You’d be forgiven if, after reading last month’s Health Affairs, you came to the conclusion that all manner of wellness programs simply will not work; in it, a spate of articles documented myriad failures to make patients healthier, save money, or both.
Which is a shame, because – let’s face it – we need wellness programs to work and, in theory, they should. So I’d rather we figure out how to make wellness work. It seems that a combination of behavioral economics, technology, and networking theory provide a framework for creating, implementing, and sustaining programs to do just that.
Let’s define what we’re talking about. “Wellness program” is an umbrella term for a wide variety of initiatives – from paying for smoking cessation, to smartphone apps to track how much you walk or how well you comply with your plan of care, and everything in between. The term is almost too broad to be useful, but let’s go with it for now.
When we say “Wellness programs don’t work,” the word work does a lot of, well, work. If a wellness program makes people healthier but doesn’t save lives, is it “working”? What if it saves money but doesn’t make people healthier?
The author in early 2010 and mid 2011
I’ve been thinking about how to write this story for a long time. Should it be a book? A blog? A self-help guide? Ever since I realized I’d lost 60 pounds over the course of a year and a half, I knew I wanted to find a way to talk about it, and maybe help others. This is my first public attempt.
A note about the rounding of my roundness: My peak weight, shortly after I began weighing myself in 2010, was 242 lbs. My lowest weight since I started weighing myself has been 183.2 lbs — right in line with where I should be, at 6’3″ tall. I’m sure that I weighed more than 242 lbs. at peak, but frankly, I don’t care that I don’t have the data to account for those last 1.2 lbs.
Adam Davidson’s New York Times Magazine story, “How Economics Can Help You Lose Weight,” helped organize my thinking about how to finally write this. In his story, Adam explains that the rigid protocol his doctor puts him through acts as a kind of economic incentive for him to stay on the diet. I’m highly skeptical that the special liquid meals he can only buy directly through his dietician will help him keep off the weight. I tried all sorts of diets in the many years that I was overweight and though I never tried the Adam’s solution, it doesn’t sound like a recipe for long term success. At least twice, I lost weight and then gained it all, and more, back. (Meta note: I feel terrible writing that. Adam, I wish you the best. Maybe something you read here will help you keep off the weight you have already lost, and congratulations on that difficult achievement.)
Now that I’ve managed to make weight loss sound simple, and sound smug about my success (I’ve stayed within the 183-192-pound range for more than two years now), what’s my big secret? It’s data. Just like I said in the headline, I keep a Google Doc spreadsheet in which I’ve religiously logged my weight every morning for the last three-plus years, starting on January 1, 2010, when I knew I had to do something about my borderline obesity.
In January we started asking ourselves, “How many people self-track?” It was an interesting question that stemmed from our discussion with Susannah Fox about the recent Pew report on Tracking for Health. Here’s a quick recap of the discussion so far.
The astute Brian Dolan of MobiHealthNews suggested that the Pew data on self-tracking for health seems to show constant – not growing – participation. According to Pew, in 2012 only 11% of adults track their health using mobile apps, up from 9% in 2011.
All this in the context of a massive increase in smartphone use. Pew data shows smartphone ownership rising 20% just in the last year, and this shows no signs of slowing down. Those smartphones are not just super-connected tweeting machines. They pack a variety of powerful sensors and technologies that can be used for self-tracking apps. We notice a lot of people using these, but our sample is skewed toward techies and scientists.
What is really going on in the bigger world? How many people are actually tracking?
A few weeks ago ABI, a market research firm, released a report on Wearable Computing Devices. According to the report there will be an estimated 485 million wearable computing devices shipped by 2018. Josh Flood, the analyst behind this report indicated that they estimated that 61% of all devices in wearable market are fitness or activity trackers. “Sports and fitness will continue to be the largest in shipments,” he mentioned “but we’ll start to see growth in other areas such as watches, cameras, and glasses.”
One just needs to venture into their local electronics retailer to see that self-tracking devices are becoming more widespread.
So why are our observations out of synch with the Pew numbers?
The latest news story to examine the issue of patient access to implantable cardiac defibrillator data (a variation on the theme of “gimme my damn data”) is an in-depth, Page One Wall Street Journal story featuring Society for Participatory Medicine members Amanda Hubbard and Hugo Campos. They have garnered attention in the past – one example is another piece on Hugo on the NPR Shots blog about six months back. The question posed by these individuals is simple — May I have access to the data collected and/or generated by the medical device implanted in my body? — but the responses to the question have been anything but. It is important to note that not every patient in Amanda’s or Hugo’s shoes would want the data in as detailed a format as they are seeking to obtain, and we should not impose the values of a data-hungry Quantified Self devotee on every similarly-situated patient. Different strokes for different folks.
The point is that if a patient wants access to this data he or she should be able to get it. What can a patient do with this data? For one thing: correlate activities with effects (one example given by Hugo is his correlation of having a drink of scotch with the onset of an arrhythmia — correlated through manual recordkeeping — which led him to give up scotch) and thereby have the ability to manage one’s condition more proactively.
We can get copies of our medical records from health care professionals and facilities within 30 days under HIPAA — and within a just a few days if our providers are meaningful users of certified electronic health records (it ought to be quicker than that … some day). In some states now, and in all states sometime soon (we hope), we can get copies of our lab results as soon as they are available to our clinicians.
Data, information, interpretation and decision-making are among the vital components of prevention, diagnosis, management and treatment.
The problem we have today is how to gather and manage the data that our bodies radiate.
In order to solve this problem, we have to surmount other problems – which are not just technological but also behavioral, cultural and financial.
But if you want an idea of what an extreme version of data-collection might look like, check out the application Placeme.
Now Placeme is *not* a Healthcare application. What Placeme does do, however, is to continually (in almost real-time) track the places that you visit. No check-ins; no need to enter and data – the application simply runs in the background and does its magic.
When you think about that (from the cultural perspective of today), that’s creepy.
And yet, this “creepy” model is the future. It represents the technological and cultural arc that social software is throwing us. We can fight it (and should in order to flesh out the nuances so we can ensure safety) but in the long-run we shall have to accept the trend and work accordingly.
So think of Placeme in terms of what the ‘Quantitative Self’ movement is attempting to achieve.
“If you cannot measure it, you cannot improve it.” Lord Kelvin
“Asking science to explain life and vital matters is equivalent to asking a grammarian to explain poetry.” Nassim Nicholas Taleb
Of course the quantified self movement with its self-tracking, body hacking, and data-driven life started in San Francisco when Gary Wolf started the “Quantified Self” blog in 2007. By 2012, there were regular meetings in 50 cities and a European and American conference. Most of us do not keep track of our moods, our blood pressure, how many drinks we have, or our sleep patterns every day. Most of us probably prefer the Taleb to the Lord Kelvin quotation when it comes to living our daily lives. And yet there are an increasing number of early adopters who are dedicated members of the quantified self movement.
“They are an eclectic mix of early adopters, fitness freaks, technology evangelists, personal-development junkies, hackers, and patients suffering from a wide variety of health problems. What they share is a belief that gathering and analysing data about their everyday activities can help them improve their lives.”
According to Wolf four technologic advances made the quantified self movement possible:
“First, electronic sensors got smaller and better. Second, people started carrying powerful computing devices, typically disguised as mobile phones. Third, social media made it seem normal to share everything. And fourth, we began to get an inkling of the rise of a global superintelligence known as the cloud.”
Hospital leaders are busy trying to cope with the changes brought on by the Patient Protection and Affordable Care Act and the realization that the federal budget deficit translates into less money for all healthcare providers in the future. The seemingly inevitable transition from fee-for-service to global payments creates anxiety about how quickly the financial incentives will shift.
While the above-described issues are certainly enough to monopolize any busy hospital executive’s time, there are other large-scale changes on the horizon that may impact hospital operations just as much. Leaders who ignore these trends will do so at their organization’s peril.
The important trends include: personalized medicine that concentrates on the individual not the population; the “quantified self” movement with constant remote physiologic monitoring; the smartphone health applications explosion, and the artificial intelligence, healthcare robot movement.
Personalized medicine: Advances in genomics and digital technology are making it possible to shift the focus of evidence-based medicine from the population to the individual patient. Today drug treatment and disease screening follow a one-size-fits-all approach that leads to overtreatment and unnecessary expense. Genetic testing allows us to individualize the treatment for the patients.
For example, about 20 percent of diabetic patients treated with metformin do not respond to the drug, a condition that can be identified by genotyping that is not routinely done today. Likewise, cancer screening by mammography after age 40 in women and colonoscopy after age 50 in men and women does not take into account the different genetic predispositions for breast cancer and colon cancer in individual patients. Two new books should be on every hospital executive’s reading list because they explore the implications for hospitals of personalized medicine: Eric Topol’s “The Creative Destruction of Medicine” and David Agus’ “The End of Illness.”
When we design today, we isolate problems and then create solutions for them, and we then celebrate those solutions. But in reality we have no idea exactly what we’ve done, because in focusing on any particular problem we have really just ignored everything else. We have failed to engage with the complex realities of our interconnected world, and in our attempts at solutions have only created more problems, the cumulative effect of which can be devastating.
When we really understanding the implications of this idea, we soon realize that in our design of anything, we must consider everything. There is no part of the entire system that isn’t affected by every other part of the entire system. This idea became very clear to me while working in healthcare. You can’t solve for a particular condition in isolation… it interacts in complex ways with the system of rest of the body. When you consider the entire body, and you soon realize that you can’t solve for the health of the individual in isolation… it interacts in complex ways with the social systems, culture, the environment, and on and on. Changes to any part of that system can have dramatic, complex, unforeseen, unintended, and often unknown consequences in other parts of the system.
Bryan Castañeda, who lives in Southern California, told me this:
The law firm I work at specializes in toxic torts. We represent people who have been occupationally exposed to chemicals and are now sick, dying, or dead. Most of our clients have been exposed to benzene and developed some kind of leukemia. We sponsor various leukemia charities, walks, and other events. [On January 21, 2012] in Woodland Hills, CA, the Leukemia & Lymphoma Society held its first annual Blood Cancer Conference. Although the speakers were mainly doctors, it was a conference meant for laymen. The chair was an oncologist from UCLA Medical Center.
After introductory remarks and the keynote speaker, there were several breakout sessions. I attended a session on acute lymphoblastic leukemia and acute myeloid leukemia. The speaker was [Dr. Ravi Bhatia,] a doctor specializing in leukemia from City of Hope in Duarte, CA. His talk was almost exclusively about new drugs and clinical trials. Very dry and dull. Things got more interesting during the question period. At one point, [Dr. Bhatia] told an attendee not to experiment on his own because “you won’t learn anything and others won’t learn from it, either.”
I would have liked to ask Dr. Bhatia three questions:
1. What’s the basis for this extreme claim (“you won’t learn anything and others won’t learn from it”)? Ben Williams, a psychology professor at UC San Diego, wrote a whole book (Surviving “Terminal” Cancer, 2002) about taking an active approach when faced with a very serious disease (in his case, brain cancer). Likewise, the website Patients Like Me is devoted to (among other things) learning from the experimentation of its members. Lots of forums related to various illnesses spread what one person learns to others. MedHelp has many forums devoted to sharing knowledge.
Programmable self is a riff on the Quantified Self (QS). It is a simple concept:
Quantify what you want to change about yourself + motivational hacks = personal change success.
There are several potential “motivation hacks” that people regularly employ. The simplest of these is peer pressure. You could tell all of your co-workers every morning whether you kept your diet last night, for instance. Lots of research has shown that sort of thing is an effective motivator for change. Of course, you can make peer pressure digital by doing the same thing on Facebook/Twitter/Google+/whatever. Peer pressure has two components: shame and praise. It’s motivating to avoid shame and to get praise. Do it because of a tweet and viola, you have digital peer pressure motivation.
Several books have recently popularized using money, in one form or another, as a motivational tool. There is some evidence, for instance, that people feel worse about losing $10 than they feel good about earning $10. This is called loss aversion, and it can easily be turned into a motivational hack. Having trouble finishing that book? Give 10 envelopes with $100 each to your best friend. Instruct them to mail the envelopes to your favorite (or most hated) charity for each month that you do not finish a chapter. Essentially, you’ve made your friend a “referee” of your motivational hack.