, academia and industry colleagues.  Recently I've focused on writing articles and books.   The pace of the Mayo Clinic Platform effort necessitates frequent blog posts.  I'm renaming my blog from "Life as a CIO"  to "Dispatches from the Digital Health Frontier".  My hope is those dispatches will help others with the path forward, following the best trails and avoiding pitfalls. 

Am I excited by the work ahead?  Most definitely.    Am I daunted by the responsibility and accountability of shaping the future of Mayo's digital businesses?   Of course.   I call this, excited anxiety.   During those stages of life when there is a perfect storm for innovation , I find that a little adrenaline really maximizes focus, especially when you're not sure where the path ahead will lead.   As my colleague Prof. Yitshak Kreiss, M.D., Director General, Sheba Medical Center  told me "innovation is when you have an urgency to change but don't know exactly how to get there.   If you know where you're going, it's just implementation not innovation."

With today's Mayo announcement, I believe the next perfect storm is beginning and I'm ready.   And I'll make sure my readers have a front row seat.

Remote Patient Monitoring and Self-Responsibility

At HIMSS next week, I'll be doing 5 presentations about the future of healthcare IT, focusing on patient directed data exchange, internet of things, and telemedicine.     Remote patient monitoring,  which combines all three, will be increasingly important.

Remote patient monitoring can take numerous forms,  and the evidence supporting these tools is mixed. Here’s another excerpt from our new book—The Transformative Power of Mobile Medicine—co-authored by Paul Cerrato that dives into the issues.  For those interested in reading the entire book, the publisher is offering a deep discount until March 31, 2019; coupon code: HIMSS2019.

Many thought leaders are convinced that remote patient monitoring improves patient care, but surveys suggest that health-care professionals are still not convinced. An analysis from the New England Journal of Medicine Catalyst Insights Council asked respondents to rate various patient engagement initiatives. “Remotely monitoring using wireless devices/wearable” was listed as the least effective way to engage patients while having physicians, nurses, or other clinicians spend more time with patients was listed as the most effective tactic. [1] There is also uncertainty about the benefits of remote patient monitoring in the scientific literature. Of course, remote patient monitoring can take so many different forms that it’s impossible to make a blanket statement about its effectiveness. But a randomized controlled trial (RCT) that included more than 1400 patients (median age 73 years) who had been hospitalized for heart failure generated less than encouraging results. Michael Ong, MD, from the University of California, Los Angeles, and his colleagues divided the group into an intervention arm, which received health coaching phone calls along with the collection of vital signs that included blood pressure, heart rates, symptoms, and weight with the help of electronic devices, and a control arm that received the usual care [2]. Ong et al. couldn’t find any significant difference in hospital readmission rates 180 days after discharge for any cause: 50.8% were readmitted despite having all the extra attention and access to all the high-tech monitoring devices versus 49.2% in the usual care arm. Similarly, the investigators detected no difference in 30-day readmission or 180-day mortality. The experimental group did, however, report better quality of life at 180 days.

 On the other hand, Essentia Health, a Minnesota-based system that includes 16 hospitals and 68 clinics, has been using home telemonitoring with a body weight scale to keep track of CHF patients. Patients weigh themselves every morning and answer a few basic questions about their symptoms. Their responses are transmitted via telephone line to the computers that triage the incoming data and alert clinicians to those in need of additional attention. Essentia has been able to reduce 30-day readmission rates to less than 2% with the program. The average readmission rate for CHF patients
is 25%. [3-4]

Detecting statistically and clinical significant benefits for remote patient monitoring is complicated. Unfortunately, Americans are used to being passive recipients of health care. When they see their physician, they expect to receive a pill or have a procedure performed. The only demand on their time and attention is taking the pill or undergoing the operation. Asking patients to take on a more active role in their care, including weighing themselves daily, taking blood pressure readings, and so on, requires a stronger sense of self-responsibility and better cognitive skills. It also requires a deep, long-term commitment from the health-care care organization launching the program. Providers cannot expect to “patch” a remote patient monitoring system into the mix without a great deal of planning and commitment from physician leaders and clinicians in the trenches. Tracy Walsh, a senior consultant with the Advisory Board, sums up the issue succinctly: providers need to “track program metrics that closely map to the organization’s broader strategic objectives.” [5]. Walsh provides a detailed graphic to help providers choose wisely. It addresses three basic questions regarding remote patient monitoring:

·     Is it technically feasible?

·     Is it clinically relevant?

·     Is it cost-effective?

References

1.     Volpp KG, Mohta NS. Patient engagement survey: improved engagement leads to better outcomes, but better tools are needed. NEJM Catal May 12, 2016;. Available from: https://catalyst. nejm.org/patient-engagement-report-improved-engagement-leads-better-outcomes-better-toolsneeded/.

2.     Ong MK, Romano PS, Edgington S, et al. Effectiveness of remote patient monitoring after discharge of hospitalized patients with heart failure: the Better Effectiveness After Transition_Heart Failure (BEAT-HF) randomized clinical trial. JAMA Intern Med. 2016;176:310-18.

3.     Siwicki B. Essentia Health slashes readmissions with population health initiative, telehealth. Healthcare IT News. March 15, 2016.

4.     Agency for Healthcare Research and Quality. Heart failure disease management improves outcomes and reduces costs. ,https://innovations.ahrq.gov/profiles/heart-failure-disease-management-improvesoutcomes-and-reduces-costs?id5275.

5.     Walsh T. Studies are conflicted about remote patient monitoring—here's what we think. Advisory Board March 31, 2016;. Available from: https://www.advisory.com/research/market-innovationcenter/
the-growth-channel/2016/03/remote-patient-monitoring-roi.

What's Next for Healthcare?

Today I had the honor of keynoting at a major announcement from Apple, Aetna and CVS/Caremark.   I'd summarize the message as "Digital Health has arrived and is now mainstream, fully embraced by the major stakeholders in the healthcare ecosystem."

Here's the upshot.

The history of healthcare and payment has been risk pool based and focused on paying for sickness.

The future belongs to wellness, personalization, and a team-based approach to keeping you healthy in your home. 

The announcement of Aetna Attain, a collaboration of Aetna, CVS/Caremark, and Apple, is based on a few key ideas:

1.  Personalization is essential
Asking everyone to walk 10,000 steps a day is unrealistic.   Some should walk 5000 and some should walk 20,000.    Performance goals should be set based on past performance, current health state, and patients like you.

2.  Privacy is foundational
Managing an ecosystem of apps, interfaces, and cloud services requires that privacy is designed in from the ground up.   Everything around Attain is based on opt-in, patient controlled privacy preferences, de-identification, continuous authentication (how are you holding your phone now), and aggregation of information.

3.  Machine learning based on patients like you is empowering
Randomized controlled trials are great but impossible to personalize.  Ideally, the past data from millions of patients like you will inform your wellness strategies for the future.

4.  Incentives/alerts are important to motivate wellness
We're all busy people.   There are many tasks competing for our attention.   If we're reminded at just the right time, maybe we'll be more likely to follow through on positive behaviors.   If we're given an incentive payment (or even compelling, avoiding a penalty) for achieving our goals, we're more likely to focus.

5.   A combination of historical medical experience plus telemetry is powerful
Raw data in the absence of context is rarely helpful.   A few years ago I had a debate with a major industry executive who argued all healthare data is "atomic" i.e. all we need to know is systolic blood pressure then we can act.  I countered that we need to know history, current symptoms, medications, how the blood pressure was taken, and patient care preferences before action can be taken.   The Attain approach is to combine all these factors before suggesting wellness behaviors.

As I said in my keynote today, I'm very optimistic about 2019.   Attain is a great example of  emerging technology convergence - internet of things, cloud, machine learning, telecare, and security coming together.    The industry will learn a great deal from the Attain project about patient generated healthcare data, patient data stewardship and alignment of incentives for wellness.

I'm glad to be part of the exploration.

Embracing ChromeOS (and the cloud mindset required)

2019 will bring many changes.   After more than 20 years as a Chief Information Officer, I will pivot to lead innovation as part of the senior leadership team for the newly merged Beth Israel Lahey Health on March 1, 2019.
   
Here's the Boston Business Journal article about it.

My innovation role will focus on 5 areas:

A front door/liaison to government/industry/academia for digital health collaboration at Beth Israel Lahey Health

Exploring new technologies, especially those arising from outside healthcare, to assess their role in provider/patient/payer workflow

Mentoring startups and internal faculty seeking to create new products/services especially in the areas of machine learning, mobile, telecare, internet of things and blockchain

Lecturing/writing to broadly disseminate lessons learned about innovation

Hosting of international visiting groups from around the world which want to learn about our innovation efforts.

In many ways, this next step combines the best of my youthful experiences researching and writing in the early 1980's Silicon Valley with my 30 years of experience as an IT leader and professor.    I look forward to it.

In the early 1980's while writing for Infoworld, I had the opportunity to personally evaluate emerging products - the IBM PC, Compaq's portable, Wordstar, Microsoft compilers, and various dial up modem services.  Nearly 40 years after evaluating the first PCs, I'm now evaluating Chromebooks and ChromeOS as the next frontier in personal computing.   Here's the experience thus far.

Think of ChromeOS as not just an operating system replacement for Windows or MacOS/ioS but an entirely new approach to computing.   It's essentially a cloud viewer, consuming data and services available on the internet combined with limited offline replication of data just in case the internet is not available.    What does that mean?  Instead of using a local file system to store my documents, media, and data, I'm using Google Drive.   If my device is lost, stolen or damaged, there is nothing to hack on the device.    My Chrome applications are all web services with nothing running on the local Chromebook - Gmail, Gsuite, and Outlook Web Access (or Office 365).   

Why is this a useful concept?    A few months ago, I was in Tel Aviv and I damaged my computer.  There was no way to replace/repair it easily.   If I had been using a Chromebook, I could buy any $200-300 Chromebook and immediately have access to all my data and services.

The Pixelbook supports Android apps in addition to ChromeOS, so I can run local software with local data if I chose.   I've added a few such apps such as Nest (cameras, smart home controls), Gmail offline (local replication of email), and Weatherlink (to control my weather station), but I really don't need them.   The combination of my phone for apps and a Chromebook for cloud hosted services works extremely well.

Are there downsides?   Absolutely.

Cloud/web native apps may not be as sophisticated or usable as locally installed apps.   Moving from local storage to cloud storage requires some planning and adaption.    I installed sync software on my previous computer and synced all my files into Google drive so cloud migration was one step.    I set up offline files so that every document I edit in the cloud is replicated into offline storage on my Chromebook for easy access when I'm on an airplane without wifi.     I previously managed photos and media on devices but now I manage them in the cloud.    All of this is change and requires getting used to.

For my use case - productivity applications, email, media management - a Chromebook works perfectly well.    I imagine there may be tasks/high intensity computing  use cases for which the cloud application and file system approach may not be optimal.   But for me, it works.

Truly, about the only thing I would like to see improved is that the Beth Israel Deaconess version of Outlook Web Access (2013) is not as full featured as Gmail or Office 365.    Once we upgrade or migrate, then the final piece of my cloud-based computing environment will fall into place.

I know that I may be edgy by suggesting that thin client, cloud-centric computing is the future, but from a security, cost, and maintainability perspective, it certainly seems like the right direction to me.

Exploring the Connected Medical Home

Over the past few weeks, I've been exploring the combination of internet of things, artificial intelligence, and ambient listening with a focus on how these technologies might improve care management, patient/family navigation of the health system, and wellness.

Google, Apple, and Amazon all have ecosystems that include the functionality I'm writing about.  Purely because I'm spending January investigating the Android/ChromeOS environment, my first exploration has been with Google products.    I'll explore Apple next.

Here's my test bed:

Unity Farm Sanctuary heating and cooling is controlled by Nest Thermostats.

The animal areas are streamed from Nest Cameras.

In the living room, I've installed a Google Home Hub, a Chromecast Generation 3, and Chromecast audio (now discontinued).

I'm currently carrying a Google Pixel 3 phone running Android Pie.   My personal computing platform this month is a Google Pixelbook.

What does this infrastructure enable me to do?

Here's a sample dialog (Google product responses are in italics)

Ok Google, what is the temperature in the living room?

The farm living room is at 66 degrees.

Ok Google, increase the living room temperature to 68 degrees

The farm living room temperature has been increased to 68 degrees.

Ok Google, show the cows on TV

Showing the Sanctuary Cows on the Farm Living Room TV

Ok Google, play music on the speakers

Playing selections from Google music on the farm kitchen speakers

Ok Google, pause.

Music paused.

Ok Google, call Mom

Calling Mom

This internet of things, artificial intelligence, and ambient listening example illustrates the many possibilities for any internet connected home.    As 5G cell phone technology is deployed in 2020, gigabit internet will exist over the air throughout the country - no wires/fiber needed.   The potential is only limited by our imagination.

What exactly is the potential?   Google Home enables the definition of routines - a kind of macro that links commands together, including "if this, then that" kinds of controls.

For example

Ok Google, Good Morning

Good Morning John

It's 22 degrees outside and today will be dry with a high of 32 degrees.

Your commute to work today will take 47 minutes because traffic is heavy

Increasing the temperature of the kitchen and decreasing the temperature of the bedroom

Playing morning music

Ok Google, Good Night

Turning off the lights

Activating the security system

Reducing the temperature of the kitchen and increasing the temperature of the bedroom

Sleep well

All of this has worked so well, that it makes me believe the future of computing is not limited to phones and apps, but increasingly a voice driven integrated ecosystem that requires very little technical expertise to use.

The artificial intelligence components can be startling.

Ok Google, play NCIS on TV

NCIS is available on CBS All Access and The CW

CBS All Access

Playing NCIS from CBS All Access on the Farm Living Room TV.  I will play from CBS All Access next time you ask for NCIS.

This required identifying that NCIS is a television program, offered by certain vendors, each with a different way to play it.   Notice also that I was vague about which TV to use, but Google Home figured it out.

Fast forward to healthcare. As we think about the integration of wearables and other in home wellness devices, this technology can integrate devices, routines, and voice commands to measure activities of daily living, suggest healthy behaviors, evaluate compliance with care plans, and communicate with care teams.

Today, only those with technological literacy and dexterity can perform these functions with a collection of apps, but it takes diligence, planning, and a steep learning curve.

Assembling all the connected home functions described above was done by me, in a few minutes, by unboxing devices and doing minimal setup - a one time only event.

As we move from fee for service to value-based purchasing, reimbursement reform will align incentives for wellness in the home rather than the treatment of sickness.  I predict that healthcare delivery organizations will restructure themselves for success  by shifting work from building more hospital beds to empowering patients outside of the hospital.  This will require training clinicians in  telemedicine  (let's call the new medical specialty "virtualists"), home support people (both visiting nurses and connected home technicians), and care managers who ensure all services are coordinated to maximize quality while reducing total medical expense.

To me, this tech works so well, and is so affordable (compared to treating sickness), that the future of the connected medical home looks very bright.

Dispatch from India

I spent last week in Bihar, an area of Northern India near Nepal.  The best way to describe the journey is in pictures.

Our small team visited villages along the Ganges to the east of Patna, tracing the path of patients from seeking care to diagnosis to treatment to compliance to wellness.   We met with patients, providers, field officers (think of them as care managers), chemists (pharmacists), and labs.    Here's what we experienced:

The villages had hand pumped water supplies, electricity and 4G cellular connections.  Cows and goats were a part of many households.

A unique telemedicine program from World Health Partners (WHP) provided access to experts, connecting each village to trained clinicians in urban areas.    We participated in such a consultation.

We visited patients in their homes to hear their stories.  All of us were touched by Pooja, a 25 year old new mother who spent 70,000 rupees (about $1000) on unnecessary medical care due to a misdiagnosis.   She had to sell her land and her cow to pay for healthcare.   We've started a go fund me to help rebuild her life.

We reviewed medical records and imaging studies, which in India are maintained by patients and families.  In this photo, I'm reviewing the records of a TB patient who is feeling better after treatment, but appears to have a negative initial chest X-ray.

We visited a local lab which offered a menu of diagnostic tests ranging in price from $.70 to $14.00. Diagnostics included GeneExpert TB testing and 3D doppler ultrasound.   All lab data is manually recorded on paper and carried by the patient.

Local chemists make available a range of medications at very low cost.

Medical record keeping is done via a brief note which is the property of the patient.  Prescriptions are often abbreviated in a way that can be hard to decipher but a local chemist can understand.   Registry data is entered for tuberculosis and is one of the few electronic workflows, completed on low cost android phones by provider support staff.

I came away with a better understanding of the cultural, political, and clinical workflow in the state of Bihar.   Next steps will be designing the digital health services which are most likely to serve the stakeholders, now that we have experience with their requirements and constraints.  We'll do everything possible to leverage the remarkable national cloud hosted services available in India including identity management via Aadhaar, payments via UPI  and the rest of the "India Stack".

As I wrote last week, the next 30 years of my life will be dedicated to purposeful causes that I hope
will make a difference.    India and China, which comprise more than 1/3 of the humans on this planet,  seem like the right focus for 2019.

Choosing Effective, Sticky Health Apps (Part 2)

In a blog post last week, I shared an excerpt from the new book that Paul Cerrato and I just completed, The Transformative Power of Mobile Medicine.  Here is a second excerpt from Chapter 3,  “Exploring the Strengths and Weaknesses of Mobile Health Apps.”

Even patients who are fully engaged in their own care still need access to medical apps they can trust. The IQVIA Institute for Human Data Science has performed a detailed analysis of the clinical evidence supporting mobile health apps, rating their maturity and relative quality. Its rating scale places a single observational study near the bottom of the scale, progressing upwards through multiple observational studies, a single randomized controlled trial, multiple RCTs, a single meta-analysis, and several meta-analyses. Using this methodology, it organized mobile apps into several categories. In the category called “Potential disappointments—more study required” are apps for exercise, pain management, dermatology, autism, schizophrenia, multiple sclerosis, and autism.  In the category called “Candidates for [clinical] Adoption” were mobile apps for weight management, asthma, COPD, congestive heart failure, stroke, arthritis, cancer, PTSD, insomnia, smoking cessation, stress management, cardiac rehabilitation, and hypertension. The most important category listed in the IQVIA analysis, which it considered candidates for inclusion in clinical guidelines, were diabetes, depression, and anxiety.

IQVIA has also generated of list of “Top rated apps” for 2017, taking into account their top clinical rating and the fact that they are free and publicly available.  Top rated apps in the free list includes Runkeeper by FitnessKeeper, Inc, Headspace, for stress management, Kwit, for smoking cessation, My Spiritual Toolkit, an AA 12 step program, mySugr, for diabetes management, and SmartBP for hypertension. In the top clinical rating list are Omada, for diabetes prevention, BlusStar Diabetes by WellDoc, Kardia by AliveCor, for atrial fibrillation and dysrhythmias, MoovCare for cancer patients, AiCure for medication management, and Walgreens medication refill app.

The UK’s National Institute for Health and Care Excellence (NICE), has also made real progress in evaluating mobile health apps. One of its missions is to provide guidelines for the use of health technologies within the NHS. NICE reviews data on drugs, medical devices, diagnostic techniques, surgical procedures, and health promotion activities, basing its recommendations on clinical evidence that demonstrates these treatments and activities are effectives, and on economic evidence that shows they are cost effective. [1]

The Institute has evaluated numerous mHealth services, with very detailed reviews of each service or mobile app.  Among the apps that have been studied: GDm-Health, which is intended for women with gestational diabetes, AliveCor Health Monitor and AliveECG app for monitoring cardiac function, Sleepio, for adults with sleeping problems, VitalPAC, for assessing vital signs in hospital patients, LATITUDE NXT Patient Management System, which allows clinicians to monitor cardiac devices at home, and numerous others. [2]

To illustrate the depth and thoroughness of the NICE reviews, consider its analysis of GDm-Health. The review explains the app’s purpose, which is to download data from a patient’s blood glucose meter and send it to a secure website where it can be monitored by clinicians. The web site also lets clinicians send text messages to patients to help them manage their condition. But NICE does not stop there. It also evaluates the app’s clinical effectiveness, user benefits, and the impact that its use would have on costs and resources. It then puts the mobile app into the context of NICE’s guideline for gestational diabetes, explains several of the app’s features in detail, and goes into an extensive discussion of the evidence supporting the app, including summaries of each of the clinical trials that support its use, the key outcomes, and its strengths and limitations.  

1. NICE. Technology appraisal guidance. https://www.nice.org.uk/about/what-we-do/our-programmes/nice-guidance/nice-technology-appraisal-guidance     Accessed Feb 6, 2018.
2. NICE. Mobile health technology search results. https://www.nice.org.uk/search?q=mobile+health Accessed Feb 6, 2018.

The Meaning of Life (as a CIO)

As I approach 60 and reflect on over 40 years in the healthcare IT industry I sometimes feel that I’ve transitioned from a rogue upstart to the leader of the status quo - always about to be disrupted. I’m no longer a trouble maker, I calm the troubled healthcare technology waters.   If I’m not careful, that could mean I’ll become a rate limiting step to radical change since I’ve been shaped by a lifetime of experience that started with punch cards, paper tape, and Fortran.

The themes I’ll write about twice a week in 2019 will be about exploring new technology around the world and in a Boston-based lab, the Healthcare Technology Exploration Center at Beth Israel Deaconess Healthcare System, which I lead.    We’ll evaluate new products, ideas, and workflows.   We’ll pilot innovations and fail fast (if needed) so that we can rapidly converge on the right tools for the business requirements we’re given.

In our first quarter we’ll describe an evaluation of the Google ecosystem and potential healthcare implications for Android, Chrome OS  and sensor devices such as

Google Pixel 3 phone
Pixelbook
Google Home Hub
Google Chromecast 3rd Generation
Google Mini-home
Google Chromecast Audio
Nest Thermostat
Nest Outdoor Camera

We’ll review internet of things devices including the Withings suite of watches, blood pressure cuffs, sleep monitors, thermometers, and scales.

We’ll evaluate telemedicine devices and services that bring cloud hosted, machine learning driven decision support to patients and providers.

And of course, we'll take a deep dive into everything Apple is doing in digital health space.

Why am I starting a new lab as I approach 60?   Simple - the meaning of life  (in my view) is about finding a purpose that serves the world selflessly, while surrounding yourself with people who give you a sense of belonging, enabling you to pursue your passion, and ultimately composing the ongoing narrative of your life.

To me, improving wellness with digital health around the world excites me every day

For example,  today I'm in Patna, India at the corner of Nepal, Bhutan, and India evaluating the potential for cloud services, apps, and devices to be used in resource constrained settlings for the management of tuberculosis.

There is no better way to solve a problem than to immerse yourself in the lives of the people you are trying to help, which is what I’m doing this week in homes, clinics, pharmacies, and hospitals.

However, a sense of purpose needs a group of like minded people who give you a sense of belonging. People you can talk to - sharing your successes/failures, and asking for feedback on your ideas.   Throughout my life I’ve been lucky enough to surround myself with people smarter than me, who are a constant source inspiration and energy.    At the moment my sense of belonging comes from extraordinary collaborators in international governments, academia, industry, foundations, and non-governmental organizations (NGOs).       I have a special respect for people in their 20 and 30’s who have far fewer biases and battle scars than me.

Although my passions have changed over the years, there is a common theme.  I’ve always worked at the edges of disciplines.   I'm a physician but my academic work has been at the intersection of medicine and digital health.  In my youth I was the first student at Stanford to have a computer in my dorm room (I built it).   I was the first young journalist to review a portable (25  pound) computer from a new company called Compaq.     I was the first person in Wellesley, Massachusetts to get broadband.   All of my experiences have been at the margins of the possible before the ideas were even considered reasonable.

And I’ll continue to tell my story via the evolving narrative of my life.    In an upcoming post, I’ll explain that my biography should start with the sentence  “He was the Forrest Gump of healthcare information technology” purely because by random chance I’ve been present at every major health related IT innovation of my generation.    And over the next 30 years (I’m vegan, so I should last that long), I’m hoping to be present for the amazing things my friends, students and collaborators do to change the world.

So my meaning of life is about making a difference in digital health around the globe, surrounded by inspirational people, investigating new ideas at the edges of the possible, while creating a story filled with impactful events.    

And that’s what I’ll write about over the next year.

Choosing Effective, Sticky Health Apps

In a recent blog post, I talked about the new book that Paul Cerrato and I just completed, The Transformative Power of Mobile Medicine.  In that post, we shared the Preface to the book in the hope that it might pique readers’ interest in mobile health.  What follows is an excerpt from Chapter 3, “Exploring the Strengths and Weaknesses of Mobile Health Apps.” 

Choosing Effective, Sticky Health Apps

Even healthcare providers who see the need for innovative mobile apps still face numerous obstacles. Given the human tendency to seek the path of least resistance, identifying the most effective, “stickiest” mobile apps becomes a real challenge. In Realizing the Promise of Precision Medicine, we discussed the need to individualize medical care and the importance of improving patient engagement. When choosing mobile health apps to meet patients’ needs, it is critical to keep both goals in mind. Each patient is at a different stage in their journey, with some lacking basic knowledge about their disorder and others almost as well informed as their providers. With that in mind, the prescription of health apps should be geared to an individual’s level of patient engagement. 

Mobile apps can be divided into several broad categories based on the level of engagement that each patient has reached. Patients will likely lose interest in a health app if it is not consistent with their level of engagement. [1] Among the categories that can meet patients’ needs are apps that:

'Provide educational information

Alert patients to take some specific action

Track their health or medical data

Present patients with data that they have put into their mobile device

Offer advice based on the data that patients input into their device

Allow patients to send information to their family or healthcare provider

Provide social network support

Reward patients for changing their behavior.’ [1]

An activated, fully engaged patient will likely know most of the basics that would be provided in a mobile app that only offers educational information and will lose interest in the digital tool quickly. Conversely, a patient who is only modestly interested in managing a chronic condition may not benefit from a more in-depth app that tracks their medical data or physiological parameters. They must learn to “crawl before they walk.” 

The second category on the list, namely alerting patients to take some action, requires a closer look as well. No doubt many patients have benefited from mobile apps that remind them to take their medication on time or to make an appointment for their periodic mammogram or colonoscopy. Forgetfulness is a normal human failing and these apps can address that. But to be realistic, most non-adherence is not driven by poor memory. It’s driven by far more complex and entrenched motives, and the reason many patients fail to heed their provider’s advice is because it is just not that important to them, or because in their minds the risks outweigh the benefits, or because they can’t afford the prescribed intervention, or because they didn’t fully understand the advice offered or….  The list is long.

Addressing the first issue, Ira Wilson, an authority on patient adherence, points out that ‘we don’t forget to pick up our kids from day care or to make dinner or anything else that’s really important.’ [2] With that reality in mind, it’s not surprising that reminder apps that send patients alerts frequently fall short. This once again emphasizes the point we have made elsewhere in this book: Mobile tools can only supplement medical care, not replace it. And for clinicians to motivate such uncooperative patients will require time, a precious commodity in today’s healthcare environment.

Time is required to ask patients about why they don’t want to follow a prescribed course of action. Time is required to query patients about possible obstacles to adherence: “Can you afford this medication?”  “Does it cause unbearable GI reactions?” “Do you have a way to get to your next appointment or would it mean losing a day’s pay and possibly termination?”  “Do you think your hypertension requires medication even though it’s not causing you any pain or discomfort?”  We obviously can’t solve all our patients’ problems, but knowing what’s behind their noncompliance is the first step toward resolving it.   

Ira Wilson takes this type of deeper probing to heart when he works with patients:

Wilson doesn’t push reluctant patients to take their medications. During a visit with a man with poorly controlled hypertension, for example, Wilson began by asking, “What does hypertension mean to you?” The man replied, “I’m kind of a hyper guy. And sometimes I get tense.” He explained that he takes his medications only when he feels both hyper and tense. In such situations, I [the author of a New England Journal of Medicine editorial] would probably reply, “That’s not how it works,” but Wilson gently asks, “May I share a different perspective?” And patients usually say, “Of course, that’s why I’m here.” 

People like Wilson don’t need a digital reminder to have these conversations or to abandon the “doctor knows best” dynamic. For those of us who struggle, the most effective adherence booster may be giving doctors and patients the time to explore the beliefs and attributions informing medication behaviors. These conversations can’t happen in a 15-minute visit. [2]

Singh K, Drounin K, Newmark LP et al. Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain. Health Affairs. 2016; 35:2310-2318. 

Rosenbaum L. Swallowing a spy—The potential uses of digital adherence monitoring. N Engl J Med. 2018;378:101-103.

Embracing Android

Happy New Year!   I'll be posting blog entries twice a week in 2019, describing my experiences in the healthcare IT innovation economy and international digital health.

Throughout my history in the industry, I’ve tested many emerging technologies and tried to predict future winners.   Here's a CIO magazine article from 2007 in which I replaced my computing platforms each month to rigorously test Windows vs. Linux vs. OSX

In the late 2000's, I felt that Microsoft had lost its agility and focused on adding features that few people wanted at the expense of usability.   I switched to Apple products because the software felt more utilitarian, secure and stable.

Now, I'm asking if Android and Chrome OS has the balance of features and usability that best meet my requirements for 2019.

I've moved to my phone to a Google Pixel 3 to help answer that question.

Thus far, my experience has been remarkable - a good mixture of speed, stability and usability.   I think of it as a toolbox that doesn't prompt me to adopt functions that I don't want.  

One of the best features is a simple consolidated notifications display that enables me to scroll down from the top of the screen and see every change that has occurred since I last picked up the phone - email, texts, app messages, reminders, and calls.

The gestures are intuitive.    The browser is Chrome (works everywhere with everything) and the email client is the highly usable and stable Gmail client

I've been so impressed with the functionality of my Android phone that I decided to move my computing environment to Chrome OS and Android as well.   My Google Pixelbook arrives on Friday and I'll travel with it in India next week.

I'm writing this using Gsuite.    My data is stored on Google Drive.  I'm making my purchases with Google Pay.

All of this will be an interesting experiment, but thus far, it seems to me that the future of healthcare IT looks belongs to cloud hosted applications/services accessed from thin browser-based and mobile clients.   Android/Chrome OS might very well be those thin clients.

I’ll report on my experiences as they evolve.