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Tag: FutureMed

Free Medical School?

UC Riverside Medical Research Building RS

One of the most compelling medical stories in the country is unfolding within the sprawling landscape of inland Southern California. The story centers on the University of California, Riverside School of Medicine where G. Richard Olds, MD, the school’s dean, is taking on one of the uber challenges in health care today: How to get doctors into areas significantly underserved by health care professionals.

The UC-Riverside School of Medicine is in its infancy having welcomed its first class of 50 students just last year. But it has embarked on an innovative program fueled by a passion not only to get doctors into geographic areas where they are most urgently needed, but also to make sure these physicians practice specialties most in demand. “There are 18 new medical schools in the United States and the vast majority are just like existing medical schools,” says Dean Olds. “We are substantially different than most other new schools. We are designed around a unique mission – to try and address the health workforce needs of inland Southern California. We need to train health care professionals who come from backgrounds and communities they will be taking care of.”

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The Data Response Curve (In Honor of the Dose Response Curve)


Data Response Curve

All medical students learn about the dose response curve in pharmacology lectures. The dose-response curve informs us of how we should dose a medication in the context of its efficacy and its toxicity. Too little medicine won’t have the desired effect, and too much medicine can be toxic.

In the era of digital health, data have become the new “big pharma,” and we are facing the emergence of a data-response curve in which access to too little data is inactionable, and access to too much data can be overwhelming. Digital health devices abound today, and has enabled quantification of nearly every health and wellness metric imaginable. Sadly, in our exuberance about these new sources of data, we often conflate “more data” with “better data.”

In the era in which data have become the booming commodity of exchange in healthcare, we describe an emerging data-response curve. Large data sets can be at best clarifying or at worst self-contradictory. Too little data on the data-response curve, as with medication dosing, can be insufficient for effective action or decision-making. Too much data can be toxic to the user such as the physician, leading to poor decisions or worse, to analysis paralysis.

We live in a world of exploding data, and we need to be thoughtful. Medicine is a people business in need of data, not a data business on need of people. In reductive form, all humans make decisions based on inputs (data) from their environment and on individual analysis of the data in the form of non-linear, non-quantifiable perception. When we as doctors, policy-makers, or simply as human beings receive these inputs, one of three things happens: 1. We make a decision to do something (for example a treatment decision based on abnormal data), 2. We make a decision to do nothing (for example, normal data which we believe requires no action), or 3. We need more data in order to make an informed decision to do item #1 or item #2. More does not necessarily equal better data. More data is simply more.

Better data are actionable data wrapped in the context of the patient and the patient’s condition. Imagine each piece of objective data connected to concurrent subjective data, and surfaced in the context of a specific condition relevant to the patient. HealthLoop enables patients to generate contextual objective data married to their subjective symptoms and served to a clinician in an actionable context. High signal and low noise are the digital health equivalents of on the dose-response curve of a favorable therapeutic window.

See where some folks live on the Chart. Where do you live?

Robots Are Coming and They Plan to Treat You like a Moron

Robots are coming
People hate to hear it, but the robots are coming and it’s only a matter of time before they start competing for skilled, white collar jobs.

Nurses are vulnerable –but before you get excited and start attacking me– so, too are consultants and bloggers. So get used to it, and figure out how you’re going to co-exist with and leverage the bots.

One of my pet peeves about robots is when their programmers try to make them act human by intentionally making them imperfect or have them simulate (feign?) empathy.

For example, I can’t stand it when the voice recognition airline rep talks in a sympathetic sounding voice when “she” can’t understand what I’m saying.

But apparently we’ll be seeing more of these little “humanizing” tricks, thanks to research from MIT that concludes that people like this kind of stuff. From the Wall Street Journalwe learn:

  • People like their therapy robots to be baby-faced
  • We feel emotionally closer to robots that sound like our own gender
  • When robots mimic our activity (like folding their arms) we like it
  • And then there’s this one:

“One study showed that people rated online travel booking and dating services more positively when the service communicated clearly that it was working for the consumer (e.g., “We are now searching 100 sites for you”) than when they simply provided search results. Surprisingly, having to wait 30 seconds for results but also receiving this communication of effort slightly increased users’ satisfaction, compared with receiving results instantaneously. Being made aware of the website’s willingness to work on their behalf made people feel that the service was sympathetic to their needs.”

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Download Two of These And Call Me In the Morning

Manpo-Meter Take 2
When it comes to discussing exercise with friends, family and patients, it seems that many of us are at a loss for words. What kind of exercise should we recommend? How much exercise is enough? How much is too much? How do I know that my patient is actually exercising? How do I prescribe exercise?

According to the U.S. Department of Health and Human Services, U.S. adults should engage in moderately intense physical activity for a minimum of 150 minutes each week; this is equivalent to 30 minutes a day, 5 days per week [1]. While it is relatively easy to keep track of the duration and frequency of exercise, it is much more difficult to quantify the intensity of an activity, let alone ensure that the activity is “moderate” for the entire 30 minutes.

In fact, in a 2008 study of women’s understanding of “moderate-intensity” of physical activity as presented in the popular media, the authors found it is not enough to simply hear and read a description of physical activity, but that it requires practice [2].

So, what are we to do? Should we have our patients log their daily activities? Should we have our patients show us sign-in sheets from the local gym?

It turns out that the dilemma of how to quantify physical activity has been a hot topic for more than 50 years. In 1965, a Japanese inventor developed the first pedometer to give people the opportunity to meet measurable goals and, thus, increase their physical activity. The device was called the Manpo-Kei (meaning “10,000 steps meter”) and it was based on research by Dr. Yoshiro Hatano that demonstrated that 10,000 steps per day allowed for a proper balance between the traditional Japanese caloric intake and the activity-based caloric expenditure of walking approximately five miles per day (the average person’s stride length is approximately 2.5 feet long, therefore 2,000 steps/mile) [3].

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If Marketing Is so Dangerous, Should Medical Schools Be Doing so Much of It?

flying cadeuciiBeginning about 5 years ago, many US medical schools introduced severe restrictions on marketing activities by pharmaceutical companies and medical device manufacturers.

These measures often prohibited representatives of such firms from entering patient care areas and even medical school facilities, with the exception of tightly controlled training activities, and then by appointment only.  In some cases, medical schools have issued outright bans against industry support of educational activities.

What is the rationale behind such actions?  It boils down to a concern that industry funding may inappropriately influence both medical education and patient care.  For example, a physician visited by an industry representative might be more likely to prescribe one of the firm’s drugs.  In announcing a ban on such activities, one school likened the industry to Don Juan, worrying that physicians might prescribe drugs because they were “seduced by industry,” and not because “it’s best for the patient.”

There is evidence that even physicians who believe their decision making is not biased by marketing are in fact affected by it.  Moreover, a good deal of such marketing is not exactly purely scientific.  A perusal of medical journals reveals a plethora of full-page ads featuring slogans such as:

“Simplicity is clear information at your fingertips,” and highlighting images such as a physician walking down a hallway with a tiger, describing the featured drug as a “powerful partner.”

Such marketing is not inexpensive.  Placing a full-page ad in a medical journal typically costs around $4,000.  On the other hand, as an air traveler I have come across a number of slick full-page airline magazines ads touting medical schools and their affiliated hospitals.

These cost on average $24,000.

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Why the Phrase “Noncompliant Patient” Bothers Me, And Should Probably Bother You Too ..

Screen Shot 2014-05-23 at 3.19.04 PM

“Patient noncompliance.” I wasn’t very familiar with this term until I started my clinical rotations. But after just the first week, I started noticing that health care providers throw this phrase around all time.

We particularly like using it as an excuse. Why did this diabetic patient require a foot amputation? Why does this patient come in monthly with congestive heart failure exacerbation? Why did this patient suffer a stroke? It’s often simply attributed to patient noncompliance.

What bothers me the most about this phrase, though, is how it’s often stated with such disdain. We act as if it’s incomprehensible that someone would ignore our evidence-based recommendations. If the patient would only bother to listen, he or she would get better. If we were patients, we would be compliant.

But that’s simply not true. We are no different from our patients. We practice our own form of noncompliance. It’s called guideline non-adherence.

Despite the fact that many guidelines are created after systematic reviews and meta-analyses – processes we would never have time to go through ourselves – we, like our own patients, are often noncompliant.

Research on guideline adherence has been around since guidelines started becoming prominent in the early 1990s. Despite the many studies and interventions to improve guideline adherence, the rates of guideline adherence still remain dismally low.

I find this particularly disconcerting. Despite my own interest in research, it makes me question the value of research. Why do we spend millions of dollars to find a better intervention that does not change how most providers deliver health care?

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Another Step toward Open Health Education

Osmosis Screen

Earlier this month Shiv and Ryan published a piece in the Annals of Internal Medicine, entitled What Can Medical Education Learn from Facebook and Netflix? We chose the title because, as medical students, we realized the tools our classmates are using to socialize and watch TV use more sophisticated algorithms than the tools we use to learn medicine.

What if the same mechanisms that Facebook and Netflix use—such as machine learning-based recommender systems, crowdsourcing, and intuitive interfaces—could transform how we educate our health care professionals?

For example, just as Amazon recommends products based on other items that customers have bought, we believe that supplementary resources such as questions, videos, images, mnemonics, references, and even real-life patient cases could be automatically recommended based on what students and professionals are learning in the classroom or seeing in the clinic.

That is one of the premises behind Osmosis, the flagship educational platform of Knowledge Diffusion, Shiv’s and Ryan’s startup. Osmosis uses data analytics and machine learning to deliver the best medical content to those trying to learn it, as efficiently as possible for the learner.

Since its launch in August, Osmosis has delivered over two million questions to more than 10,000 medical students around the world using a novel push notification system that syncs to student curricular schedules.

Osmosis is aggregating medical school curricula and extracurricular resources as well as generating a tremendous amount of data on student performance. The program uses adaptive algorithms and an intuitive interface to provide the best, most useful customized content to those trying to learn.

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The End of Antibiotics. Can We Come Back from the Brink?

Tom Frieden CDCAntibiotic resistance — bacteria outsmarting the drugs designed to kill them — is already here, threatening to return us to the time when simple infections were often fatal. How long before we have no effective antibiotics left?

It’s painfully easy for me to imagine life in a post-antibiotic era. I trained as an internist and infectious disease physician before there was effective treatment for HIV, and I later cared for patients with tuberculosis resistant to virtually all antibiotics.

We improvised, hoped, and, all too often, were only able to help patients die more comfortably.

To quote Dr. Margaret Chan, Director General of the World Health Organization: “A post-antibiotic era means, in effect, an end to modern medicine as we know it.”

We’d have to rethink our approach to many advances in medical treatment such as joint replacements, organ transplants and cancer therapy, as well as improvements in treating chronic diseases such as diabetes, asthma, rheumatoid arthritis and other immunological disorders.

Treatments for these can increase the risk of infections, and we may no longer be able to assume that we will have effective antibiotics for these infections.

Last September, CDC published our first report on the current antibiotic resistance threat to the United States.

The report conservatively estimates that each year, at least 2 million Americans become infected with bacteria resistant to antibiotics, and at least 23,000 die.  Another 14,000 Americans die each year with the complications of C. difficile, a bacterial infection most often made possible by use of antibiotics. WHO has just issued their report  on the global impact of this health threat.

It’s a big problem, and one that’s getting worse. But it’s not too late. We can delay, and even in some cases reverse the spread of antibiotic resistance.

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Should Medical Schools Teach to the Boards?

flying cadeuciiIn the 2012 National Residency Match Program Survey, which is sent out to residency program directors around the country by the NRMP, the factor that was ranked highest with regards to criteria considered for receiving an interview—higher than honors in clinical clerkships, higher than extracurricular experiences or AOA election, and even higher than evidence of professionalism, interpersonal skills, and humanistic qualities—was the USMLE Step 1 score.

When considering where to rank an interviewed applicant, the Step 1 score took a backseat to some of the aforementioned criteria that are perhaps more telling of what kind of person the interviewee is, although it was still one of the highest considered criteria for ranking applicants as well.

When a single exam is given this level of importance in determining a future physician’s most critical period in career development—their residency—we have to look carefully at our system.

Two points of consideration come to mind. First, is it wise to weigh a test score so heavily? Many students and faculty could easily point out that student performance on exams by no means always reflects their clinical acumen and social skills when seeing patients.

Medicine is, after all, an art far more than a science.

Nonetheless, it would be foolish to assume that scores have no worth—a high score on an exam, particularly a behemoth such as the USMLE Step 1, points out many qualities in an individual: hard work, persistence, discipline, and frankly, an understanding of textbook medicine.

And thus, we are left somewhere in the middle—perhaps we should weigh scores less than we do, but when you have to sort through thousands of applications, the only standardized metric to quickly compare is, in the end, a number somewhere between 192 and 300.

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Moore’s Law in Healthcare – Three Predictions

apple storeJe n’ai fait celle-ci plus longue que parce que je n’ai pas eu le loisir de la faire plus courte. —Blaise Pascal

Translation: I have made this longer than usual because I have not had time to make it shorter.

As Appley as it gets.

A while ago I was challenged to write about what an Apple-like approach to healthcare might look like.

That challenge has been weighing on me.

For starters, we’re all over Appled aren’t we? Maligned anecdotes about Steve Jobs and the iPhone make their way into almost every presentation remotely related to innovation or technology. Triteness aside, I’ve been stalled because Apple is really a philosophy, not a series of steps or lessons learned. (Although, they are nonetheless methodical.)

Instead, what I’ve been kicking around in the ole noggin are three notional predictions, which I’ll assert are inevitabilities which will fundamentally disrupt healthcare delivery as we know it today.

What follows is about as Appley as I’m likely to get. Despite big-bang product launches, Apple actually plays the long game. They introduce small features into products to affect user behavior years before a flagship product takes advantage of those reprogramed behaviors.

That’s how they disrupt.

I believe there are three meaningful, unstoppable trends, in our current world which will significantly alter healthcare. The steps taken towards these inevitabilities, along the way, are what will define the innovators and leaders. They are the ones who see this future and know how to drive towards it.

The three trends are:

  • Tools and culture which favor individual empowerment
  • The commoditization and automation of diagnosis
  • Accelerated globalization of treatment options

But wait, there’s Moore.

Don’t worry, I’m not going to leave you hanging. I’ll attempt to rationalize each of these points and explain why, particularly when considered as a bundle, they are a powerful force for disruption. And to prime that pump, we have to talk about Gordon Moore.

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