Category Archives: complex adaptive systems

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Hammerbacher, Sinai and Minerva…

Top piece on Sinai’s vision. Everything’s lined up there except the doctors – hmmm…. They’ll need some amazing insights to bust through the inertia, but expect they’ll glean them…

http://www.fastcoexist.com/3022050/futurist-forum/in-the-hospital-of-the-future-big-data-is-one-of-your-doctors

In The Hospital Of The Future, Big Data Is One Of Your Doctors

December 5, 2013 | 7:30 AM

From our genomes to Jawbones, the amount of data about health is exploding. Bringing on top Silicon Valley talent, one NYC hospital is preparing for a future where it can analyze and predict its patients’ health needs–and maybe change our understanding of disease.

The office of Jeff Hammerbacher at Mount Sinai’s Icahn School of Medicine sits in the middle of one of the most stark economic divides in the nation. To Hammerbacher’s south are New York City’s posh Upper East Side townhouses. To the north, the barrios of East Harlem.

What’s below is most interesting: Minerva, a humming supercomputer installed last year that’s named after the Roman goddess of wisdom and medicine.

It’s rare to find a supercomputer in a hospital, even a major research center and medical school like Mount Sinai. But it’s also rare to find people like Hammerbacher, a sort of human supercomputer who is best known for launching Facebook’s data science teamand, later, co-founding Cloudera, a top Silicon Valley “big data” software company where he is chief scientist today. After moving to New York this year to dive into a new role as a researcher at Sinai’s medical school, he is setting up a second powerful computing cluster based on Cloudera’s software (it’s called Demeter) and building tools to better store, process, mine, and build data models. “They generate a pretty good amount of data,” he says of the hospital’s existing electronic medical record system and its data warehouse that stored 300 million new “events” last year. “But I would say they are only scratching the surface.”

Could there actually be three types of Type 2 diabetes? A look at the health data of 30,000 volunteers hints that we know less than we realize. Credit: Li Li, Mount Sinai Icahn School of Medicine, and Ayasdi

Combined, the circumstances make for one of the most interesting experiments happening in hospitals right now–one that gives a peek into the future of health care in a world where the amount of data about our own health, from our genomes to ourJawbone tracking devices, is exploding.

“What we’re trying to build is a learning health care system,” says Joel Dudley, director of biomedical informatics for the medical school. “We first need to collect the data on a large population of people and connect that to outcomes.”

To imagine what the hospital of the future could look like at Mount Sinai, picture how companies like Netflix and Amazon and even Facebook work today. These companies gather data about their users, and then run that data through predictive models and recommendation systems they’ve developed–usually taking into account a person’s past history, maybe his or her history in other places on the web, and the history of “similar” users–to make a best guess about the future–to suggest what a person wants to buy or see, or what advertisement might entice them.

Through real-time data mining on a large scale–on massive computers like Minerva–hospitals could eventually operate in similar ways, both to improve health outcomes for individual patients who enter Mount Sinai’s doors as well as to make new discoveries about how to diagnose, treat, and prevent diseases at a broader, public health scale. “It’s almost like the Hadron Collider approach,” Dudley says. “Let’s throw in everything we think we know about biology and let’s just look at the raw measurements of how these things are moving within a large population. Eventually the data will tell us how biology is wired up.”

Dudley glances at his screen to show the very early inklings of this vision of what “big data” brought to the world of health care and medical research could mean.

On it (see the figure above) is a visualization of the health data of 30,000 Sinai patients who have volunteered to share their information with researchers. He points out, in color, three separate clusters of the people who have Type 2 diabetes. What we’re looking at could be an entirely new notion of a highly scrutinized disease. “Why this is interesting is we could really be looking at Type 2, Type 3, and Type 4 diabetes,” says Dudley. “Right now, we have very coarse definitions of disease which are not very data-driven.” (Patients on the map are grouped by how closely related their health data is, based on clinical readings like blood sugar and cholesterol.)

From this map and others like it, Dudley might be able to pinpoint genes that are unique to diabetes patients in the different clusters, giving new ways to understand how our genes and environments are linked to disease, symptoms, and treatments. In another configuration of the map, Dudley shows how racial and ethnic genetic differences may define different patterns of a disease like diabetes–and ultimately, require different treatments.

These are just a handful of small examples of what could be done with more data on patients in one location, combined with the power to process it. In the same way Facebook shows the social network, this data set is the clinical network. (The eventual goal is to enroll 100,000 patients in what’s called the BioMe platform to explore the possibilities in having access to massive amounts of data.) “There’s nothing like that right now–where we have a sort of predictive modeling engine that’s built into a health care system,” Dudley says. “Those methods exist. The technology exists, and why we’re not using that for health care right now is kind of crazy.”

While Sinai’s goal is to use these methods to bring about more personalized diagnoses and treatments for a wide variety of diseases, such as cancer or diabetes, and improve patient care in the hospital, there are basic challenges that need to be overcome in order to making this vision achievable.

Almost every web company was born swimming in easily harvested and mined data about users, but in health care, the struggle has for a long time been more simple: get health records digitized and keep them private, but make them available to individual doctors, insurers, billing departments, and patients when they need them. There’s not even a hospital’s version of a search engine for all its data yet, says Hammerbacher, and in the state the slow-moving world of health care is in today, making predictions that would prevent disease could be just the icing on the cake. “Simply centralizing the data and making it easily available to a broad base of researchers and clinicians will be a powerful tool for developing new models that help us understand and treat disease,” he says.

Sinai is starting to put some of these ideas into clinical practice at the hospital. For example, in a hint of more personalized medicine that could come one day, the FDA is beginning to issue labels for some medicines that dictate different doses for patients who have a specific genetic variant (or perhaps explain that they should avoid the medicine altogether). The “Clipmerge” software that the hospital is beginning to now use makes it easier for doctors to quickly search and be notified of these kinds of potential interactions on an electronic medical record form.

On the prediction side, the hospital has already implemented a predictive model called PACT into its electronic medical record system. It is used to predict the likelihood that a discharged patient will come back to the hospital within 90 days (the new health care law creates financial incentives for hospitals to reduce their 90-day readmission rate). Based on the prediction, a high-risk patient at the medical center now might actually receive different care, such as being assigned post-care coordinator.

Eventually, there will be new kinds of data that can be put in mineable formats and linked to electronic patient records, from patient satisfaction surveys and doctors’ clinical notes to imaging data from MRI scans, Dudley says.

Right now, for example, the growing volumes of data generated from people’s fitness and health trackers is interesting on the surface, but it’s hard to glean anything meaningful for individuals. But when the data from thousands of people are mined for signals and links to health outcomes, Dudley says, it’s likely to prove valuable in understanding new ways to prevent disease or detect it at the earliest signs.

A major limitation to this vision is the hospital’s access to all of these new kinds of data. There are strict federal laws that govern patient privacy, which can make doctors loathe to experiment with ways to gather it or unleash it. And there are many hoops today to transferring patient data from one hospital or doctor to another, let alone from all the fitness trackers floating around. If patients start demanding more control over their own health data and voluntarily provide it to doctors, as Dudley believes patients will start to do, privacy could become a concern in ways people don’t expect or foresee today–just as it has on the Internet.

One thing is clear: As the health care system comes under pressure to cut costs and implement more preventative care, these ideas will become more relevant. Says Dudley: “A lot of people do research on computers, but I think what we’re hoping for is that we’re going to build a health care system where complex models … are firing on an almost day-to-day basis. As patients are getting information about them put in the electronic medical record system there will be this engine in the background.”

 

JESSICA LEBER

complex adaptive systems

Fox vs. Hedgehog

Source: http://bigthink.com/experts-corner/beware-the-one-trick-hedgehog

Beware The One Trick Hedgehog

DECEMBER 9, 2013, 12:00 AM
Unnamed-1

There are two kinds of experts and we often don’t use them wisely. The differences between foxes and hedgehogs, and Newton and Darwin, can show when a diversified portfolio of experts is advisable. This year’s Nobel Prize committee in economics evidently agrees: It rewarded the apparently “opposing” theories of Eugene Fama (efficient markets) and Robert Shiller (animal spirits), which pit reason against passion.

Philip Tetlock did the relevant experiment, getting established experts to make 82,000 predictions about political and economic trends and tracking their accuracy. He found differences in thinking style that could predict who’d predict better. Tetlock classified experts using the aphorism “The fox knows many things, but the hedgehog knows one big thing.”

Hedgehogs think the world follows simple rules, and prefer a grand unified theory. Convinced they possess the One True Theory, they confidently and zealously defend it. This encourages a closed mindset which is more prone to confirmation bias (squeezing evidence into the theory and discounting what doesn’t fit).

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Foxes believe the world is complex and distrust grand theories. They’re empirically driven, seek locally useful rules, and are open, cautious, eclectic thinkers tolerant of counter arguments. Unwedded to One True Theory they cope better with ambiguity, see the limits of their thinking tools, often qualify their opinions, and more readily adapt to new data.

Tetlock found that foxes fared better than hedgehogs, who barely beat “dart-throwing
chimps.”

Despite that hedgehogs hogged the spotlight. The media love their certain sounding sound bites and flamboyant forecasts. Sadly, the most quoted were the worst predictors and increased
confidence actually decreased accuracy.

Darwin’s greatest lesson applies: Fit to context is key. Hedgehog-experts are good in fields with stable behaviors and known rules. Otherwise, fox-experts are a better bet. This relates to how Newton differs from Darwin. Newton worked with unchanging behaviors. His laws can predict detailed outcomes in simple closed situations. But Darwin dealt with complex systems of changing parts and behaviors; he described the shape of open generative processes (note the cautious foxiness of that plural; “natural selection was the main but not the exclusive means” of evolution. These evolutionary processes have stable tendencies but less predictable specific outcomes.

The closer we get to humans and social sciences, the less Newton-like and hedgehoggy life gets. Economies, full of changing parts and innovative behaviors, need foxy thinking.

Aquinas famously feared “the man of a single book.” And we should be wary of experts with a single model. Models are hedgehog thinking incarnated. With assumptions built into their structure, they can create “model-risk.” Widespread use leads many to overlook the same issues. The dominance of Fama’s big idea possibly had this effect in the last financial
crisis.

The more we rely on markets, the more important it is to use economic experts wisely. Market-loving hedgehogs tend to downplay the empirical problems of their beloved system. Fixed ideas are risky in a changing world; we’re predictably safer hearing also from market-realist foxes. So should we diversify or concentrate risks?

Illustration by Julia Suits, The New Yorker Cartoonist & author of The Extraordinary Catalog of Peculiar Inventions.

complex adaptive systems, cool, data saving lives, entrepreneurship, file note, healthcare, healthy habits, meaning, musings, nutrition, policy, politics, quantified self, rapid learning health systems, research methodology

Healthways…

http://www.healthways.com  || http://www.healthways.com.au

Christian Sellars from MSD put on a terrific dinner in Crows Nest, inviting a group of interesting people to come meet with his team, with no agenda:

  • Dr Paul Nicolarakis, former advisor to the Health Minister
  • Dr Linda Swan, CEO Healthways
  • Ian Corless, Business Development & Program Manager, Wentwest
  • Dr Kevin Cheng, Project Lead Diabetes Care Project
  • Dr Stephen Barnett, GP & University of Wollongong
  •  Warren Brooks, Customer Centricity Lead
  • Brendan Price, Pricing Manager
  • Wayne Sparks, I.T. Director
  • Greg Lyubomirsky, Director, New Commercial Initiatives
  • Christian Sellars, Director, Access 

MSD are doing interesting things in health. In Christian’s words, they are trying to uncouple their future from pills.

After some chair swapping, I managed to sit across from Linda Swan from Healthways. It was terrific. She’s a Stephen Leeder disciple, spent time at MSD, would have been an actuary if she didn’t do medicine, and has been on a search that sounds similar to mine.

Healthways do data-driven, full-body, full-community wellness.

They’re getting $100M multi-years contracts from PHIs.

Amazingly, they’ve incorporated social determinants of health into their framework.

And even more amazingly, they’ve been given Iowa to make healthier.

They terraform communities – the whole lot.

Linda believes their most powerful intervention is a 20min evidence-based phone questionnaire administered to patients on returning home, similar to what Shane Solomon was rolling out at the HKHA. But they also supplant junk food sponsorship of sport and lobby for improvements to footpaths etc.

Just terrific. We’re catching up for coffee in January.

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

BMJ: Can behavioural economics make us healthy

  • BE policies are by design less coercive and more effective than traditional approaches
  • It is generally far more effective to punish than to reward
  • Sticks masquerading as carrots – simultaneous, zero-sum incentives and penalties
  • References to policies which have and have not worked – but why can’t policy be research?
  • Conventional economics can therefore justify regulatory interventions, such as targeted taxes and subsidies, only in situations in which an individual’s actions imposes costs on others—for example, second hand cigarette smoke. But the potential reach of behavioural economics is much greater. By recognising the prevalence of less than perfectly rational behaviour, behavioural economics points to a large category of situations in which policy intervention might be justified—those characterised by costs which people impose on themselves (internalities), such as the long term health consequences of smoking on smokers.
  •  Is it fair to say that in a universal health care system, any preventable ill health imposes costs on others, as it is the tax payer who picks up the cost of treatment?
  • present bias: the tendancy for decision makers tend to put too much weight on costs and benefits that are immediate and too little on those that are delayed. Present bias can be used to positive effect by providing small, frequent (i.e. immediate) payments for beneficial behaviours e.g. smoking cessation, medication adherence, weight loss
  • “peanuts effect” decision error: the tendency to pay too little attention to the small but cumulative consequences of repeated decisions, such as the effect on weightof repeated consumption of sugared beverages or the cumulative health effect of smoking.
  • competition and peer support are more powerful forms of behaviourally mediated interventions

Care of Nicholas Gruen.

PDF: CanBehaviouralEconomicsMakeUsHealthier_BMJ

Similarly in Health Affairs: http://content.healthaffairs.org/content/32/4/661.short

complex adaptive systems, policy

Health Affairs: Ageing research will deliver best ROI

  • “In the last half-century, major life expectancy gains were driven by finding ways to reduce mortality from fatal diseases. But now disabled life expectancy is rising faster than total life expectancy, leaving the number of years that one can expect to live in good health unchanged, or diminished. If we can age more slowly, we can delay the onset and progression of many disabling disease simultaneously”
  • The study also shows significantly lower and declining returns for continuing the current research ‘disease model’, which seeks to treat fatal diseases independently, rather than tackling the shared, underlying cause of frailty and disability – such as the aging process itself.
  • Indeed, lowering the incidence of cancer by 25% in the next few decades – in line with the most favourable historical trends – would barely improve population health over not doing anything at all, the analysis showed.
  • Further analysis showed the same is true of heart disease, the leading cause of death worldwide. The study shows that, with major advances in cancer treatment or heart disease, a 51-year-old can expect to live about one more year. A modest improvement in delaying aging would double this to two additional years — and those years are much more likely to be spent in good health.
    The increase in healthy years of life would also have an economic benefit of approximately $7.1 trillion over the next five decades, they added.
    “Even a marginal success in slowing aging is going to have a huge impact on health and quality of life,” said corresponding author S. Jay Olshansky of the School of Public Health at the University of Illinois-C hicago. “This is a fundamentally new approach to public health that would attack the underlying risk factors for all fatal and disabling diseases.”
    “We need to begin the research now,” he said. “We don’t know which mechanisms are going to work to actually delay aging, and there are probably a variety of ways this could be accomplished, but we need to decide now that this is worth pursuing.”
  • Several previous studies have already shown how we might age more slowly, they team noted. These have included studies of the genetics of “centenarians” and other long-lived people.
    Attempts to slow the signs of biological aging have also been achieved in animal models, using pharmaceuticals and also dietary interventions such as caloric restriction or supplementation. But until now, no assessment has been made of the costs and health returns on developing therapies for delayed aging, said the research team.

Source: http://content.healthaffairs.org/content/32/10/1698.abstract

Recent scientific advances suggest that slowing the aging process (senescence) is now a realistic goal. Yet most medical research remains focused on combating individual diseases. Using the Future Elderly Model—a microsimulation of the future health and spending of older Americans—we compared optimistic “disease specific” scenarios with a hypothetical “delayed aging” scenario in terms of the scenarios’ impact on longevity, disability, and major entitlement program costs. Delayed aging could increase life expectancy by an additional 2.2 years, most of which would be spent in good health. The economic value of delayed aging is estimated to be $7.1 trillion over fifty years. In contrast, addressing heart disease and cancer separately would yield diminishing improvements in health and longevity by 2060—mainly due to competing risks. Delayed aging would greatly increase entitlement outlays, especially for Social Security. However, these changes could be offset by increasing the Medicare eligibility age and the normal retirement age for Social Security. Overall, greater investment in research to delay aging appears to be a highly efficient way to forestall disease, extend healthy life, and improve public health.

Article: http://www.foodnavigator-asia.com/Policy/Is-research-on-delayed-aging-a-better-investment-than-cancer-and-heart-disease

Article PDF: Is research on delayed aging a better investment than cancer and heart disease_

complex adaptive systems, cool, data saving lives, entrepreneurship, healthcare, healthy habits, nutrition, policy, quantified self, rapid learning health systems, research methodology

Living on the edge with Farzad

  • It’s not as simple as you give people information and they change their behavior.  It’s information tools that build on that data and build on communities and a much more sophisticated understanding about how behavior changes. What TEDMED is also great at, is understanding the power of marketing. People think of marketing of being about advertising, but marketing is the best knowledge we have about how to change behavior and all those intangibles, those predictably irrational insights, of how and why we do what we do.
  • It’s harnessing those, instead of having them lead to worse health – like present value discounting that leads to people wanting to procrastinate and eat that doughnut now instead of going to the gym. Or the power of anchoring, where we fixate on the first thing we see and won’t think objectively about the true risks of things. Or the herd effect, our friend is overweight and so we are more likely to be overweight.
  • All those nudges that are possible can be delivered to us ubiquitously and continuously, and we can choose to have them. It’s not some big brother dystopic vision. It’s me saying, ‘I want to be healthier, so I will do something now that will help me overcome and use my irrationality to help me stay healthy.  To me, that’s the neat new edge between mobile cloud computing, personal healthcare, behavioral economics, healthcare IT, data science and visualization, design, and marketing. It’s that sphere that has so many possibilities to get us to better health.

http://blog.tedmed.com/?p=4153

 

The exit interview: Farzad Mostashari on imagination, building healthcare bridges and his biggest “aha” moments

Posted on  by Stacy Lu

Farzad Mostashari, MD, stepped down from his post as the National Coordinator for Health Information Technology at the U.S. Department of Health and Human Services (HHS), during the first week of October, which was also the first week of the Federal partial shutdown. During his tenure, Dr. Mostashari, who spoke at TEDMED 2011 with Aneesh Chopra, led the creation and definition of meaningful use incentives and tenaciously challenged health care leaders and patients to leverage data in ways to encourage partnerships with patients within the clinical health care team.

Whitney Zatzkin and Stacy Lu had the opportunity to speak with Dr. Mostashari during his last week in office.

WZ: Sometimes, a person will experience an “aha!” moment – a snapshot or event that reveals a new opportunity and challenges him/her to pursue something nontraditional. Was there a critical turning point when you figured out, ‘I’m the guy who should be doing this?’

Yeah, I’ve been fortunate to have a couple of those ‘aha’ moments in my life. One of them was when I was an epidemic intelligence service officer back in 1998, working for the CDC in New York City. I’ve always been interested in edge issues, border issues; things that are on the boundaries between different fields. I was there in public health, but I was interested in what was happening in the rest of the world around electronic transactions and using data in a more agile way.

In disease surveillance we often look back — the way we do claims data now – years later or months later you get the reports and you look for the outbreak, and often times the outbreak’s already come and gone by the time you pick it up. But I started thinking and imagining: What if the second something happens, you can start monitoring it? In New York City the fire department was monitoring ambulance calls. I said, ‘Wow, if we could just categorize those by the type of call, maybe we’ll see some sort of signal in the noise there.’

When I was first able to visualize the trends in the proportion of ambulance dispatches in NYC that were due to respiratory distress, what I saw was flu.  What jumped out at me was the sinusoidal curve. Wham! At different times of year, it could be a stutter process – it would go up and you would see this huge increase, followed two weeks later by an increase in deaths. It was like the sky opening up. The evidence was there all along, but I am the first human being on earth to see this. That was validation, for me, of the idea that electronic data opens up worlds. To bring that data to life, to be able to extract meaning from those zeros and ones — that’s life and death. That was my first ‘aha’ moment.

The second aha was after I joined New York City Department of Health, and I started a data shop to build our policy around smoking and tracking chronic diseases. What we realized was that healthcare was leaving lives on the table. There were a lot of lives we could save by doing basic stuff a third-year medical student should do, but we’re not doing it.  Related to that – Tom Frieden had a great TEDMED talk about everybody counts.

I said, ‘I want to take six months off and do a sabbatical, and see if there’s anything to using electronic health records to provide those insights, not to save lives by city level, but on the 10 to the 3 level – the 1,000 patient practice. That started the whole journey.  None of the vendors at the time had the vision we had, but we finally got someone to work with us and rolled this system out.  We called some doctors some 23 times, and did all the work to get to the starting line.  Finally, I took Tom on a field visit to see one of the first docs to get the program.

It was a very normal storefront in Harlem, and a nice physician, very caring, very typical.  I asked her what she thought of the program. She said, ‘It’s ok. I’m still getting used to it.’  I said, ‘Did you ever look at the registry tab on the right, where you can make a list of your patients? She said no.  I said, ok – how many of your elderly patients did you vaccinate for flu this year? She said, ‘I don’t know, about 80 to 85 percent.  I’m pretty good at that.’  I said, ‘o.k., let’s run a query.’  And it was actually something like 22 percent. And she said – this was the aha moment – ‘That’s not right.’

That’s generally the feeling the docs have when they get a quality measure report from the health plan. But that’s population health management — the ability to see for the first time ever that everybody counts. And being able to then think about decision support and care protocols to reduce your defect rate. That was the validation that we’re on to something. Without the tools to do this, all the payment changes in the world can’t make healthcare accountable for cost and quality if you can’t see it.

WZ: Everyone has that moment in life when they’re considering all of their career options. As you were considering medical school, what else was on the table?

I actually didn’t think I was going to go to medical school. I was at the Harvard School of Public Health. I was interested in making an impact in public health. I grew up in Iran, and thought I would do international public health work. And then my dad got sick; he had a cardiac issue. The contrast between the immediacy of the laying on of hands of healthcare, and the somewhat abstractness of international public health — the distance, the remove — tipped me into saying,  ‘You know, maybe I should go to medical school.’  I’ve been on that edge between healthcare and public health ever since, and always trying to drag the two closer to each other.

SL: Fast forward 20 years.  You’re giving another talk at TEDMED.  What’s the topic?

TEDMED and Jay Walker’s vision is more powerful in the futurescope, rather than in the retroscope. It’s more powerful to be where we are today and imagine a different future rather than look back and say, ‘Oh, yeah, we’ve done this.’  So what’s the future I would love to imagine?

The most exciting thing – as Jay Walker once mentioned in a talk comparing “medspeed” to “techspeed” – is to fully imagine what will happen if techspeed is brought to healthcare. Right now, there’s all this unrealized value that’s being given away for free that doesn’t show up on any GDP lists – what Tim O’Reilly called “the clothesline paradox.”  That kind of possibility brought to medicine, but where software costs $100,000 as opposed to free, and it evolves daily and is more powerful and quicker every day, and it’s beautiful and usable and intuitive, and that’s what people compete on.

And all of that is toward the goal of empowering people.  Someone said, maybe it was Jay at TEDMED, that a 14-year-old kid in Africa with a smart phone has more access to information than Bill Clinton did as President. Information is power, and it has changed everything but healthcare. For me the vision is breaking down that wall, so that patients can be empowered and can bind themselves to the mast to use what we’ve learned about how behavior changes.

It’s not as simple as you give people information and they change their behavior.  It’s information tools that build on that data and build on communities and a much more sophisticated understanding about how behavior changes. What TEDMED is also great at, is understanding the power of marketing. People think of marketing of being about advertising, but marketing is the best knowledge we have about how to change behavior and all those intangibles, those predictably irrational insights, of how and why we do what we do.

It’s harnessing those, instead of having them lead to worse health – like present value discounting that leads to people wanting to procrastinate and eat that doughnut now instead of going to the gym. Or the power of anchoring, where we fixate on the first thing we see and won’t think objectively about the true risks of things. Or the herd effect, our friend is overweight and so we are more likely to be overweight.

All those nudges that are possible can be delivered to us ubiquitously and continuously, and we can choose to have them. It’s not some big brother dystopic vision. It’s me saying, ‘I want to be healthier, so I will do something now that will help me overcome and use my irrationality to help me stay healthy.  To me, that’s the neat new edge between mobile cloud computing, personal healthcare, behavioral economics, healthcare IT, data science and visualization, design, and marketing. It’s that sphere that has so many possibilities to get us to better health.

The thing about the health is, we have a Persian saying: Health is a crown on the head of the healthy that only the sick can see. When you have it, you don’t appreciate it, but when you’re sick and someone you love is sick, there’s nothing better.  You would do anything to get that. We need to bring that vision of the crown to everyone and help each of us grab it when we can.

WZ: I noticed you closing your eyes while preparing to answer a question. How do you pursue being able to exercise your imagination, in particular while you’re sitting in a building that’s been marked for being the least imaginative?

Because the world, as it is, is too immediate and real and limiting, sometimes you have to close your eyes to see a different world.

What has been amazing has been to see that, contrary to what people expect, this building is filled with people with untapped, unbound, unfettered imaginations who are slogging through. They’re just trapped. You give them the opening, the smallest bit of daylight to exercise that, and they’re off and running.

I give a lot of credit to Todd Park as our “innovation fellow zero,” He saw the possibility that there are more than two kinds of people in the world, innovators and everybody else. For him, it was about going to create a space where outside innovators can be the catalyst or spark that elevates and permissions the innovation of the career civil servant at CMS in Baltimore. That’s been cool.

SL: What’s your bowtie going to do after you leave HHS?  Will we see it lounging on the beach in Boca?

I like the bowtie.  I think I’m going to keep it.  Perhaps the @FarzadsBowtie Twitter handle is going to go into hibernation, I don’t know.  I don’t control it. One of the things the bowtie does for me is help me remember not to get too comfortable.

I once said at the Consumer Health IT Summit – ‘You’re a bunch of misfits – glorious misfits. And I feel like I’m very well suited to be your leader. You know, I always felt American in Iran, and felt Iranian in America when I came here. I felt like a jock among my geeky friends, and like a geek among jocks. For crying out loud, I wear a bowtie!  I don’t have to tell you I’m a misfit.’

It’s that sense of not fitting into the world as it is. The world doesn’t fit me.  So instead of saying,  ‘I need to change,’ this group of people said, ‘The world needs to change.’ That’s the difference between a misfit and a glorious misfit.

The person who doesn’t fit into our healthcare system is the patient. The patient’s preferences don’t fit into the need to maximize revenue and do more procedures. The patient’s family doesn’t fit into the, ‘I want to do an eight-minute visit and get you out the door’ agenda. The patient asking questions doesn’t fit.  That’s the change we need to make. It’s not that we need to change. Healthcare needs to change to fit the patient.

Shortly following this interview, Dr. Mostashari left HHS and is now the a visiting fellow of the Engelberg Center for Health Care Reform at the Brookings Institution, where he aims to help clinicians improve care and patient health through health IT, focusing on small practices.

This interview was edited for length and readability.

complex adaptive systems, healthcare, healthy habits, policy, quotes & aphorisms, rapid learning health systems

Gamification in health…

  • people are more open to learning from a game than a powerpoint or clinician
  • fun, competition, and social networks all have positive affects on health and fitness behavior
  • “Practitioners still haven’t internalized the idea that we need to help people do the right thing. Not just by giving them the opportunity, but making them want to do it.”
  • “Designing engagement into social games is largely about manipulating dopamine response. Gamifying health allows us to hack into our natural feedback loops by engineering ways for us to get more dopamine for demonstrating good behavior.”

 

Source: http://www.medcrunch.net/whats-fun/ (via RWJF)

Gaming for Patient Treatment – What’s Fun Got to Do With It?

by  on Nov 6, 2013 • 8:48 pm

“People rarely succeed unless they have fun in what they are doing.” -Dale Carnegie

The Theory of Fun is an organization devoted to social experiments in fun. In one experiment, they turned a staircase next to an escalator into a piano to see whether people would still opt for the less physically challenging escalator. Not only did people choose for the fun piano staircase; they also went up and down the stairs multiple times (see the results here.) Playfulness has increasingly become incorporated into patient engagement and adherence. Additionally, creative tactics like video games that use fun, competition, and your social networks have shown positive affects on health and fitness behavior.

RM2 Customer 1 Gaming for Patient Treatment What’s Fun Got to Do With It?Paul Tarini, team leader for the Robert Wood Johnson Foundation’s Pioneer Portfolio, reported in 2010 that the collision of games and healthcare was inevitable. Featured that year at the Games for Health conference in Boston, MA, were dancing games for patients with Parkinson’s disease, or alternatives-to-smoking games on iPhones. Since, we’ve seen an unveiling of companies that develop games benefitting all sorts of conditions from anxiety and depression (SinaSprite byLitesprite) to games for kids with cancer (Re-Mission2 by Hopelab). The results have been significant and have illustrated how patients feel more inclined to accept and learn from a game about their condition than from, say, a PowerPoint or clinician. In Re-Mission2, results showed how players adhered to their treatment longer and more consistently after interacting with the game. Even more impressive, players had higher levels of chemotherapy in their body and so were literally responding to treatment better.

Michael Fergusson, founder and CEO of Ayogo Games, a social gaming production company based in Vancouver, believes games are the key to patient engagement and adherence. Practitioners, Fergusson says, “ still haven’t internalized the idea that we need to help people do the right thing. Not just by giving them the opportunity, but making them want to do it.”

Prescribed Fun: The Trick (or Science) of Adherence and Engagement

The World Health Organization (click for report) has said that people around the world will benefit more from adherence than from new therapy. Esther Dyson, an active investor in the digital health movement, has said, “It’s colossal stupidity that people aren’t healthier, because we know how to do it.” Yet, we don’t. Our own inability to do what we know we need to is the cause of many health care problems.

Perhaps social games can help. Social games are digital games played with your online social communities (like Facebook and Twitter). According to Ayogo Games: “Designing engagement into social games is largely about manipulating dopamine response. Gamifying health allows us to hack into our natural feedback loops by engineering ways for us to get more dopamine for demonstrating good behavior.”

A recent NPR article, “How Video Games Are Getting Inside Your Head – And Your Wallet”discusses how video game architects actively track children’s engagement with the game they’re playing. Inherent in any game design is research, tests, and analysis, all of which are imperative to making the game more fun, more engaging, and more likely to hold the player’s attention longer, and in some cases long enough to buy something.

The science of the brain and human behavior are integral to the success of a game. Many, especially parents trying desperately to get their kids outdoors, interacting with “real” things and “real” people, have more damning language about these studies than applauding. Indeed, most, when attributing the term “brain manipulation” to something, don’t have many nice things to say. Yet, looking at all this through a health care lens, if doing the same types of testing, tweaking and manipulation leads to positive and permanent change in health and fitness of an individual, it can’t be that bad, right?

Michael Fergusson believes this, and has created successful games where players’ health and behavior improve because of it.  One of Ayogo’s first health care games, Healthseeker, was for people living with diabetes, and the first health care game on Facebook. They had over 15,000 players. There were parts that were extremely successful, but other elements that weren’t. They reviewed the data and looked at what worked and what didn’t to see what design elements of the game brought players success in their health goals. What they found was players who consistently received incoming messages of encouragement from their online social networks had significantly greater chances of success. Putting friends and family into their application, Ayogo discovered, makes the game more meaningful. As a result, this design element has been brought forward into other game designs.

Team Fun 

“Man is most nearly himself when he achieves the seriousness of a child at play.” -Heraclitus

Outside of the digital space, Little Bit Therapeutic Riding Center provides equine facilitated therapy to children and adults with neurological, pyshological, and physiological disabilities. For the riders, working with horses provides an overwhelming sense of joy, and the therapy no longer becomes treatment-like. Instead, it’s fun and unpredictable. More, a rider’s experience of success is linked to the team supporting her efforts – her volunteers, her horse, and her instructor. Play, joy, laughter, excitement – they all have healing powers for our minds, bodies, and spirits – and the value of your community in sustaining all that cannot be underestimated, whatever the method.

“The experience of interacting with your own health can be dramatically affected,” says Fergusson. Because of this you want the design of the experience to engage as many people as possible so that embedded in the design, is an evolving conversation where people can learn together and improve the quality of life together. To this, Fergusson asks an interesting question: “There’s a question about who’s behavior you’re really trying to affect in social gaming – is it the person’s behavior or the community of that person?” Perhaps it’s both that need to change in order for engagement and adherence to really stick.

complex adaptive systems, cool, musings, nutrition, policy, politics, technology

I have no idea, I just write…

Punchy interview with Bill Gates’ favourite author. Alignment on food. Other things interesting, but unrelated.

http://www.wired.com/wiredscience/2013/11/vaclav-smil-wired/?mbid=synd_gfdn_bgtw

This Is the Man Bill Gates Thinks You Absolutely Should Be Reading

Author Vaclav Smil tackles the big problems facing America and the world.   Andreas Laszlo Konrath“There is no author whose books I look forward to more than Vaclav Smil,” Bill Gates wrote this summer. That’s quite an endorsement—and it gave a jolt of fame to Smil, a professor emeritus of environment and geography at the University of Manitoba. In a world of specialized intellectuals, Smil is an ambitious and astonishing polymath who swings for fences. His nearly three dozen books have analyzed the world’s biggest challenges—the future of energy, food production, and manufacturing—with nuance and detail. They’re among the most data-heavy books you’ll find, with a remarkable way of framing basic facts. (Sample nugget: Humans will consume 17 percent of what the biosphere produces this year.)His conclusions are often bleak. He argues, for instance, that the demise of US manufacturing dooms the country not just intellectually but creatively, because innovation is tied to the process of making things. (And, unfortunately, he has the figures to back that up.) WIRED got Smil’s take on the problems facing America and the world.

You’ve written over 30 books and published three this year alone. How do you do it?

Hemingway knew the secret. I mean, he was a lush and a bad man in many ways, but he knew the secret. You get up and, first thing in the morning, you do your 500 words. Do it every day and you’ve got a book in eight or nine months.

What draws you to such big, all-encompassing subjects?

I saw how the university life goes, both in Europe and then in the US. I was at Penn State, and I was just aghast, because everyone was what I call drillers of deeper wells. These academics sit at the bottom of a deep well and they look up and see a sliver of the sky. They know everything about that little sliver of sky and nothing else. I scan all my horizons.

Let’s talk about manufacturing. You say a country that stops doing mass manufacturing falls apart. Why?

In every society, manufacturing builds the lower middle class. If you give up manufacturing, you end up with haves and have-nots and you get social polarization. The whole lower middle class sinks.

You also say that manufacturing is crucial to innovation.

Most innovation is not done by research institutes and national laboratories. It comes from manufacturing—from companies that want to extend their product reach, improve their costs, increase their returns. What’s very important is in-house research. Innovation usually arises from somebody taking a product already in production and making it better: better glass, better aluminum, a better chip. Innovation always starts with a product.

Look at LCD screens. Most of the advances are coming from big industrial conglomerates in Korea like Samsung or LG. The only good thing in the US is Gorilla Glass, because it’s Corning, and Corning spends $700 million a year on research.

American companies do still innovate, though. They just outsource the manufacturing. What’s wrong with that?

Look at the crown jewel of Boeing now, the 787 Dreamliner. The plane had so many problems—it was like three years late. And why? Because large parts of it were subcontracted around the world. The 787 is not a plane made in the USA; it’s a plane assembled in the USA. They subcontracted composite materials to Italians and batteries to the Japanese, and the batteries started to burn in-flight. The quality control is not there.

Bill Gates’ actual bookshelf. We count six books by Smil in this section alone.   Ian Allen

Can IT jobs replace the lost manufacturing jobs?

No, of course not. These are totally fungible jobs. You could hire people in Russia or Malaysia—and that’s what companies are doing.

Restoring manufacturing would mean training Americans again to build things.

Only two countries have done this well: Germany and Switzerland. They’ve both maintained strong manufacturing sectors and they share a key thing: Kids go into apprentice programs at age 14 or 15. You spend a few years, depending on the skill, and you can make BMWs. And because you started young and learned from the older people, your products can’t be matched in quality. This is where it all starts.

You claim Apple could assemble the iPhone in the US and still make a huge profit.

It’s no secret! Apple has tremendous profit margins. They could easily do everything at home. The iPhone isn’t manufactured in China—it’s assembled in China from parts made in the US, Germany, Japan, Malaysia, South Korea, and so on. The cost there isn’t labor. But laborers must be sufficiently dedicated and skilled to sit on their ass for eight hours and solder little pieces together so they fit perfectly.

But Apple is supposed to be a giant innovator.

Apple! Boy, what a story. No taxes paid, everything made abroad—yet everyone worships them. This new iPhone, there’s nothing new in it. Just a golden color. What the hell, right? When people start playing with color, you know they’re played out.

Let’s talk about energy. You say alternative energy can’t scale. Is there no role for renewables?

I like renewables, but they move slowly. There’s an inherent inertia, a slowness in energy transitions. It would be easier if we were still consuming 66,615 kilowatt-hours per capita, as in 1950. But in 1950 few people had air-conditioning. We’re a society that demands electricity 24/7. This is very difficult with sun and wind.

Look at Germany, where they heavily subsidize renewable energy. When there’s no wind or sun, they boost up their old coal-fired power plants. The result: Germany has massively increased coal imports from the US, and German greenhouse gas emissions have been increasing, from 917 million metric tons in 2011 to 931 million in 2012, because they’re burning American coal. It’s totally zany!

What about nuclear?

The Chinese are building it, the Indians are building it, the Russians have some intention to build. But as you know, the US is not. The last big power plant was ordered in 1974. Germany is out, Italy has vowed never to build one, and even France is delaying new construction. Is it a nice thought that the future of nuclear energy is now in the hands of North Korea, Pakistan, India, and Iran? It’s a depressing thought, isn’t it?

The basic problem was that we rushed into nuclear power. We took Hyman Rickover’s reactor for submarines and pushed it so America would beat Russia. And that’s just the wrong reactor. It was done too fast with too little forethought.

You call this Moore’s curse—the idea that if we’re innovative enough, everything can have yearly efficiency gains.

It’s a categorical mistake. You just cannot increase the efficiency of power plants like that. You have your combustion machines—the best one in the lab now is about 40 percent efficient. In the field they’re about 15 or 20 percent efficient. Well, you can’t quintuple it, because that would be 100 percent efficient. Impossible, right? There are limits. It’s not a microchip.

The same thing is true in agriculture. You cannot increase the efficiency of photosynthesis. We improve the performance of farms by irrigating them and fertilizing them to provide all these nutrients. But we cannot keep on doubling the yield every two years. Moore’s law doesn’t apply to plants.

So what’s left? Making products more energy-efficient?

Innovation is making products more energy-efficient — but then we consume so many more products that there’s been no absolute dematerialization of anything. We still consume more steel, more aluminum, more glass, and so on. As long as we’re on this endless material cycle, this merry-go-round, well, technical innovation cannot keep pace.

Yikes. So all we’ve got left is reducing consumption. But who’s going to do that?

My wife and I did. We downscaled our house. It took me two years to find a subdivision where they’d let me build a custom house smaller than 2,000 square feet. And I’ll test you: What is the simplest way to make your house super-efficient?

Insulation!

Right. I have 50 percent more insulation in my walls. It adds very little to the cost. And you insulate your basement from the outside—I have about 20 inches of Styrofoam on the outside of that concrete wall. We were the first people building on our cul-de-sac, so I saw all the other houses after us—much bigger, 3,500 square feet. None of them were built properly. I pay in a year for electricity what they pay in January. You can have a super-efficient house; you can have a super-efficient car, a little Honda Civic, 40 miles per gallon.

Your other big subject is food. You’re a pretty grim thinker, but this is your most optimistic area. You actually think we can feed a planet of 10 billion people—if we eat less meat and waste less food.

We pour all this energy into growing corn and soybeans, and then we put all that into rearing animals while feeding them antibiotics. And then we throw away 40 percent of the food we produce.

Meat eaters don’t like me because I call for moderation, and vegetarians don’t like me because I say there’s nothing wrong with eating meat. It’s part of our evolutionary heritage! Meat has helped to make us what we are. Meat helps to make our big brains. The problem is with eating 200 pounds of meat per capita per year. Eating hamburgers every day. And steak.

You know, you take some chicken breast, cut it up into little cubes, and make a Chinese stew—three people can eat one chicken breast. When you cut meat into little pieces, as they do in India, China, and Malaysia, all you need to eat is maybe like 40 pounds a year.

So finally, some good news from you!

Except for antibiotic resistance, which is terrible. Some countries that grow lots of pork, like Denmark and the Netherlands, are either eliminating antibiotics or reducing them. We have to do that. Otherwise we’ll create such antibiotic resistance, it will be just terrible.

So the answers are not technological but political: better economic policies, better education, better trade policies.

Right. Today, as you know, everything is “innovation.” We have problems, and people are looking for fairy-tale solutions—innovation like manna from heaven falling on the Israelites and saving them from the desert. It’s like, “Let’s not reform the education system, the tax system. Let’s not improve our dysfunctional government. Just wait for this innovation manna from a little group of people in Silicon Valley, preferably of Indian origin.”

You people at WIRED—you’re the guilty ones! You support these people, you write about them, you elevate them onto the cover! You really messed it up. I tell you, you pushed this on the American public, right? And people believe it now.

Bill Gates reads you a lot. Who are you writing for?

I have no idea. I just write.

complex adaptive systems, data saving lives, facts & data points, healthcare, policy, rapid learning health systems

Preventing medical error

  • diagnostic errors are the most preventable medical mistakes
  • Automation is part of the solution – sifting through medical records to look for potential bad calls, or to prompt doctors to follow up on red-flag test results.
  • Another component is devices and tests that help doctors identify diseases and conditions more accurately
  • online services that give doctors suggestions when they aren’t sure what they’re dealing with
  • changing medical culture is another approach

Source: http://online.wsj.com/news/articles/SB10001424052702304402104579151232421802264

The Biggest Mistake Doctors Make

Misdiagnoses are harmful and costly. But they’re often preventable

A patient with abdominal pain dies from a ruptured appendix after a doctor fails to do a complete physical exam. A biopsy comes back positive for prostate cancer, but no one follows up when the lab result gets misplaced. A child’s fever and rash are diagnosed as a viral illness, but they turn out to be a much more serious case of bacterial meningitis.

Such devastating errors lead to permanent damage or death for as many as 160,000 patients each year, according to researchers at Johns Hopkins University. Not only are diagnostic problems more common than other medical mistakes—and more likely to harm patients—but they’re also the leading cause of malpractice claims, accounting for 35% of nearly $39 billion in payouts in the U.S. from 1986 to 2010, measured in 2011 dollars, according to Johns Hopkins.

The good news is that diagnostic errors are more likely to be preventable than other medical mistakes. And now health-care providers are turning to a number of innovative strategies to fix the complex web of errors, biases and oversights that stymie the quest for the right diagnosis.

Part of the solution is automation—using computers to sift through medical records to look for potential bad calls, or to prompt doctors to follow up on red-flag test results. Another component is devices and tests that help doctors identify diseases and conditions more accurately, and online services that give doctors suggestions when they aren’t sure what they’re dealing with.

twisted_stethescope

Finally, there’s a push to change the very culture of medicine. Doctors are being trained not to latch onto one diagnosis and stick with it no matter what. Instead, they’re being taught to keep an open mind when confronted with conflicting evidence and opinion.

“Diagnostic error is probably the biggest patient-safety issue we face in health care, and it is finally getting on the radar of the patient quality and safety movement,” says Mark Graber, a longtime Veterans Administration physician and a fellow at the nonprofit research group RTI International.

Big Efforts Under Way

The effort will get a big boost under the new health-care law, which requires multiple providers to coordinate care—and help prevent key information like test results from slipping through the cracks and make sure that patients follow through with referrals to specialists.

There are other large-scale efforts in the works. The Institute of Medicine, a federal advisory body, has agreed to undertake a $1 million study of the impact of diagnostic errors on health care in the U.S.

In addition, the Society to Improve Diagnosis in Medicine, which Dr. Graber founded two years ago, is working with health-care accreditation groups and safety organizations to develop methods to identify and measure diagnostic errors, which often aren’t revealed unless there is a lawsuit. In addition, it’s developing a medical-school curriculum to help trainees improve diagnostic skills and assess their competency.

 

Robert Wachter, associate chairman of the department of medicine at the University of California, San Francisco, says defining and measuring diagnostic errors is an important step. “Right now, none of the incentives for improvement in health care are based on whether the doctor made the correct diagnosis,” Dr. Wachter says. But equally important, he adds, “we need to nurture bottom-up innovation.”

That’s already happening. Large health-care systems are mining their electronic records for missed signals. At the Southern California Permanente Medical Group, part of managed-care giant Kaiser Permanente, a “Safety Net” program periodically surveys its database of 3.6 million members to catch lab results and other data that might fall through the cracks.

In one of the first uses of the system, a case manager reviewed 8,076 patients with abnormal PSA test results for prostate cancer, and more than 2,200 patients had follow-up biopsies. From 2006 to 2009, 745 cancers were diagnosed among those patients—and Kaiser had no malpractice claims related to missed PSA tests.

The program is also being used to find patients with undiagnosed kidney disease, which is often found via an abnormal test result for creatinine, which should be repeated within 90 days. From 2007 to 2012, the system found 7,218 lab orders placed for patients with an abnormal test that had not been repeated. Of those, 3,465 were repeated within 90 days of a notice to patients that they needed a repeat test, and 1,768 showed abnormal results. The majority, 1,624, turned out to be new cases of the disease.

Michael Kanter, regional medical director of quality and clinical analysis, says the system enables clinicians to go back “as far as is feasible to find all of the errors that we can and fix them.”

Because the disease is slow moving, Dr. Kanter says, people with a five-year-old undiagnosed case may not have been harmed. Likewise, with many early prostate cancers, “in many of these cases it doesn’t mean harm would have reached the patient,” he says. “But we don’t want patients not to have the information they should have had through some kind of lapse in the system.”

Dealing With the Flood

Electronic records aren’t a panacea, of course, and can even lead to information overload. In a survey of Veterans Administration primary-care practitioners reported last March in JAMA Internal Medicine, more than two-thirds reported receiving more patient-care-related alerts than they could effectively manage—making it possible for them to miss abnormal test results.

Some researchers suggest the best solution isn’t to flood doctors with information but to provide a second set of eyes to find things they may have missed.

The focus now is preventing dangerous delays in follow-ups of abnormal test results. In a pilot program, researchers at the Houston VA developed “trigger” queries—a set of rules—to electronically identify medical records of patients with potential delays in prostate and colorectal cancer evaluation and diagnosis. Records included charts that had no documented follow-up for abnormal findings suspicious for cancer after a certain period, according to the research team’s leader, Hardeep Singh, chief of health policy and quality at Michael E. DeBakey VA Medical Center in Houston and an assistant professor of medicine at Baylor College of Medicine.

The queries were run on nearly 600,000 records of patients seen at one VA facility in 2009 and 2010. Dr. Singh says the use of triggers, which helped find abnormal PSA tests and positive fecal occult blood tests, could detect an estimated 1,048 instances of delayed or missed follow-up of abnormal findings annually and 47 high-grade cancers.

The VA has funded a randomized trial to test whether an automated surveillance system of triggers can improve timely diagnosis and follow-up for five common cancers.

“This program is like finding needles in a haystack, and we use information technology to make the haystack smaller and smaller so it’s easier to find the needles,” Dr. Singh says.

More health-care systems are also turning to electronic decision-support programs that help doctors rank possible diagnoses by likelihood based on symptoms and notes in the medical record. In a study of one such system, called Isabel, researchers led by Dr. Graber found that it provided the correct diagnosis 96% of the time when key clinical features from 50 challenging cases reported in the New England Journal of Medicine were entered into the system. The American Board of Internal Medicine is studying how Isabel could be linked to assessments of physician skill and knowledge.

Another system, DXplain, developed at Massachusetts General Hospital in Boston, was shown in a study last year to significantly improve diagnostic accuracy among first-year medical residents.

Edward Hoffer, associate clinical professor at Harvard and senior computer scientist at Mass General who leads the DXplain program, says the aim now is to have DXplain “push” diagnostic suggestions to physicians through an electronic-medical-records system rather than requiring doctors to initiate a query, which some are still reluctant to do. “We have to focus our attention on dealing with situations where doctors think they know what the diagnosis is, but they don’t,” Dr. Hoffer says.

Other Avenues

New devices also hold promise for confirming a diagnosis and avoiding unnecessary tests. A number of companies are rushing to provide aids such as portable diagnostic equipment and lab tests that can analyze tiny samples of blood and other bodily fluids quickly to detect disease.

Consider MelaFind, which came to market in the U.S. in 2011. The device allows dermatologists to noninvasively examine moles as deep as 2.5 millimeters beneath the surface to gauge the level of “disorganization,” an indicator of irregular growth patterns that are a sign of melanoma, among the deadliest cancers.

New York dermatologist Macrene Alexiades-Armenakas says she uses MelaFind to confirm that a mole is to be removed and prioritize the level of disorganization in multiple abnormal moles. In some cases, when another doctor or the patient has been concerned about a mole, MelaFind supported “clinical diagnosis of a benign mole, thereby sparing them a biopsy,” she says.

But such devices will never replace a thorough physical exam with a trained eye and careful follow-up, says Dr. Alexiades-Armenakas: “These diagnostic tools are aids to increase our accuracy and adjuncts to good physical diagnosis, not a substitute.”

Some efforts to cut down on errors take a different route altogether—and try to improve diagnoses by improving communication.

For instance, there’s a push to get patients more engaged in the diagnostic process, by encouraging them to speak up about their symptoms and ask the doctor, “What else could this be?” At Kaiser Permanente, a pilot program provides patients with a pamphlet that encourages them to think about and write down their symptoms and what concerns or fears they have, encouraging them to ask specific questions to be sure they understand their diagnosis and the next steps they must take.

Medical schools, meanwhile, are teaching doctors to be more receptive to patient input and avoid “anchoring,” the habit of focusing on one diagnosis and excluding other possible scenarios, and “premature closure,” not even considering the correct diagnosis as a possibility.

The Critical Thinking program at Dalhousie University in Halifax, Nova Scotia, established last year, aims to help trainees step back and examine how biases may affect their thinking. Developed by Pat Croskerry, a physician known for his research on the role of cognitive error in diagnosis, it uses a list of 50 different types of bias that may lead to diagnostic error.

The program is being integrated throughout four years of the medical school. Students study cases such as a psychiatric patient with shortness of breath who was assumed to be merely having an anxiety attack; doctors overlooked that she was a smoker on birth-control pills, a risk for the blood clot that later traveled to her lung and killed her.

“If we can teach physicians how to think more critically,” Dr. Croskerry says, “they would be more effective in delivering good care and arriving at the right diagnosis.”

Ms. Landro is an assistant managing editor for The Wall Street Journal and writes the paper’s Informed Patient column. She can be reached at laura.landro@wsj.com.

complex adaptive systems, data saving lives, entrepreneurship, healthcare, healthy habits, musings, nutrition, policy, quantified self, rapid learning health systems

Because in health, less is more…

When we look back at contemporary health systems 50 years from now, we will consider them to be an technologically indulgent folly of grand proportions, driven by an imperative to deliver more and more complex care in order to justify higher and higher costs.

In a fee-for-service context, elaborate technologies justify higher costs. An elective angiogram costs $25,000. If this had to be paid by individuals, there would be no interest in conducting them with the frequency that they are performed today.

Perhaps this is why Singapore, with its health savings accounts with health costing around 4% of GDP (achieving the same high outcomes of Australia), lacks the excesses of more universal health systems?

The use of bariatric surgery for obesity is perhaps the most egregious example of this phenomenon. A AU$20,000 – 30,000 procedure is now introducing moral hazard that will undermine attempts to introduce behavioural and lifestyle change i.e. “Why bother changing my lifestyle when I can simply get a lap band to fix me later?”

Pharmaceutical companies are also using this play book with the introduction of their new, highly-specialised, so-called “biologics” to the market, particularly in the cancer area. They are often protein based and extremely difficult to manufacture, but are also very targeted. Funders are responding to this threat with value-based payment schemes where by the drug company only gets paid if the treatment succeeds.

Current health market settings establish this perverse incentive. Moves to value/outcomes-based care will remedy these perversities, providing incentives for activities that reduce care costs. In such an environment, the cheapest interventions also become the most profitable.

Home delivered broccoli instead of lap-bands.

CBT SMS’s instead of SSRIs and psychotherapy.

A rapid learning health system instead of a profit yearning sickness market.