Category Archives: research methodology

data saving lives, healthy habits, nutrition, quantified self, rapid learning health systems, research methodology, technology

SMS provides for an effective weight loss intervention

 

Source: http://www.fiercemobilehealthcare.com/story/study-texting-effective-intervention-tool-weight-control/2013-11-21?utm_medium=nl&utm_source=internal

Citation: http://www.jmir.org/2013/11/e244/

Study: Texting effective intervention tool for weight control

November 21, 2013 | By 

Daily text messaging may be a useful self-monitoring tool for weight control, particularly among racial/ethnic minority populations most in need of intervention, according to Duke University study results published in a Journal of Medical Internet Research article.

“Recent studies show that racial/ethnic minorities are more likely than white individuals to own mobile phones,” states the article. “The high familiarity with and penetration of mobile technologies makes text messaging an ideal intervention platform among these populations.”

The purpose of the randomized controlled pilot study was to evaluate the feasibility of a text messaging intervention for weight loss among predominantly black women, who “have alarmingly high rates of obesity as compared with other gender and racial/ethnic groups.” The secondary aim of the study was to evaluate the effects of the intervention on weight change relative to an education control arm.

Fifty obese women aged 25-50 years were randomized to either a six-month intervention using a fully automated system that included daily text messages for self-monitoring tailored behavioral goals (e.g., 10,000 steps per day, no sugary drinks) along with brief feedback and tips (26 women) or to an education control arm (24 women). The article states that weight was objectively measured at baseline and at six months, while adherence was defined as the proportion of text messages received in response to self-monitoring prompts.

At six months, the article reports that the intervention arm lost a mean of 1.27 kg, and the control arm gained a mean of 1.14 kg. The average daily text messaging adherence rate was 49 percent with 85 percent texting self-monitored behavioral goals two or more days per week. Moreover, about 70 percent strongly agreed that daily texting was easy and helpful and 76 percent felt the frequency of texting was appropriate.

“Given that the majority of evidence indicates that greater adherence leads to better outcomes, our study suggests that mHealth-based approaches to self-monitoring may enhance engagement and reduce the burdens commonly associated with other modes,” concluded the article. “Our intervention was relatively low intensity and has greater potential for dissemination compared to higher intensity interventions. As technology penetration increases in the target population, the use of this modality will become increasingly relevant and helpful as an intervention tool for weight control.”

Earlier this year, an article published in the Journal of American Medical Informatics Association revealed that mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in a weight loss program are more effective than traditional methods. The study involved a post hoc analysis of a six-month randomized weight loss trial among 96 overweight men and women, which found that physical activity app users self-monitored exercise more frequently over the six-month study and reported greater intentional physical activity than non-app users.

To learn more:
– read the article in JMIR

facts & data points, healthy habits, nutrition, policy, research methodology

A behavioural economist’s view on obesity…

This is a typically obtuse, academic view of obesity, breathlessly attempting to cite the immense complexity of the disease, capping it with a plea for more research dollars, or at least a reallocation of research dollars.

There are a couple of interesting snippets:

  • pets are also getting obese – 58.3% of cats were obese in 2012
  • lab animals too are getting obese – 11.8% per decade from 1982 to 2003
  • is this due to antibiotic-mediated changes to gut bacteria that not just change how we digest, but also how we behave?
  • socially mediated effects?

So surprising that a behavioral economist’s view could be so dismal.

 

Source: http://www.nytimes.com/2013/11/10/business/the-co-villains-behind-obesitys-rise.html?_r=2&

The Co-Villains Behind Obesity’s Rise

Waltraud Grubitzsch/European Pressphoto Agency

Researchers have compared tissue samples from obese mice with those of normal mice to try to determine which behavioral or biological factors might cause humans to gain weight. Here, a 2012 experiment in Leipzig, Germany.

By SENDHIL MULLAINATHAN
Published: November 9, 2013

Why is obesity soaring? The answer seems pretty clear. In 1955, a standard soda at McDonald’s was only seven ounces. Today, a medium is three times as large, and even a child’s-size version is 12 ounces. It’s a widely held view that obesity is a consequence of our behaviors, and that behavioral economics thus plays a central role in understanding it — with markets, preferences and choices taking center stage. As a behavioral economist, I subscribed to that view — until recently, when I began to question my thinking.

For many health problems, of course, behavior plays some role but biology is often a major villain. “Biology” here is my catchall term for the myriad bodily mechanics that are only weakly connected to our choices. A few studies have led me to wonder whether the same is true with obesity. Have I been the proverbial owner of a (behavioral) hammer, looking for (behavioral) nails everywhere? Have I failed to appreciate the role of biology?

A first warning sign comes from looking at other animals. Our pets have been getting fatter along with us. In 2012, some 58.3 percent of cats were, literally, fat cats. That is taken from a survey by the Association for Pet Obesity Prevention. (The very existence of this organization is telling.) Pet obesity, however, can easily be tied to human behavior: a culture that eats more probably feeds its animals more, too.

And yet, a study by a group of biostatisticians in the Proceedings of the Royal Society challenges this interpretation. They collected data from animals raised in captivity: macaques, marmosets, chimpanzees, vervets, lab rats and mice. The data came from labs and centers and spanned several decades. These captive animals are also becoming fatter: weight gain for female lab mice, for example, came out to 11.8 percent a decade from 1982 to 2003.

But this weight gain is harder to explain. Captive animals are fed carefully controlled diets, which the researchers argue have not changed for decades. Animal obesity cannot be explained through eating behavior alone. We must look to some other — biological — driver.

Fittingly, the study is titled “Canaries in the Coal Mine.” Could our inability to explain animal obesity with behavior be a warning sign? Perhaps we are also overlooking biological drivers for human obesity. But what might these culprits be?

A particularly interesting candidate resides in your gut. Your digestive system is actually a complex ecosystem, playing host to hundreds of species of bacteria that do things as diverse as fermenting undigestedcarbohydrates and providing vitamins. They also regulate how much fat your body stores.

Not everyone, however, has the same gut bacteria. And, interestingly, the composition of this bacteria correlates with obesity. Of course, this relationship could be simple: the obese eat differently, and therefore they have different bacteria.

But a recent study in the journal Science showed that cause and effect could go the other way as well. Researchers harvested bacteria from pairs of human twins, where one twin was obese and the other was not. Then they transplanted these bacteria into mice. The mice who received bacteria from the obese twin gained weight, while the others did not. The mice did not eat more: Their metabolism changed so that they put on more weight even with the same caloric input.

What, then, determines your gut bacteria? It could be antibiotics or environmental toxins or how processed your food is. Another possibility is raised by a study in The New England Journal of Medicine that shows that obesity seems to “spread” across social networks, with people infecting their friends and neighbors. I had always assumed that was because birds of a feather flock together — and that is surely part of the explanation. But because gut bacteria can also spread among people in close proximity, perhaps the obesity epidemic really is, well, an epidemic?

I’m not arguing that behavior does not matter. Biology and behavior often interact; the spread of flu depends on whether we wash our hands. Similarly, the bacteria study found that the “obese gut bacteria” had an impact only when the mice were fed diets heavy in saturated fats.

Perhaps most interestingly, changing biology may even be changing cravings. Some biologists have hypothesized that our gut bacteria actually drive cravings for certain unhealthy foods. A focus on biology doesn’t mean a reduced emphasis on behavior, just a richer understanding of it.

These and other studies raise important possibilities, which deserve more research and attention. At the very least, we should invest as many obesity research dollars in uncovering and understanding these biological channels as we do in understanding behavioral channels. And this is a behavioral economist talking!

After all, this could radically change the way we think about policies to curb obesity. As one newspaper editorial pronounced:

“A little town in Sweden has put a local tax on fat men. It is declared that ‘the fat man stands accused by the very fact of his too solid flesh’ (vide “Hamlet”) ‘of gluttony and laziness.’ Millions of fat men throughout the world may rise up and denounce as liars the town councillor who drew up this cruel indictment and those who voted for it, but the gentler way of reproving them would be to point out the tritely recognised danger of generalisation in almost any statement of supposed fact. Not all fat men are lazy and gluttonous. Obesity is in many a congenital habit of body; in others a disease.”

That editorial was written in 1923, for the paper known as The Paris Herald. Maybe the writer was on to something.

SENDHIL MULLAINATHAN is a professor of economics at Harvard.

This article has been revised to reflect the following correction:

Correction: November 17, 2013

Because of an editing error, the Economic View column last Sunday, about possible causes of obesity, misstated the source of bacteria that were transplanted into mice as part of an obesity study. The bacteria came from human twins, not from other mice.

 

A version of this article appears in print on November 10, 2013, on page BU6 of the New York edition with the headline: The Co-Villains Behind Obesity’s Rise.
cool, data saving lives, entrepreneurship, healthcare, healthy habits, meaning, nutrition, policy, politics, quantified self, rapid learning health systems, research methodology, storytelling

Chronic Disease Fear Factor Ageing Messaging

Governments won’t be able to afford you if you are over 70 and can’t work
You will need to be productive
The current health market can only extend your life, but not your productive life
The new health system will have to do both if we are to preserve our standard of living
Sure, people will need to die sometime, but it’s the when, how and why they die that needs to evolve
This health system aims to deliver on this
Australia is well positioned to lead the world on this
Excitement

data saving lives, entrepreneurship, healthcare, healthy habits, nutrition, policy, politics, rapid learning health systems, research methodology, technology

Katz slam dunks….

  • Used the Harvard Nurses Health Study to develop an algorithm for food healthiness as determined by health outcomes from the study – a GPS for nutrition – CLEVER!
  • Offered to do this with Government in the early 2000s but was knocked back
  • Developed a proprietary algorithm called ONQI, owned by NuVal
  • Choosing higher scoring foods correlates with a lower risk of dying prematurely.
  • “The very government agencies that regulate the food supply are extensively entangled with the entities producing our food, from farm to factory. In comparison, we mere eaters of food have very little clout. The government may be just a little too conflicted on the topic of food to be in the business of putting the truth, the whole truth and nothing but the truth on at-a-glance display.
    Certainly the big food manufacturers, the makers of glow-in-the-dark snackattackables, should NOT be in the business of nutrition guidance whatever their inclination. That approach makes the fox look like a highly qualified security officer for the henhouse.
    Which leaves independent nutrition, and public health experts and private sector innovation. And here we are.
    Private-sector innovation often involves intellectual property, trade secrets and patent applications. It involves some entity making an investment and wanting a return. That is all true of NuVal, for better or worse. It wasn’t my plan – it was just the only way to get this empowering system into the hands of shoppers. Of note, the ONQI remains under the independent control of scientists, and not the business.”
  • This is a terrific strategy – worthy of emulation.

Source: http://health.usnews.com/health-news/blogs/eat-run/2013/06/11/nutrition-guidance-who-needs-to-know-what

Nutrition Guidance: Who Needs to Know What?

  June 11, 2013 

I am writing today about nutrition guidance and who needs to know what to make it useful.

Permit me to disclose right away that I am the principal inventor of the Overall Nutritional Quality Index (ONQI) algorithm, used in NuVal – a nutritional guidance system that stratifies foods from 1 to 100 on the basis of overall nutritional quality: the higher the number, the more nutritious the food. As the Chief Science Officer for NuVal, LLC, I am compensated for my continuous and considerable allocations of time and effort. But it was never supposed to be that way – and the reasons why it is are an important part of this story.

As to why this column now, there are two recent provocations. One is our ongoing work to complete the updated algorithm, ONQI 2.0, and the window that provides into a world of weirder foods than I ever even considered possible. The other is a paper published in the Journal of the Academy of Nutrition and Dietetics a few months back and a more recent exchange of letters related to that article. The article described the advantageous novelties of a nutritional profiling system, such as weighting nutrients for their health effects rather than counting them all the same. But this was less about novelty, and more about NuVal, since the innovations described have long been included in the ONQI.

[See: Debunking Common Nutrition Myths.]

Claims about alleged novelties that were already included in NuVal prompted a letter from my colleagues and me to the journal, which was published along with a response from the original authors. In that response, they acknowledged that the NuVal system included the so-called “novelties” and acknowledged that the ONQI is, to date, the only nutritional profiling system shown to correlate directly with health outcomes. So the real concern, the letter went on, is that the ONQI algorithm is proprietary and the details are not fully in the public domain.

Which brings us back to why NuVal is a private and proprietary system in the first place and whether or not it matters that certain details of the algorithm – which populate 25 pages or so of computer code written in a language called SAS – are not on a billboard. Why isn’t the ONQI public rather than private, and who really needs to know every detail of the algorithm for it to be useful? (All of the nutrients included in it, and the basic approaches used to generate scores, have been published.)

The ONQI, and NuVal, are a private sector innovation because the public sector said: no thanks. In 2003, I was privileged to be a member of a group of 15 academics invited to Washington, D.C. by then-Secretary of Health Tommy Thompson. A Food and Drug Administration task force had been formed to guide efforts related to the control of rampant obesity and diabetes, and we were a part of that effort. We gathered in a conference room with Secretary Thompson, the FDA Commissioner (Mark McClellan) and others, including the surgeon general and the heads of the National Institutes of Health and the Centers for Disease Control and Prevention.

[See: Why Aren’t Americans Healthier?]

We were each given one three-minute turn to offer up one good idea the FDA and other federal agencies might use to help combat the ominoustrends in diabetes and obesity. I used my turn to describe, in essence, the project that later became the ONQI. I suggested that the secretary might convene a totally independent group of top-notch experts in nutrition and public health, perhaps under the auspices of the Institute of Medicine.

The group should have no political or industry entanglements and should be allowed to work for as long as it took to convert the best available nutrition science and knowledge into a guidance system anyone could understand at a glance. I was thinking, in essence, of the equivalent of GPS for nutrition, so that no one trying to identify a better food in any given category would get lost, confused or misled by Madison Avenue.

[See: 10 Things the Food Industry Doesn’t Want You to Know.]

I waited two years for the feds to do something along these lines. When they didn’t, I decided to undertake the project myself, with the backing of Griffin Hospital in Derby, Conn. – a Yale-affiliated, not-for-profit community hospital, which owns the ONQI algorithm to this day. Other than this being a private rather than federal endeavor, all other aspects of the project were just as proposed to the U.S. Secretary of Health. When we completed the algorithm, I offered it again to the FDA. A scientist at the agency recommended a private-sector approach if I hoped to live long enough to see the system do its intended good.

Why didn’t the feds take on the project? We can all conjecture. I suspect it has something to do with the story Marion Nestle told us all in Food Politics, and the stories we routinely hear about the Farm Bill from the likes of Michael Pollan, Mark Bittman and others. The very government agencies that regulate the food supply are extensively entangled with the entities producing our food, from farm to factory. In comparison, we mere eaters of food have very little clout. The government may be just a little too conflicted on the topic of food to be in the business of putting the truth, the whole truth and nothing but the truth on at-a-glance display.

[See: Seeking a More Perfect Food Supply.]

Certainly the big food manufacturers, the makers of glow-in-the-dark snackattackables, should NOT be in the business of nutrition guidance whatever their inclination. That approach makes the fox look like a highly qualified security officer for the henhouse.

Which leaves independent nutrition, and public health experts and private sector innovation. And here we are.

Private-sector innovation often involves intellectual property, trade secrets and patent applications. It involves some entity making an investment and wanting a return. That is all true of NuVal, for better or worse. It wasn’t my plan – it was just the only way to get this empowering system into the hands of shoppers. Of note, the ONQI remains under the independent control of scientists, and not the business.

[See: Mastering the Art of Food Shopping.]

Which leads us back to the second question: Is it a problem for a system like this to be a private-sector innovation? Who, really, needs to know every detail of such an algorithm?

Consider that if you are shopping for a car, you do need to know if it comes with anti-lock brakes or all-wheel drive. But to decide if these are working for you, you don’t need engineering blueprints; you just need to drive in the snow. When shopping for a smartphone, you may want to know if it has GPS. But you don’t need the trigonometry equations on which the GPS is based to determine if it works; you just have to see if it helps you get where you want to go.

Nutrition guidance in general, and NuVal in particular, are just the same. What are the exact formula details? Who cares. We routinely rely on tools based on math and engineering most of us don’t understand – but we don’t need all that input to know if the tools are working for us. We just need the output. We need to be able to use them. People using NuVal have lost more than 100 pounds, and even over 200 pounds. Choosing higher scoring foods correlates with a lower risk of dying prematurely. More than 100,000 scores are on public display in 1,700 supermarkets nationwide. The ONQI is at least as transparent as any car or smartphone or computer.

[See: The No. 1 Skill for Weight Management.]

Let’s acknowledge: If you are reading this on a computer screen, neither of us truly understands the engineering involved in me writing it, using word processing software, attaching it to an email and sending it to my editor at U.S. News & World Report so she could post it in cyberspace, where you found it. But we do know it worked.

We rely on private-sector innovation for a lot of important jobs, and even many that put our safety on the line. The private sector makes our cars and planes. We seem to be comfortable using these without scrutinizing patent applications. The private sector makes our computers, and smartphones and GPS systems, and we can tell whether or not these work, even if we don’t know how.

Why, then, is nutrition guidance different? The answer, I believe, is politics, profits and the inertia of the status quo. We are accustomed to vague nutrition guidance from conflicted sources, and those same sources are apt to imply there is something wrong with private-sector innovation and the intellectual property issues that come along with it. But if those issues don’t undermine the cars, and planes and navigation systems that get us from city to city and coast to coast, it’s not at all clear why they should be a problem when navigating among choices in a supermarket aisle.

[See: The Government’s MyPlate Celebrates Second Birthday.]

As a scientist, and not a businessperson, my preference would be to put the ONQI on a billboard for all the good it would do. But on this, I must defer to the businesspeople who have made the relevant investments and are entitled to safeguard potential returns. As for the scrutiny that all advanced systems should get, the ONQI has been shared with scientists at leading universities and health agencies around the world – but for private assessment and use rather than public display. Others like them who want to review the program need only ask.

We should all care that the military-industrial establishment seems opposed to putting the blunt truth about nutritional quality, as best we know it, on at-a-glance display. We should care that federal authorities responsible for nutrition guidance are also responsible, if only indirectly, for food politics and supply-side profits. That story may lack novelty. It may be old news. But it is nonetheless something everyone who eats does need to know – engineering blueprints not required.

healthcare, nutrition, policy, rapid learning health systems, research methodology

Forbes: Curing Type 2 Diabetes with Surgery: It Works — Now Let’s Figure Out Why

  • Insulin resistance stabilises ahead of weight loss in gastric bypass surgery
  • Insulin resistance tracks with weight loss in lap band surgery
  • No one knows why, though some pharma start ups are looking for a molecule
  • A great example of empiricism triumphing over reductionism

PN: This still leaves the door open to the solid food hypothesis

http://www.forbes.com/sites/davidshaywitz/2012/03/26/curing-diabetes-with-surgery-it-works-now-lets-figure-out-why/

3/26/2012 @ 11:59PM |29,806 views

Curing Type 2 Diabetes with Surgery: It Works — Now Let’s Figure Out Why

During my endocrinology training, I was captivated by a phenomenon I’d seen on the wards, and had just started to read about in the literature: type 2 diabetic patients receiving bariatric surgery exhibiting rapid, seemingly instantaneous improvements in their glycemic control, apparently related to profoundly reduced insulin resistance as a consequence of the surgery.

The first teaching seminar I gave as a fellow, at Endocrinology Grand Rounds, asked the distinguished medical faculty who gathered in the Ether Dome, “Is Diabetes a Surgical Disease?”

At the time, the answer was, “Yes?”  Now, two recent reports presented today at the ACC, and simultaneously published in the NEJM (here and here), seem to upgrade this answer to “Yes!”

Both reports conclude that bariatric surgery surpasses medical therapy as a treatment for type 2 diabetes, and are fascinating not only because of the immediate clinical implications (as discussed by Matt Herper here, and in anNEJM editorial comment here), but also because there’s some really cool underlying science that nobody seems to understand.

The fundamental paradox is the same mysterious clinical phenomenon that so intrigued me years ago: the drastic improvement in diabetic function that occurs significantly before most of the weight is lost.

The authors of the first study note, “Reductions in the use of diabetes medications occurred before achievement of maximal weight loss, which supports the concept that the mechanisms of improvement in diabetes involve physiologic effects in addition to weight loss, probably related to alterations in gut hormones.”

The authors of the second study were also struck by the rapid improvement in glycemic control they observed, reporting that all patients treated surgically were able to discontinue all their diabetes medicines within fifteen days of their operation – a remarkable result (and entirely consistent with my own clinical experience).  Almost all of the surgically-treated patients remained free of diabetes after two years, while none of the medically-treated patients were as fortunate.

As the authors write, “there was no correlation between normalization of fasting glucose levels and weight loss after gastric bypass and biliopancreatic diversion, findings that are consistent with results of previous studies, which suggests that such surgeries may exert effects on diabetes that are independent of weight.”

The authors also point out this result is in contrast with gastric banding procedures (which constrict the stomach but don’t otherwise alter the anatomy); the improvement in diabetes seen in those patients does appear to correlate more directly with weight loss.

The intriguing scientific question is how can bariatric surgery result in an almost immediate improvement in the insulin resistance profile of diabetic patients?  To my mind, this is among the most important unanswered questions in endocrinology, and medical science more generally.  While the effect is generally attributed to “gut hormones” (as the authors of the first study write), the biology beyond that gets a bit murky.

To be sure, some companies are working on it – the example that springs first to mind is NGM Biopharmaceuticals, a small Bay-area biotech (with which I have no personal nor professional connection) founded in 2008 as an ambitious science play by The Column Group, Rho Ventures, and Prospect Venture Partners.  I’m sure others are working on this challenge as well.

A final point – as attracted as we are to the view of basic science driving clinical medicine, the experience with gastric bypass surgery arguably exemplifies the reverse, and represents a triumph of empiricism, as well as a reminder of the value of human physiology (see here), and more generally, the importance of studying people (and not just parts of people).

It also would not be the first (nor will it be the last) time that medical sophisticates learned a valuable lessons from those laboring – often, as in the case of many bariatric surgeons, with inadequate respect – on the front lines of patient care.

This article is available online at: 
healthcare, healthy habits, quantified self, rapid learning health systems, research methodology

mHealth mediated exercise prescriptions work

  • mobile technologies improve outcome measures associated with exercise interventions when compared to those interventions alone
  • not definitive, but certainly encouraging

Source: http://www.fiercemobilehealthcare.com/story/mhealth-improves-risk-profile-cardiovascular-disease-type-2-diabetes-patien/2013-11-08

Abstract: http://www.biomedcentral.com/1471-2458/13/1051/abstract

Provisional paper (PDF): Lifestyle interventions

mHealth improves risk profile in cardiovascular disease, type 2 diabetes patients

November 8, 2013 | By 

A provisional article published in the peer-reviewed journal BMC Public Health suggests that mHealth technology supporting exercise prescription interventions can be effective.

The findings are based on a Canadian study of 149 adults with at least two metabolic syndrome risk factors, one group using the intervention and one control group.

“Mobile health technologies have proved to be a beneficial tool to achieve blood pressure and blood glucose control in patients with diabetes,” argue the authors, who are currently completing their analyses‎ and will be submitting their data for publication in the next few weeks. “These technologies may address the limited access to health interventions in rural and remote regions. However, the potential as a tool to support exercise-based prevention activities is not well understood.”

The study was undertaken to “investigate the effects of a tailored exercise prescription alone or supported by mobile health technologies to improve metabolic syndrome and related cardiometabolic risk factors in rural community-dwelling adults at risk for cardiovascular disease and type 2 diabetes,” states the article. The authors hypothesized that the primary outcome, systolic blood pressure, and secondary outcomes would be improved in both groups, but to a greater extent in the mobile health intervention group at 12 weeks and that these changes would be better maintained at 24 and 52 weeks in the intervention group with mobile health support, compared with the active control group.

The results of the study “will contribute to the current literature by investigating the utility of mobile health technology support for exercise prescription interventions to improve cardiometabolic risk status and maintain improvements over time, particularly in rural communities,” concludes the provisional article, which serves as a protocol paper.

Study participants were recruited from rural communities in Ontario, Canada. Participants were randomized to either: an intervention group receiving an exercise prescription and devices for monitoring of risk factors with a smartphone data portal equipped with a mobile health application; or an active control group receiving only an exercise prescription.

In addition to the exercise prescription, the intervention group received a mobile health technology kit for self-monitoring of biometrics and physical activity. The kit included a smartphone (Blackberry Curve 8300 or 8530) equipped with Healthanywhere health monitoring app (Biosign Technologies), a Bluetooth-enabled blood pressure monitor (A & D Medical), a glucometer (Lifescan One Touch Ultra2) with Bluetooth adapter (Polymap Wireless) and a pedometer (Omron).

Nevertheless, a recent study in the Journal of Medical Internet Research found that although mobile health interventions are effective in promoting physical activity, their degree of validity reported in studies is unclear.

Using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework, the review revealed a recent increase in studies conducted to determine the effectiveness of mHealth interventions for the promotion of physical activity. Yet, quantity, not quality, seems to prevail, the authors argued.

To learn more:
– read the article in BMC Public Health

data saving lives, entrepreneurship, healthcare, healthy habits, quantified self, rapid learning health systems, research methodology

sharing drives behaviour change

http://medcitynews.com/2013/10/calico-communities-legislation-tech-drive-new-era-health/

  • peer support is a powerful model to support behaviour change
  • social media-backed sharing of progress reinforces achievements
  • Stevens is the CEO of KEAS > workplace health interventions

Calico, communities, legislation and tech drive a new era of health

October 14, 2013 12:45 pm by  | 0 Comments

America’s healthcare system has historically taken only baby steps to empower individual health and wellness ownership – until now. Recent events are about to alter existing healthcare paradigms and I believe this to be the most pivotal of moments. With Google’s Calico, the Affordable Care Act (ACA), Penn State’s wellness debacle and the rise of health-oriented social, healthcare entities are now taking a microscope to existing practices and infrastructures. What will they find? An industry destined for a radical makeover that will result in a prevention-based and consumer-driven healthcare network.

 Let’s take a look at the players involved, from the good (social networking and technology), the bad (Penn State’s wellness initiative) and the TBD (Calico and the ACA).

The Emerging Models
Legislation, technology, communities, and social networking are forcing a healthcare overhaul. Consider Google’s Calico: It has the opportunity to create the largest online community to share health information, turning personal health on its head. With a greater global consumer reach than any other organization, Google has the access and resources to throw at this opportunity, making it the ideal company to coordinate this effort – and being led by Art Levinson, the Bill Gates of biotech, doesn’t hurt.

Addressing the issue of aging in a share- and prevention-oriented effort is a response to the growing presence of the “empowered patient.” Calico could finally deliver on the promise for people to have the ability to seize proactive command over their health with a full understanding of their health data and risk factors. Previously constrained by outdated regulations and a healthcare system that doesn’t prioritize prevention, the tables are finally turning. The potential can live up to the hype.

The October 1 launch of ACA-mandated healthcare exchanges is another step toward preventative care and information sharing. While the ACA is polarizing on both sides, (the outcome of its execution remains yet to be seen) the core of the ACA will impact the resulting healthcare industry in a way that empowers individuals to own their well-being and fosters collaboration with all patient caregivers.

The Anti-Model 
Pennsylvania State University recently (and wisely) repealed a recent decision that established apunitive-based health and wellness program. Love or hate it, even the ACA agrees with the ‘carrot’ versus the ‘stick’ (companies can offer a reward of up to 30 percent of health costs for employees who participate in programs like risk assessment). Given the backlash and media attention Penn state received, it was an unfortunate way to learn what not to do.

Additionally, HIPAA is about to be a relic. Designed in a bygone era, HIPAA will be rendered obsolete thanks to the ACA. Because the ACA will provide benefits to those with pre-existing conditions, HIPAA’s privacy laws will only exist as roadblocks to individual health and wellness. The future of healthcare is driven by information sharing. It’s time for HIPAA to die

The Proven Models
Peer support in healthcare is proving to be wildly successful. As consumers, we increasingly seek the wisdom of crowds to create and sustain meaningful behavior change. El Camino Hospital in Mountain View, CA, recently launched a healthcare program for its employees in which social networking was a one of the tent poles in the program. During an 8-week time frame, over 1,000 participants lost over 1,000 pounds and began eating more fruits and vegetables. What was the number one motivating factor? Sharing progress updates with colleagues.

Today, 80 percent of healthcare costs are associated with preventable illnesses such as obesity, diabetes, hypertension and high cholesterol. It’s no wonder people are demanding to take back ownership of their health. Social networking, communities, technology and legislation are propelling old school healthcare into a consumer-driven and preventative-based model. I say bring it on — it’s about time.

complex adaptive systems, healthcare, healthy habits, nutrition, policy, rapid learning health systems, research methodology

NYT: The Challenge of Diabetes for Doctor and Patient

..or why managing diabetes doesn’t fit with how doctors have been taught, and therefore generally like, to treat patients >>> we need a radically new approach not involving doctors, busy doing other things – see Iora Health post re. health coaches.

The good news: lifestyle change for the obese or those with prediabetes may have lower progression to diabetes
http://archinte.jamanetwork.com/article.aspx?articleid=1485081

The average news: childhood obesity is plateauing [PN: ??from a scandalously high base]
http://www.nytimes.com/2012/12/11/health/childhood-obesity-drops-in-new-york-and-philadelphia.html?_r=0

The bad news: Intensive lifestyle change for diabetics did not reduce the risk of stroke or heart attack, even though these patients were able to lose weight, improve their overall quality of life, take fewer medications and even decrease costs.

Lifestyle changes — diet and exercise — require huge and ongoing investment efforts for patients; we’d like to think it pays off for the big-ticket clinical outcomes. Hopefully future studies will show benefits.

 

OCTOBER 17, 2013, 3:43 PM

The Challenge of Diabetes for Doctor and Patient

By DANIELLE OFRI, M.D.

My patient was miserable — parched with thirst, exhausted and jumping up to go to the bathroom every few minutes. His vision was blurry and he’d been losing weight the last few weeks, despite eating voraciously. I’d only just met him, but I was able to diagnose diabetes in about a minute. What was unusual was that this was a scheduled office visit; usually, patients with such overwhelming symptoms are the provenance of emergency departments and urgent care centers.

A quick shot of insulin and five glasses of water and my patient felt like a new man, with no need to go to the E.R. But now, of course, the hard work would begin. A new diagnosis of diabetes is an enormous undertaking — lots to explain, major life changes to contemplate, myths to dispel, consultations with a nutritionist and a diabetes nurse.

Two days later I had another new patient for a scheduled visit — thirsty, tired, losing weight, eating and drinking like mad, eyes so blurred he could hardly see. We’d barely gotten past the introductions before I’d made another new diagnosis of diabetes. Another shot of insulin, another five glasses of water, and then the plunge into the thicket of diabetes education.

Most of my regular office visits with diabetic patients — even newly diagnosed patients — don’t involve such dramatic presentations. More often the disease is found when we screen patients who have risk factors like obesity or a family history of the disease, or who have commonly co-occurring illnesses like hypertension, heart disease or elevated cholesterol.

These two patients highlighted the outsized role that diabetes plays in the primary care setting. The tidal wave of diabetes over the last two decades has made it one of the most common diseases that internists and family doctors treat. Right now feels like a good-news-bad-news time on the diabetes front, which in a general medical clinic can sometimes feel like the only front there is.

The good news is that childhood obesity rates have begun to inch downward in some cities, including among poor children, the first positive sign in the obesity epidemic in years. Obese children are potential future diabetic patients, so even incremental progress is a public health victory to celebrate.

Also good news is a study in which adults with obesity and pre-diabetes were able to lose weight with sensible lifestyle changes and coaching. This took place in a primary care setting, not a research setting, so this also suggests that we might be able to bend the curve of new diagnoses of diabetes.

But there’s also bad news. Intensive lifestyle changes for patients with diabetes, disappointingly, did not reduce the risk of stroke or heart attack, even though these patients were able to lose weight, improve their overall quality of life, take fewer medications and even decrease costs. Lifestyle changes — diet and exercise — require huge and ongoing investment efforts for patients; we’d like to think it pays off for the big-ticket clinical outcomes. Hopefully future studies will show benefits.

Even with all the research and new treatments available, combating diabetes can feel like a Sisyphean task. The bizarre contradiction of junk food being cheaper than healthy food, combined with a bombardment of advertising — especially toward children — make it a challenge even for motivated people to eat healthfully. Sugary drinks in monster-size containers abound. And our fixation with screens large and small keeps us increasingly sedentary.

But even with all the uphill challenges, there are successes, even if not perfect ones. Both of my patients who came to my office with florid diabetes that week have improved. Perhaps it was the concreteness of their symptoms that motivated them, but they have both made steady progress getting their diabetes under control.

Over the past few months they’ve been eating more moderately, and exercising more regularly. We’ve been calibrating their medications so that their blood sugars have left the stratospheric levels and are now only moderately elevated. Medication side effects, cost of glucose meter supplies, real-life logistics, and concomitant issues of blood pressure and cholesterol control have made it a challenge to get to normal. We’d still be dinged as “failures” in the quality-measures department for not achieving the recommended clinical goals, but both patients feel vastly better and are much healthier now.

So there’s bad news and good news. But the real news for these two patients – and for many, many more like them — is that diabetes is a marathon, not a sprint. Although there have been a flurry of life changes right now, diabetes is something they will live with for the rest of their lives. They will always have to be cognizant of what they eat. They will have to keep track of medications, glucose levels, carbohydrate intake, doctors’ appointments, exercise, and weight.  They will have to be on the lookout for the many complications that diabetes can bring. This of course is not news to anyone who has diabetes or treats diabetes, but for these two patients this was news.

Now, we gear up for the long haul, the messy, complicated, occasionally gratifying business of living with a lifelong chronic illness.

Dr. Danielle Ofri’s newest book is “What Doctors Feel: How Emotions Affect the Practice of Medicine.” She is an associate professor of medicine at NYU School of Medicine and editor in chief of the Bellevue Literary Review.

http://well.blogs.nytimes.com/2013/10/17/the-challenge-of-diabetes-for-doctor-and-patient

data saving lives, healthcare, rapid learning health systems, research methodology

What doctors can learn from each other – value based healthcare

http://www.ted.com/talks/stefan_larsson_what_doctors_can_learn_from_each_other.html

http://www.ichom.org

  • 17-fold difference in outcomes for prostate surgery in Germany (5% vs 50%)
  • Continuous improvement not only improves quality of care over time, but also improves the quality of care for all who participate in it
  • Agents of change are the clinicians
  • Physicians are always very competitive – “always best in class”
  • They are extremely motivated to improve if they are shown not to be the best.
  • Physicians also thrive from peer recognition – “if one cardiologist calls another cardiologist at a competing [lagging] hospital and asks how they can improve, the leading cardiologist will share”
  • These qualities and dynamics establish an environment supportive of continuous cycle improvement
  • BCG have formed the International Consortium for Health Outcomes Measurement (ICHOM) with Michael Porter (Harvard Business School) and Karolinska Institute (Sweden) but reps from UK, USA, HK, BEL, SWE, NO, DK, DE, NL, AU, SG, Switzerland
  • They will establish data sets providing international outcome comparisons: 4 (2013), 8 (2014), 16 (2015) – 40% of disease burden in 4 years.
  • measuring value (vs costs) in healthcare – the things that matter to patients – will make clinicians part of the solution, not the problem

ContinuousCycleImprovement

 

data saving lives, entrepreneurship, healthcare, rapid learning health systems, research methodology, technology

Jointly Health – analytics for remote monitoring

Jointly Health is the first Big Data Analytics and Closed-Loop Decision Support Platform for Remote Patient Monitoring

From their website:

Company Overview

Jointly Health is a venture-backed company headquartered in Orange County, CA. In collaboration with Qualcomm Life, Jointly Health provides a very disruptive, end-to-end Remote Patient Monitoring and Analytics Platform that can detect changes in health states much earlier and with greater specificity. Jointly Health also makes this information actionable by healthcare professionals inside their existing workflow.

First Application

The first application of Jointly Health is to reduce preventable hospital admissions in patients with complex chronic disease. In the U.S. there are 4 million preventable hospitalizations resulting in $88 billion in preventable costs and unquantifiable amounts of human   suffering. Remote patient monitoring has the potential to reduce these hospitalizations but is plagued by missed intervention opportunities, false alarms and inefficiencies. Jointly Health solves these problems.

Uniqueness

Jointly’s proprietary platform utilizes a number of advanced technologies including Predictive Analytics, Complex-Event Processing, Real-Time Analytics, Signal Processing and Machine Learning and has four distinct advantages.

1. Can collect a wide variety of remote health data at high velocity and volume. This includes multiple types of physiological data, human observational, environmental, contextual, and other meta data.

2. Has an adaptable ecosystem that enables our customers to build complex disease models which we can then execute.

3. Can remotely detect changes in health states much earlier and with greater specificity.

4. Provides healthcare professionals with a closed-loop decision support system for intervention optimization.

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From: http://www.medgadget.com/2013/11/futuremed-day-4-the-end-of-the-beginning.html

Kreindler elaborated on the value of high speed data for applications including remote patient monitoring and analytics to proactively detect deteriorating health states before they being to detract from quality of life. The energetic talk concluded by touching on how Jointly Health, in collaboration with Qualcomm Life, harnesses big data and analytics to make “information actionable.”