By far and away, the biggest proliferation of connected health devices has been in the activity monitoring space, so I am inevitably trying, testing, wearing two or three of them at any given time.  And they remind me every day how active or inactive I am. 10,000 steps a day is a nice benchmark – most days I get to 5000. 7000 is high.  10,000 is rare.  Stated another way, I’m at a plateau in my quest for a healthier lifestyle.  How can I get there?  Do I have to give up some of the exciting work-related things that keep me a touch overcommitted?

When I first started monitoring my activity, it became quickly apparent to me just how inactive I am on an average day in the office.  Meeting after meeting means lots of time in a chair.  I just learned of a study from Australian researchers published two years ago that found that spending more than four hours a day in front of a computer or television was associated with a doubling of serious heart problems, even among people who exercised regularly.  Stated more dramatically, if you sit for more than 4 hours per day, your risk of heart attack is roughly equivalent to someone who smokes.  My own Body Media armband data from a recent Sunday illustrates this principle.  I was catching up on computer work in the morning and went out to do yard work in the afternoon.   The vertical axis is kilocalories and the horizontal axis time.

You can see just how low the calorie burn is during the first part of the graph (period of inactivity) compared to the second part.  When we sit for long periods of time, our body tells our metabolic machinery to make more fat for storage and this contributes to obesity, diabetes, hypertension and risk of heart attack.

So what is the solution?

I’m calling it “small frequent activities.”  You can use your activity monitoring data to help you with this.  If you are tracking steps, set a reminder on your phone or computer to check your step count a few times/day.  Find some activities that you can do which enable you to get in 10 minutes of walking or at least standing.  Fit those into your schedule in a way that is not disruptive.  Use your step count as a tool to measure success.

This is not to excuse you from setting a work out goal and a longer-term activity goal.  Think of daily step count as a batting average and these 10-minute excursions as individual at bats. Both are important to achieving success.  But if you work out for 30 minutes per day, and walk an additional 3000 steps, your heart attack risk will be lower if you spread those 3000 steps out in small, frequent activity increments.

Can the same logic be applied to calories taken in?  I don’t believe research has been published to confirm it, but intuitively it makes sense.  In fact, recently in the New York Times, Claudia Dreifus wrote about a mathematician, Carson Chow, who has built a mathematical model to explain why our country has put on so much weight over the last 20 years.  One of the things Chow notes in his model is that, “if you eat 100 calories fewer a day, in three years you will, on average, lose 10 pounds — if you don’t cheat.”  In one way, this sounds like useless advice because most of us vary our caloric intake on a given day by way more than 100 calories (there are 100 calories in 8 ounces of soda).  But there is something empowering about these data.  Dr. Chow has created a simulator that you can access to see how small changes in your diet or activity make a difference long term.

The insight here is to make small adjustments and stick to them. Climb a few flights of stairs each day and don’t put that teaspoon of sugar on your berries in the morning.  Take a conference call while walking around your office.  Sustained over time these adjustments lead to better health and they are not so overwhelming as the New Year’s resolution of going to the gym or the diet that drops 30 lbs in two months only to see it creep back on over time.

I guess the baseball analogy holds well again.  Hitters make adjustments in the middle of the game according to what the pitcher is throwing. They tend to get more hits the second time through the order. And if they do that consistently, their batting average rises.

Really, I’m not messing with you.  There is something to the idea of buzz word use in our search engine optimized world, but as I reflected on these three technology trends, I thought it worth pausing for a moment to reflect on just how game-changing each is for those of us in the connected health space.

Wireless/Mobile

Of all the top-of-the-hype-cycle buzz words in health care right now, mobile tops the list.  And while we probably can’t cure cancer, reverse aging and find the true meaning of life with mobile technology, it really has revolutionized the world of healthcare.

The key features that are so exciting are the miniaturized computing capabilities in mobile devices combined with their always on, always connected state.  Those of us who grew up espousing the vision of telehealth now have no excuse (from a technology perspective anyway).  We can videoconference from our iPads over 4G networks, or use our smartphones as data-collection hubs for remotely monitored sensor data about our patients.  We can message our patients in the moment when it’s most needed.  With mobile technology, we have the infrastructure to deliver on the promise of connected health: using objective information derived from patients to provide insights that lead to improved self-care, as well as the opportunity to deliver care in the moment or continuously.  Both of these strategies have been shown to improve quality and lower costs, particularly when applied to chronic illnesses such as diabetes, hypertension and congestive heart failure.

Big Data

This is the newest of our buzz words, but the healthcare implications are huge and exciting.  The term Big Data is a colloquialism referring to the power of collecting and analyzing large data sets.  The companies that provide storage and super-computing services are salivating at the opportunities to bring this technology to healthcare.

Three trends suggest that they are sniffing at a real opportunity:

• The first is the decreasing cost of genetic sequencing (now around $1000 and falling fast) combined with the exciting results we’ve seen when genetic information has been used to target therapeutic interventions in certain cancers.  The era of personalized medicine is near at hand. The computational power and storage needed to make genetic mapping part of an individual’s standard health information (the same way we all know our cholesterol level today) are staggering.  But the precision that genetic data affords will allow us to diagnose, prognosticate and recommend therapeutic interventions as never before.
• The second trend is the rise in consumer connected health and its intersection with the power of wireless.  Personal health measurement devices abound (FitBit, Withings, Zeo, etc.), each making their data easily available via wireless networking.  The tendency is to publish open APIs so the data from these devices can be captured and analyzed, yielding insights into consumer behavior. This is the cornerstone of the improved self-care value proposition of connected health.  This data collection and sharing will enable us to create phenotypic maps that are as unique and precise as the genotypic maps noted above.  Applying these data sets on individual and population levels represents an enormous opportunity for the Big Data folks.
• The third trend is the movement of bundled provider payment or global payments, otherwise known as the movement to Accountable Care.  Providers are waking up to the notion that organizations need to create highly individualized/segmented programs and interventions that enable efficient, but compassionate care and promote patient affinity and loyalty.  Once again, the opportunity here for data storage and analytics is huge.

The Cloud

Of all of our overused buzz words, this one seems to be the most ubiquitous in consumer advertising these days (possibly tied with mobile).  What does the Cloud really mean and what are the implications for healthcare?  Simply put, Cloud computing involves giant banks of connected computers that can handle multiple software applications and data storage at once.  Up until recently, sharing software applications or storing data was inefficient and had several downsides. Then, a few years back, someone developed software that would enable you to spread your application and storage across many networked devices.  This led to much more efficient computing.  All servers are efficient, operating at capacity. If an organization needs more computing power, it’s easy to immediately order more. Lastly if one computer breaks no one really notices because the load is balanced by others.

The implications for healthcare?  Both the power of mobile and the power of Big Data could not be achieved without the added innovation of cloud computing.  Storage of information in the cloud and access on  mobile devices allows for those devices to truly be windows into the world of information (ever notice how ‘dumb’ your iPad seems when it’s not connected to the Internet?).  All of that Big Data is stored in the Cloud.  These three innovations rely on one another for success.

It’s an exciting time.  Although the buzz word Bingo surrounding these three concepts is slightly annoying, the applications for healthcare are truly amazing.  Healthcare needs to be revolutionized and these technologies provide a critical substrate.

But actually that’s only true for some of us.  Those of you who were around to witness the amazing performance of Robert DeNiro in Raging Bull (1980) know he gained 50 lbs to play the character of Jake LaMotta in his later life.  After the film, DeNiro lost the weight promptly and easily.  He can be seen as slim and trim playing a priest in True Confessions  (1981) not long after. Even if you look at modern-day pictures of DeNiro (e.g. in Little Fockers 2010), he is no where near as heavy as he was when he played the senior LaMotta 30 years before.

Ok, now are you convinced that it is more complicated than simple calories in vs. calories out?

In Personalized Prevention, Part I, I reviewed the concept of connected health as phenotypic mapping and started a discussion of how one type of data might inform our use of the other.  In Part II, I discussed the psychology of engagement as applied to connected health interventions.  In this post, I want to use obesity as an illustration of how it might practically work.  I am not going to cover the public health story on obesity (how we live in a time of calorie excess and a dearth of opportunities to be active).  I know some of you will have that top of mind and may wonder why its not mentioned.  Yes, we’re all growing a bit more overweight as time goes on due to this trend. In general, we’d all benefit from eating more plants, more colorful foods, less animal-based food, less processed food and finding ways to be more active.  Today, I want to talk though about how the genetics of obesity may be able to help us create segments of the population that may respond differently to connected health interventions. Also, response to connected health interventions may be a trigger to prompt genetic testing.

Although I am not an expert on genetics, I have studied up on the genetics of obesity as I am giving at talk at BioIT, May 25, at the BIO meeting in Boston.  We are a long way off from having exact obesity genotypes the way we now do for certain cancers and the like.  But the genetics argue that we can distinguish at least 5 genotypes:

• Thrifty genotype: low metabolic rate and insufficient thermogenesis

• Hyperphagic genotype: poor regulation of appetite and satiety and propensity to overfeed

• Sedens genotype: propensity to be physically inactive

• Low lipid oxidation genotype: propensity to be a low lipid oxidizer

• Adipogenesis genotype: ability to expand complement of adipocytes and high lipid storage capacity

Imagine a world where we knew this information before or shortly after birth.  Could you envision someone with either the thrifty genotype or the sedens genotype being targeted for an exercise program involving activity monitoring and customized motivational tools as were discussed in Parts I and II? If we got to these folks when they were young, do you think we’d have the ability to reorient their lifestyle choices for the better?

One example worthy of consideration is the partnership we have with the Boston Public Schools to encourage activity in children from some of our underserved schools.  I blogged on this some time ago.  The 2011 program was such a success that we’ve expanded it this year, and we are just launching the spring 2012 program.  The children who took part last year shared numerous stories about how wearing a smart pedometer, getting weekly feedback and participating in a classroom competition on activity helped them become more aware of how active they are, encouraged them to be more active and even bring the culture of activity into their homes.

When people are on a connected health program,  we can determine at an individual and at a population level who is active and who is not responding to the program. Imagine that we could take those data and compare them with genetic data to elicit finer and finer comparisons.

I am wildly enthusiastic about personalized connected health, about the opportunities to combine genetic and phenotypic data to gain insights about individuals and about personalized prevention.

 I don’t spend much time on Facebook.  Its not that I’m antisocial, but on a given day if I get through my email inbox by 10 PM, I feel good about myself.  That leaves little time for social networking.  I haven’t played Angry Birds or Farmville for the same reason.  I just have other priorities.  I grew up in a family of plain-spoken, simple Vermonters.   My dad was a kind and gentle man, but when he raised his voice we all took notice. And, because of his ‘kinder-gentler’ side and plain-spoken character, my brother and I took him quite seriously and felt it was wise to comply with his wishes.  Also, my folks both had a deep sense of the value of good health and strove to achieve a healthy lifestyle.

I believe this combination of circumstances and history is what is behind my individual connected health psychology.  I am responsive to authority – a compliant fellow who sometimes forgets, but when reminded complies.

In Personalized Prevention, Part I, I talked about the power of genetic data combined with the phenotypic mapping that connected health tools give us to micro-segment the population to a level where we have a completely unique, individual genotypic and phenotypic profile.  The example I used was obesity, suggesting that with these two technologies colliding, we’ll have the opportunity to identify individuals at risk for weight gain early in life and put them on connected health programs to keep them trim.  Many readers pushed back and the essence of the push back was, “micro-segmentation alone is not the answer.  Even providing individuals with data on their caloric expenditure in the context of their risk for weight gain will not solve this problem.”

Folks, I couldn’t agree more.  The medium of blogging is best suited to ‘bite-sized’ writing and the first bite in this series was about the micro-segmentation piece.  Today I want to spend time on the psychology of engagement, as I believe it is critical to the success of connected health and can also be highly individualized.

The first point to re-emphasize is that connected health data alone do not solve any problems, except perhaps for the very small group of highly motivated fitness buffs and quantified selfers (maybe 10% of the population).  There was a time when companies in this space boasted that they could ‘get biometric data into the PHR or EMR.’  Work done at the Center for Connected Health and by others has demonstrated that this is nearly meaningless.  We’ve relearned the old adage that data is not information.

Of course, it’s all about what you do with the connected health data.  Objective data inputs are a critical component of the solution – self-reported data is also nearly useless – but the success of connected health programs is all about the psychology of how we engage program participants in these data in order to motivate them to improve their health.

Most companies who have focused on engagement have not bothered to include the objective data stream because of the cost of sensors and the complexity of integration.  Most have also touted one engagement strategy or another as the key to success.  The options these days seem to be:  gamification, social networking, coaching, reminders, incentives and punishments.

Lets go back to me as an example.  If my employer rolled out a wellness program and the engagement tool was social networking, I am afraid I would not be successful in it.  Likewise for competitions/games.  But set me up with a reminder system and an automated coach with an authoritarian tone and I will improve my health behavior.

Purveyors of wellness programs tout their success, e.g., ‘40% engagement after 6 weeks.’    My question is what about the 60% who didn’t engage?  It seems to me we understand the tools and triggers to get closer to 100%, but we must admit that one size does not fit all and do some behavioral segmentation at the outset to tailor programs to what individual buttons need to be pushed.

Healthrageous comes the closest to offering this type of approach (I say this with as much objectivity as possible, as a co-founder and share holder).  Their vision is to know so much about you that they can anticipate the engagement experience that gets you involved in a way that you feel they know you intimately.  This will come about through a machine learning environment and as more and more participants take advantage of their programs, they’ll do better and better at this.  In the meantime, I think we can start with a simple set of questions designed to paint a profile of each individual that is akin to the one I wrote describing me at the beginning of this post.  We’re working on that at the Center. I am excited to share our learning as we go forward.

To learn more, I initially checked in with some local geneticists but their focus was on identifying genetic mutations in various cancers in order to predict therapeutic response.  This fascinating area was recently discussed in the NEJM in a piece called Preparing for Precision Medicine.  However, that is not exactly what I’ve been dreaming about.  I was thinking more about the potential to identify folks with propensity towards chronic illnesses like obesity, diabetes and hypertension using genetic techniques. Then, getting these individuals on connected health programs in an effort to change the course of their personal health history, before they wound up with these often avoidable, costly conditions.

A couple of months ago I had an email and subsequent visit by George Church, the world-famous geneticist and founder of the Personal Genome Project.  This conversation was pivotal for me as George is interested in collaborating with researchers who can track and map phenotype in such a way that we can match to genotype.  Our team is meeting with him again this week and I’m looking forward to an exciting collaboration to emerge.

The intersection of connected health and genetics is interesting and complex terrain, and I am going to break up the discussion into several posts.  Today I just want to introduce the concept of Personalized Prevention and get your reaction to it.  Subsequently, there will be posts on some of the lifestyle diseases that have a genetic component and how we might use connected health to address those conditions.  As a start, I want to make sure we are all on the same page as to the meaning of a couple of terms.

A person’s genotype is the manifestation of the DNA in their cells, i.e. genetic information.  An individual’s phenotype is the expression of those genes in terms of proteins, cell behavior and ultimately human traits and behaviors.  Some time ago, the visionaries in the world of genetics coined the term personalized medicine to refer to the idea that if we know your genotype, we can be precisely predictive of your risk of getting certain diseases, as well as your response to certain therapeutics.

The $1000 genome is nearing reality.  As a society, we’ve not yet begun to appreciate what this means.  There are all sorts of implications but the most mind-bending is the idea that we will eventually be able to create diagnoses that are unique to you and therapeutic responses that are equally unique.

Consider that we are constantly bombarded with messaging about health care that goes like this: “40% of patients had a positive response as compared to placebo.”  This sounds like a triumph at the population level, but what if you are one of the 60% that would not respond and we could predict that?  One of my professors was prescient on this matter back in the ‘70s and said, “Patients don’t really care what their percent likelihood of an outcome is.  For them, the outcome is 100% success or failure and they’d like to be able to predict it on that  binary level.”  Until very recently we’ve only been able to offer patients a sense of risk, but the time is coming where we will be able to be much more confident in our choices for them.

Connected health does this too.  It is the ‘phenotypic map’ that corresponds to the detailed ‘genotypic map’ the geneticists come up with.  Consider if we have a population of workers and we want to incent them to be more active.  Connected health can provide, at a minimum, a very precise measurement of the outcome.  It enables folks who are investing in the program to see — both at a population and individual level — whether the program is resulting in increased activity.

Healthrageous has had success with this in the employer/health plan market.  They are giving customers precise data on how their populations respond to various incentives and programs to increase activity and lower blood pressure. The company will be moving next into diabetes.  Healthrageous can measure a program’s success quite precisely, reporting % engagement, % that stick with the program through the end and % achieving clinically significant results.  In all cases, they are creating new industry norms, but equally exciting is the precision of their reporting.

The illustration below lays out the concept of Personalized Prevention graphically.  Individuals who are at risk to develop a chronic illness can be identified, then offered connected health programs as a tool to prevent progression.  Likewise, individuals who are not responding to connected health programs can be identified as candidates for genetic testing to uncover the reasons why not.

I think the best example of how this might work is for people who are overweight or obese.  There is now good evidence that people who gain weight reset their satiety thermostat, i.e., when they lose weight even to a previously low weight, their body sends their brain a signal that they are chronically hungry, as if trying to get them back to their overweight state.  Tara Parker-Pope covered this wonderfully in a recent NY Times Magazine article called The Fat Trap.

I’ll write more on this next time, but to me it makes great sense to try to identify folks at risk for weight gain and educate them about activity using smart pedometers.  The feedback loops that connected health provides allow for an intense education into how one can easily increase activity.  It seems that, knowing there is a risk of weight gain, and knowing that this extra weight would be incredibly hard to take it off, an individual might be motivated to sign up for an activity monitoring program. Finding the right motivational triggers is, in part, how we create Personalized Prevention.

So what do you think? Does the concept of Personalized Prevention make sense?

Right out of the gate, we health care providers have a big hill to climb.  We are the ones who remind you that you are sick. Who wants to be engaged with that?  Once patients get into the mindset of being sick, the context becomes pain, suffering, inconvenience, depression, time out of work, rehabilitation, and on and on. It’s no wonder that patients don’t engage much (other than the occasional masochist among us).  And the conversation immediately gravitates to whether insurance will pay or not. We’ve observed patients in our connected health programs who are happy to go to the sporting goods store to fork over their own money for a heart rate monitor so they can watch their heart rate during a work out, but baulk at paying for a blood pressure monitor to be part of a hypertension program.  After all, fitness is your own business, but when we’re talking about sickness your insurer owes you….

A little while back, some airports introduced those whole body scanners – the ones where you stand with your hands over your head and the machine takes an image of your body to rule out the presence of weapons, explosives, etc. Given all of the threats from shoe bombers to liquid bombers that have made it through traditional metal detectors, I thought this was a good idea.  More monitoring to insure my safety is a good thing.  But the outcry from the libertarians and the privacy crowd was deafening.  It was newsworthy for weeks.  All kinds of concerns about TSA agents peaking at one’s body profile, etc.

So imagine my surprise when I talked on the phone the other day with folks from Unique solutions.  They use the exact same technology in the shopping mall to allow consumers to create a clothing size template that is unique to them.  Armed with that scan information, you can go to certain merchants to buy highly customized clothing of a fit that is unique to you.  When I heard about this, I wondered how widespread it is, but right after the phone call I saw one of these in a mall near my home.  Consumers are flocking, apparently.  No complaints from the privacy crowd on this one.  Who’d a thunk it?  Essentially the same scan.  Same risks best I can tell (couldn’t an errant employee view your scan?). But no outcry.

This is fascinating.  There are two angles to think about here. One is the psychology and the other is the health application for this technology.

I’m motivated to think about how many ways we can re-invent how we engage patients about their illness.  By way of analogy, I’d say that we as healthcare providers are like the TSA with the airport scanners.  The alternative therapy, fitness industry is like the mall-based solution.  Two ways of viewing the same challenge. What this tells me is that we have to think hard about how we communicate with patients and develop ways to be less serious, less dour and more hopeful. I don’t mean to say healthcare should become a joke, but there is a long way between comedy and the way we talk to our patients now.

The applications for this technology in health are interesting to ponder.  Overweight is not one uniform problem.  Abdominal fat has more dire health consequences than other types of fat.  There are other examples of where body habitus can help predict health outcomes.  People who engage in serious exercise programs can add muscle mass as they lose fat, obscuring the value of BMI as a reporting tool.  I could imagine a new metric beyond BMI which would use one’s unique body scan as a tool to predict future health state and to track response to weight loss or diet initiatives.  Add a wireless weight scale and a smart pedometer and things start to look very interesting.

Tell me what you think about this.  Why do people raise a fuss about a technology in one location but embrace it as hip when presented in a different context. Does that give us clues as to how we should design our communication tools and patient engagement initiatives?  Do you see health care applications for this type of scanner? Let me know.

While interesting reading, to me, the piece seems flawed from two perspectives.  First, the article is highly focused on an acute care view.  Dr. Detsky notes that he practices in an inpatient setting and the piece reflects this bias.  Secondly, it is truly difficult to really know what patients want when you are in the role of the doctor.  I can fully say that when I take on the role of patient, I can’t really do so in a pure way, completely divorcing myself from my role as a doctor. I don’t think its possible for a physician to fully embrace the role of patient, possessing the insights into health and disease that years of clinician training and medical practice.  So, despite his best efforts, I don’t think that Dr. Detsky can tell us what patients really want.

It’s not that I think the JAMA article is off-point but rather incomplete.  There is so much more to health care than what goes on in the acute-care/inpatient setting. When we are sick enough to need an inpatient bed, most of us want to be cared for in the most profound way.  This perspective on care doesn’t translate well to the two other domains of health care that I routinely think about – namely health/wellness and chronic illness.

Focusing on health/wellness and chronic illness, I’m going to risk falling into the same trap I’ve criticized Dr. Detsky for: I’m going to take a stab at what I think patients want. However, using the blog format for this communication allows me to take advantage of social media allowing for feedback, especially from those of you who are not doctors!  So, please help me with this.  If we hit a home run, the output from this dialogue will be fodder for our Symposium and for other writing projects I’m involved with.

In the realm of fitness and wellness, I believe:

• We want to live forever in a healthy, painless state.
• We want our health care professionals to take us seriously when we engage them in dialogue around alternative approaches to diet, exercise, nutrition, sleep and longevity.
• We want integration of our fitness/wellness world into our healthcare world. Right now they are silos that don’t talk to each other.
• We want to engage our healthcare professionals in conversations around all of the data we’re collecting about ourselves with consumer-level devices (and not have those data dismissed as unimportant).

In the realm of chronic illness:

• We want low-friction solutions to help us cope.
• We don’t want to be told we’re sick and we don’t want to be treated as sick.
• We don’t want to face the future consequences of our chronic (often symptomless) illnesses.
• We want to feel as if we can dig ourselves out of the chronic illness abyss – to feel hopeful.

In general:

• We want good service.  A person to answer the phone.  A kind voice.  A caring and supportive person.
• We want to be treated with respect.
• We don’t want to spend time in the doctor’s office or hospital.
• We want simple, consumer-friendly processes for accomplishing tasks like scheduling an appointment or refilling a prescription.
• We want access to professional advice (Dr. Detsky and I align on this one).
• We want transparency of process – ‘a play book on how to get things done.’
• We want a way to take charge of coordinating our care without complex, repetitive and obtuse processes.

For centuries, patients have put up with tremendous inconvenience and friction to move themselves through the healthcare system.  They’ve put up with it because the only way to get care is to visit the doctor and the system is constructed to make the doctor’s work life as productive as possible, not to make it easy for patients.  I expect that to change in the coming years.  We’ll see more patient empowerment,  more instances where consumers can make their own health care decisions without  a physician and more opportunities to streamline care delivery making it simpler and more patient-friendly.

What do you think?  Did I get it right? What’s missing? Let me know.

In a fee-for-service world, physicians are both the fountain of relevant knowledge and the source of all revenue.  So we have built our workflows, systems and processes around their comfort and success.  As physicians succeed, so does the rest of the healthcare juggernaut.  I know other industries fall victim to these kind of MC Escher-like business models, but it seems particularly acute in healthcare.

My belief is that this paradox makes our industry highly susceptible to under-imagining what real innovation could look like.  We have some pretty deep blinders on, it seems.  One of my favorite Steve Jobs legends is that when asked about the consumer research that led to the development of the iPad, he quipped, “We don’t expect consumers to be able to tell us what they don’t realize they need.” [I am paraphrasing, but this is reasonably accurate.]

As we trot out our prized innovators in healthcare, we don’t seem to hear that kind of talk.  We hear about improved ‘door to balloon time’ in the care of acute MI, about using Lean to improve hospital work flow and supply chain management, about programs to encourage more generic drug prescribing and about decision support systems that help doctors avoid wrong dosing or prescribing medications that negatively interact with one another.  Indeed these are innovations, but they are all innovations that Christensen would classically call incremental.

At the Center for Connected Health we purport to be patient-centered in our approach.  I think we do a decent job at this. But try as we might, it’s hard to get at two things. One is a true patient perspective that is imaginative, articulate and consistent.

I’m making a pitch to our Symposium organizers that this year we devote a good deal of space on the program to drawing out the patient perspective from multiple angles.  We’ll see how persuasive I am.

The second challenge is finding patient advocates who do not feel intimidated in front of an audience.  We also have trouble finding advocates that are ‘pure’, i.e., folks simply disguised as patient advocates but really championing a different cause.  I have to give thanks to the tireless work of folks like Dave DeBronkart and Sarah Krug who are tireless advocates and my friends at the Society for Participatory Medicine. But we need more like them.

In the meantime, consider with me how we as innovators should best create the programs, technologies and services that chronically ill patients don’t know they want or need yet. How do we develop devices to motivate and monitor activity for the fitness buffs who think they are content with a good pair of running shoes and a gym membership? How important is the patient perspective in the development of connected health programs and services?

In my next post, I’ll share with you my impressions of an article that appeared in JAMA last  month about patient perspective.

There has been a lot of hand-wringing and discussion about how to fix this problem.  There is even a new series of buzzwords entering our lexicon (ACO, patient-centered medical home, bundled payments, shared savings, bending the cost curve – this is an incomplete list).  This last one amuses me – bending the cost curve.  Try as we might, those of us in organized healthcare can’t come up with ways to really cut costs.  We proudly talk about strategies that may keep costs from going up as quickly.  The goal of keeping medical inflation at the same rate as general inflation is often mentioned.  The trouble is, we’re starting out spending so much more than any of our developed world comparators. Yet, can we claim that the quality of care we deliver is as good as other nations that spend considerably less?  So is ‘bending’ the cost curve really enough?

One reason we have so much trouble is that so much of our costs are tied up in labor (56% according to one recent study).  As someone recently quipped, “in healthcare, a dollar saved is a dollar of someone’s wages lost” – or at least 56 cents of wage lost. Also, as classically described by Christensen in The Innovators Dilemma, most of our decisions are made either by physicians or in consultation with physicians. So many times over the years, I’ve witnessed interesting ideas brought forth and dismissed out of hand by physician leaders. “Our patients would never go for that….”or ”That would not work clinically,” etc.  Of course clinical judgment plays an important role in healthcare delivery and the perspective that a physician brings is valuable.  But when we’re talking about efforts to really manage costs, we have a conflict of interest. Can decision-making physicians really look objectively at solutions that are presented which might result in less demand for our services and may affect our income? After all, we’re only human.

Last week, I was privileged to be on a plenary panel at the 3d annual mHealth Summit in Washington. My predecessor on the panel is the President of Apollo Hospitals in India. He gave an impassioned speech (effective too, laced with humor and using his booming voice and stage presence) declaring that mHealth would go nowhere unless doctors were compelled to adopt it.

Our Center stands on the border between two very different worlds.

In one world, our healthcare delivery system is facing the hurdles alluded to above. Partners, the delivery system we work for does its best to move 7000 physicians and a large hospital system to a new reimbursement model and, consequently, a new care model.  It’s going slowly, but we’re viewed as leaders and we’ve done amazing things to try to get us there.

In our industry, there is more talk than ever about the potential of connected health, but not too much implementation just yet. In fact, the predominant strategy floating around involves hiring more staffing for better care coordination and improved quality.  Wait, didn’t I say that 56% of costs are labor?  So we’re adding more labor?

In the other world our Center lives in, consumers are moving to take charge of their own health, adopting connected health as either a personal fitness aid, or as part of an employee benefit offering (e.g., the work that Healthrageous is doing).  This too is in its early stages, but as I watch it unfold, I’m struck by the possibility that the health care cost crisis may be solved by innovation that occurs outside of the traditional healthcare delivery system.

One example that is interesting is retail clinics. They are flourishing now.  They are taking business away from our primary care physicians. No one notices because they are all so busy, but as retail clinics grow, at some point we’ll notice.  Another trend to follow is how Walmart re-invents primary care.  It’s early and speculative, but I’ll bet a week’s pay that this model will include some component of home monitoring and surely lots of opportunity for patient/consumer self-care.

At our Connected Health Symposium last month, we held a lunch for several companies who are ‘non-traditional’ entrants into connected health. We had participation from a beverage company, a consumer products company, and a large retailer to name a few.  Why are they all interested in connected health?  I’m just learning, but I’m sure if they smell a business opportunity it is unlikely to involve mainstream healthcare.

So keep an eye peeled for something to happen.  Some routine service that you think you must see your doctor for will be delivered online or in some much more convenient way.  God knows, today’s mainstream healthcare delivery is about as consumer unfriendly as you can get. So once something that competes and is convenient, a true sea change should be upon us.

What do you think? Can you conceive some truly disruptive concepts that will take business away from mainstream healthcare delivery and still deliver quality care?

In preparation for the meeting, I reflected back on the days when my colleague Doug McClure, now CTO at Healthreageous, and I envisioned what would be needed to bring connected health mainstream.  One area that has been troublesome has been the ease with which we can extract data from various home-monitoring sensors (blood pressure cuffs, pedometers, glucometers and the like) and get it into the cloud for analysis and utility.  At this point a variety of strategies exist, from plugging a device into your computer (via USB port) to the wireless home hub, to embedded mobile chips in the sensors themselves.  This cacophony suggests an integration nightmare.  Long before we founded Healthrageous, Doug and I thought device connectivity would give us an edge.

Fast forward 5 years and its hard to find a sensor that does not have some sort of wireless connectivity.  Many of them have connectivity integrated through a smartphone or home hub directly to the company’s website.

Device connectivity has largely been conquered.  So is that the market?  Well, there are countless sensors that you can buy and easily start tracking your own physiologic info and learning from the experience.  It is this phenomenon that was the genesis of the Quantified Self movement, now with meet-ups in many cities world wide.  It seems like selling products to this burgeoning market of self-tracking zealots might make sense.

The challenge is, it appears to be about 10% of the population.  Lots and lots of devices chasing a small and finite population…..

Then there is the deluge of smartphone apps.  More than 10,000 of them last count.  So are apps the answer? Well not exactly. It seems that 26% of the time apps are opened zero or one time.  Further, 75% of the time folks stop opening them at about the 10^th try.  That is kind of discouraging. It seems that apps alone are not the answer.

Maybe there is some way to marry these two concepts. We know that data=self entry is a particularly weak strategy as it is subject to social desirability bias as a confounder. We all want to look good and healthy so we’re prone to report those readings that support this and somehow not report those readings that do not.

Healthrageous has taken the path of focusing on dynamic personalization.  With all of the data being collected about you, they are able to craft a uniquely motivational program of messaging for you. And it’s working.  Their early results show positive improvement in both blood pressure and activity monitoring.

Likewise Runkeeper is doing some interesting integrations with devices as is Gravity Eight.

These are just a few of the companies that now take advantage of the near ubiquitous tracking data that can be derived from consumer-level sensors, but seek to surround those data with strategies to draw the consumer in and create the opportunity for sustained behavior change.

The tools are:  social networking, incentives, games/contests, and automated coaching.

So if you are in the business of recommending investments or partnerships in the rapidly changing/growing space of connected health, the data is coming in.

Companies that figure out how to present objective data to consumers in a compelling way, combined with motivational coaching, social networks and gaming will succeed. Not all of these tools will be necessary.  But the trick will be finding out which one suits each individual.  Those entrants that have a highly customizable platform and an ability to sense what you as the consumer will respond to, will be the winners.