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Serendipity, Personalization and Connected Health

April 24, 2013

In a world where most folks change jobs every couple of years, people are often amazed to hear that I started work in connected health 19 years ago.  Implicit in their amazement is a question, “Why did you stick with it so long?”  The quickest response is that the work we started back then is not yet finished.  A more accurate answer is a bit more complex.  First, we have never wavered from a clear vision of how healthcare delivery needs to change.  We’ve been able to recruit a truly stellar team of people to work with.  And, we’ve had some good luck along the way.  In this post, I want to tell the story of a couple of those serendipitous moments, what they meant to us and how we moved beyond them.

The first goes back to circa 2000 when the Medicare payment structure for home health changed to prospective payment.  The Center for Connected Health was formed in the mid 90’s with a vision that connected health could be an antidote for capitation.  Capitation never really took hold in the mid ‘90s, and thus connected health stayed largely in the realm of pilots and experiments.  But, when prospective payment hit home care, the leadership of what was then called Partners Homecare saw telehealth as an opportunity to succeed under this new payment model.  We then had our first real customer.

The serendipity comes in when we sat down with our home care colleagues to talk about where to focus our efforts.  We chose congestive heart failure (CHF), because it was costly, prevalent and the source of a lot of home nursing visits.  What we didn’t appreciate was just how suited CHF is to connected health as an intervention.  CHF management is mostly about fluid management.  Weight is a pretty good proxy for fluid status, and dietary interventions (largely around salt and fluid intake) are usually effective at controlling fluid.  Thus the feedback loop of daily weight combined with just-in-time nursing interventions, usually by phone, resulted in a reproducible improvement of patient care, a decrease in hospital admissions and a net lowering of the cost of care.  With this early success, we formed the connected health initiative and began to work in other areas of chronic illness management including hypertension, diabetes, mental health and asthma/COPD.  Some of these programs were more successful than others, but the impressive results that we saw in CHF spurred us on to work in these other areas.  Had we started with COPD, where the relationship between any one variable and clinical deterioration is much less clear, we probably would have not gone in this direction at all.

One of the insights from this early work was the power of feedback loops.  Measuring weight in those CHF patients and following it up with just-in-time teaching about salt and fluid led to a remarkable trend in improved patient self-care.  We began to design programs around the idea that objective, numeric feedback is an important part of connected health program success.  The development of wireless sensors, mobile apps and shared APIs created a technical infrastructure that allows us to easily gather numeric data from our patients and feed it back to them as well as to a clinician.  We showed great success with this method in hypertension and diabetes.  The Quantified Self movement was born.  A number of companies sprung up using various trackers to monitor health and fitness information (Runkeeper, MapMyFitness, Fitbit and our own Healthrageous are just a few examples).  In each case, and in our own research, we followed outcomes for a group of participants defined from a disease perspective.  And we were happy that we could increase engagement to 60-70% over the course of a program.  We felt good about the combination of objective feedback loops and just-in-time clinician involvement.  But something was not quite right.  If our approach was so good, why weren’t we hitting closer to 100%?  And why did we never do better than 60-70% at a population level?  The dilemma is illustrated in the figure below.

Intervention graph

I’ve been traveling to meetings and conferences for the last couple of weeks and heard a lot about the power of social interactions to change behavior.  Lots of companies are coming up with social-based interventions – ask your friends to encourage you to get more active; compete as a team; set goals as a group, etc.  I heard others say with confidence that incentives are the key to behavior change.  Still others say health coaching is key and of course there are the proponents of making healthcare a game to encourage engagement.  If you look at the chart above and the population-level outcomes for any of these interventions, I think you can objectively conclude they are all RIGHT and they are all WRONG.  Right because for some significant part of the population, each respective strategy resonates, but wrong because for others it does not.  Let’s face it: we’re far too complex and different as individuals to have a one-size-fits-all solution.

Having started with CHF, diabetes and hypertension – conditions where a physiologic measurement can be used as a tool to drive engagement — we in turn learned about how no single motivational psychology resonates with every individual.

We continue to observe, to learn and to adapt our thinking, as most recently as this past week.  I was chatting with a friend the other day and she confided in me that she is underwhelmed by the use of tracking as a method for healthcare improvement.  At this moment another insight crystallized for me.  Some people just don’t respond to quantitative information.  This friend told me how she could really see the opportunity for social media to increase engagement, but just was not convinced that self-tracking was that relevant.

This opens up an interesting new vista for us.  Not only do we have to work on personalizing our motivational interventions, but we have to figure out how to engage people in other ways than with feedback loops.

Our understanding of the value of feedback loops is that they provide measurable, objective data (there is lots of good evidence that we are generally terrible at estimating quantitative information); they allow for goal setting and measurement of achievement; they generally increase awareness of the variable being followed (e.g., weight, steps, blood pressure, etc.) and they allow for some reality-check or accountability (it turns out self-deceit is quite popular when it comes to health).

So let’s hear from all of you non-quantified-selfers – those of you who do not really see quantified information about your health as interesting or motivating in the least.  How do we achieve the goals of objective measures, goal-setting and accountability without using self-tracking?

Note: Situated in the heart of Boston, and within the Partners HealthCare network, we at the Center could not help but be personally impacted by the tragic events at last week’s Boston Marathon, as were citizens around the world.  Much has already been said about the bombings, the incredible and inspirational reaction of our police, first responders, bystanders and healthcare professionals, and the outpouring of compassion and support for the victims and their families.  There is not much more I can add, except to welcome the thoughts and prayers of our friends and colleagues, as we join together, to move forward, heal and stand strong for Boston.

30 Comments leave one →
  1. Ron Pion MD permalink
    April 25, 2013 4:53 pm

    Suggestion: Introduce all the successful people/patients to others wishing to be successful and the percentages will rise. Consider introducing patients and their physicians, nurses, friends and others to a new emerging affordable collaborative tool…..zoom.os.

  2. April 25, 2013 8:04 pm

    Thank you, Ron

  3. Ron Pion MD permalink
    April 25, 2013 8:31 pm

    Error.…….offering ‘connectivity’ to all

  4. April 26, 2013 10:12 am

    It is not that different from other forms of effective management these days. A manager simply showing a proactive interest helps a lot to shape behaviour and focus attention.

    Mostly healthcare professionals do not behave like modern managers. They are prescriptive and reactive and this is a role that patients have come to expect. A manager genuinely interested in my performance will be proactive and prompt me to draw my own conclusions that I should pay more attention, say, to monitoring my weight.

    Speaking as a patient, I have NEVER been called by a physician simply to enquire whether the pills are working, or how I am doing with our agreement to make lifestyle changes. Were they EVER to do this, my motivation to comply would be much higher and I might even start keeping track of my weight loss to show them.

    Sympathies for Boston by the way.

  5. April 30, 2013 11:46 am

    Chris Johnson is on the right track. We have found that older patients, in particular, are of a generation that will respond eagerly to what an authority figure like a doctor will tell them to do and follow up on. The key may be “doctor engagement.”

    • April 30, 2013 12:17 pm

      Yes, we see this phenomenon in older folks as well. We’ve used the term ‘the sentinel effect’ to describe it. It does not resonate with everyone though.

  6. April 30, 2013 11:54 am

    First, I think that you’re making a premature assumption that data won’t speak to people. What people require is that the data is collected seamlessly and that the data then provides something of specific value back to them. Once these two things happen, we’ll see people benefiting from data. Unfortunately, right now collecting the data feels like work and the visualizations and use of the data doesn’t provide specific value to the end user.

    That said, the biggest motivator can often be peer pressure. It won’t feel like peer pressure and it will be positive peer pressure, but it’s a drug that has no shelf life.

    • April 30, 2013 12:16 pm

      Perhaps I am premature. It took me by surprise, though, to meet people who find objective data about their health irrelevant to their view of how to improve their health.

  7. April 30, 2013 12:09 pm

    I really like this questions. I am not a QS participant, but heavily involved in patient engagement. I think this issue stems from the natural consequence of data collection. When data is collected that is individually important, but not mutually material it is not valued, or can feel to be an imposition.There is no nexus point. The nexus point occurs when the data is what the provider wants and what the patient knows, or the patient wants and the provider knows. This is the golden spot. Because our current system is so disjointed, this nexus point is difficult to find. So we look for evidence of who and what is right and swirl to get evidence, versus finding or encouraging what is mutually material.

    I am encouraged by efforts to get patient generated data in the EHR, including structured and not structured data. I am also encouraged by the use of DIRECT for patients and providers, staring with the Blue Button Plus initiative. QS experience can inform this work.

    • April 30, 2013 12:14 pm

      This is really interesting. I have to think and process. Very helpful.

  8. April 30, 2013 12:55 pm

    Do insurers underwrite a portion of the cost of home health devices? I am a newly enrolled QS participant asked by my physician to periodically gather and report certain health metrics. I am aware of devices which will suffice but they are not inexpensive. Any thoughts
    on reimbursements?

    • April 30, 2013 8:21 pm

      I’m not aware of any 3d party reimbursement for monitoring devices.

      • April 30, 2013 9:08 pm

        Thank you JK, may I call you JK, for your personalized response. I posted where the state of Az has mandated reimbursements for telehealth in certain geographies. Is this a movement unto itself; Arizona, really? Isn’t funding the base question of all issues in the US?

      • April 30, 2013 9:11 pm

        Arizona has always been ahead of the reimbursement curve, and though i don’t know the details of all that they are reimbursing, my hunch is that it is more in the realm of virtual visits than home monitoring tech

  9. Paul Dattoli permalink
    April 30, 2013 1:03 pm

    Hi Joe
    I think leveraging Social media is clearly the way to go. Representing a person’s health in a graphical fun kind of manner on their SM device sounds like a great direction to investigate. Don’t show me numbers that I don’t completely understand, show me pictures. Preferably fun pictures when signs are good, cautious pictures when signs are so-so, and danger pictures when I should get my butt to my doctor, or hospital. Or as one reply stated, “call me”. Each year it seems more small monitoring devices that are less disruptive and capable of sending information to your smart device are popping up. I believe the efforts and the mission of the Center are right-on and making great progress.

    On our Boston Marathon event:
    As we were all informed quickly of the event and deeply saddened to hear of the casualties, I was impressed by the role Social Media played from the outset. In nearly every picture or video clip that hit the air, you could observe people communicating via their smart handheld devices. There was a plethora of communications going on all over Boston and the surrounding cities and towns throughout this event. Just as our outstanding police, authorities, and healthcare organizations joined forces and handled the situation so well, our people rallied behind them and leveraged social media to add millions of eyes everywhere throughout our state.

    Boston – that’s our home!

  10. Ann Rosas permalink
    April 30, 2013 1:15 pm

    I love this topic – I am trying to become more of a quantified person. To that end, I just bought a FitBit One tracker. What an easy device to set up and use! I find myself delighted with earning badges for steps or floors, etc. I can more easily connect my behavior (movement) with my health progress goal of becoming more active – and that is the reason that I think folks will find meaning in connected health on an individual level. Very few folks will want to quantify themselves just to help the ‘greater good’ but if it allows them to better understand their own health behaviors and how they (themselves) create wellness they will jump on it.

    I would be willing to share my FitBit data with my doctor, if there’s an easy way to port this data. My daily step count could be integrated into my EHR, but so far no one is asking for it.

    I would love to see seniors using connected health as an adjunct to traditional office visits – why drive 5 miles just to have your doctor check your blood pressure? We need reimbursement for this type of care, so that it can become a usual and customary part of medical care for all ages.

    Ann Rosas, MHA
    Community Resources Manager
    Senior Helpers

    • April 30, 2013 8:20 pm

      glad you’re enjoying the Fitbit I like the design of this one, myself.

  11. Matt Emerson permalink
    April 30, 2013 1:36 pm

    It seems to me that one of the motivating factors with being a part of a “quantified self” program is that people feel empowered to make a change in their health. When they see the numbers go in a positive direction it gives them a positive feeling. The people who do not feel engaged with “the quantified” self may need a person to tell them they are doing a good job rather then interpreting it from the number. They may respond more to positive conversation then to a positive reading. There is a certain emotional detachment that comes from relating numbers to your health status instead of a person you trust saying “keep up the good work”.

  12. Dave Dickinson permalink
    April 30, 2013 1:49 pm


    I think you are on to one of the most critical issues within connected health. We came across your friend’s data skepticism many times at Zeo, and we realized that our ability to transcend from quantified self early adopters into the mainstream world of the sleep concerned would require far more than just the raw data itself. The gift wrapping matters as much as the present inside. Moving from Quantified Self early adopters to a mainstream Motivated Self will not be easy, but here are some clues that may help others as they take on this challenge:

    • All data is not created equal (to motivate). Some of the health data that various sensors are generating is simply not that provocative or intrinsically motivating. The more intuitively obvious the data is, the lower my engagement will be. Within sleep, we realized that simplistic sleep/wake data is simply not very motivating and will relegate this health metric to the back seat of behavioral change. However, when you are able to help consumers discover a new health unknown, such as the amount and vital roles of their REM, Deep and Light sleep, this new level of shock and awe may provide a better catalyst to engage the mainstream. Another example might be a cholesterol test where the underlying HDL (“good”) and LDL (“bad”) data may be more motivating to encourage statin compliance than just my overall number alone (because I may be more scared). I believe that the level of data granularity, and then the scales that are used to convey what is high, low and average, are very important considerations to not only catalyze interest but then to also provide enough statistical significance for the critical positive reinforcement rewards that will be needed later to sustain the changed behavior.

    • Relate the data to something else I care about NOW. Unfortunately, consumers are not motivated enough to take action when the resulting benefits are longer-term and/or too scary, like the prospect of getting a terrible illness one day in the future. This is one of the greatest challenges of preventative healthcare. However, other ideas may be able to help here. For example, we found that comparing your personal sleep data to others your own age was far more motivating. Most people do not want to age before their time and well understand what being older than your age may imply as it relates to their performance, sex appeal, career development, closeness to the prospect of dementia and more. The cosmetic industry is a very big business, and Real Age® built an entire business model around this powerful consumer insight.

    • Make your advice as personalized as possible. Knowing about what is best for “people like me” is a good start, but the consumer now has far higher expectations of what is possible with technology. They want a personalized self-assessment that is quickly followed up with far more “prescriptive” advice. This is still relatively new ground for the connected healthcare movement, as the marriage of personal sensors and powerful mobile apps is still in its infancy. I think we ain’t seen nothing yet when it comes to personalization. When we get there, I think we should expect better outcomes than we have now.

    • The presentation of the data matters. Many, if not most, quantified selfers revel in being able to demonstrate and share their data correlations, cause & effect discoveries and new and insightful hypotheses. They are anecdotally discovering some amazing things, but alas, this is not the average consumer. Over the last six years, I have attended many connected health conferences as well. Unfortunately, I rarely see presentations from behavioral psychologists or, as important, designers and artists who can move us with the power of their visuals. Some data charts and graphs simply have no chance to capture our fear or to engage our competitiveness. Some data, like trend analysis, is also just not best displayed on a small smartphone screen, which is yet another challenge with connected healthcare as we move faster toward mobile viewing versus watching our health wins and losses on the bigger screens at home.

    Motivating behavioral change through data visualization can still be very powerful, but it is more of an art than a science, and we will need far more artists, user interface experts and psychologists to help make our data work harder to motivate better health.

    Joe, thanks for the inspiration to share.

    Dave Dickinson
    Former CEO, Zeo, Inc.

  13. April 30, 2013 2:01 pm

    Perhaps quantitative feedback data on measures of health status are more meaningful and motivational for some of us than for others. And you are correct in observing that we are all unique personalities in this regard. This is where psychology and psychosocial interventions might compliment those involving feedback and timely intervention by a medically trained person. Working through our internal and situational sources of resistance to change is an iterative kind of adaptive development that is facilitated by patient and perceptive examination of the subjective themes at issue. Of course, this is inherently less efficient than our technically mediated support. But if you wish to get closer to 100% and amplify the gains you have gotten with your connected solutions, I believe it would be worth exploring. Out of that work recurring themes might emerge that could be addressed with greater efficiency.

  14. April 30, 2013 11:45 pm

    Reblogged this on lava kafle kathmandu nepal.

  15. May 1, 2013 3:09 am

    Really thoughtful comments above.

    We probably should look more to marketing disciplines to help manage customers here.

    One area is segmentation. So attitudes to authority, generally, can be quite different between the seniors who grew up in WW2, the boomers, and the younger generations. The boomers rebelled strongly against authority – music, fashion, corporatism, anti-draft, red brigades, etc. It is a massive generation gap. Today’s youngsters are much more conformist. So while taking the time to understand patients as individuals, we should think of some segment differences when tailoring responses.

    A second area would be the discipline of “Key Account Management”. Any company supplying complex products – and medicine is a complex product – has programs specifically geared to managing the complex of interactions between provider and customer. Data is an important part of the picture but much more effective when placed in the context of a managed relationship.

  16. Suneel Ratan permalink
    May 7, 2013 11:08 pm

    Joe: In any of your studies and research, what have you seen in terms of the characteristics (demographics, conditions, etc.) of the 30 to 40 percent who won’t engage relative to those who will? Not to be pessimistic, are there some people who just aren’t engageable?

    • May 8, 2013 8:43 am

      There may indeed be some people that are not engageable. Our belief, though, is that by fine tuning and refreshing the messaging, we can do lots better than a uni dimensional intervention.

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