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Summary:

Two Indiana University researchers have developed a computer model they say can identify significantly better and less-expensive treatments than can doctors acting alone. It’s just the latest evidence that big data will have a profound impact on our health care system.

A pair of Indiana University researchers has found that a pair of predictive modeling techniques can make significantly better decisions about patients’ treatments than can doctors acting alone. How much better? They claim a better than 50 percent reduction in costs and more than 40 percent better patient outcomes.

The idea behind the research, carried out by Casey Bennett and Kris Hauser, is simple and gets to the core of why so many people care so much about data in the first place: If doctors can consider what’s actually happening and likely to happen instead of relying on intuition, they should be able to make better decisions.

In order to prove out their hypothesis, the researchers worked with “clinical data, demographics and other information on over 6,700 patients who had major clinical depression diagnoses, of which about 65 to 70 percent had co-occurring chronic physical disorders like diabetes, hypertension and cardiovascular disease.” They built a model using Markov decision processes — which predict the probabilities of future events based on those immediately preceding them — and dynamic decision networks — which extend the Markov processes by considering the specific features of those events in order to determine the probabilities. Essentially, their model considers the specifics of a patient’s current state and then determines the best action to effect the best possible outcome.

Credit: Indiana University

Credit: Indiana University

Specifically, Bennett and Hauser found via a simulation of 500 random cases that their model decreased the cost per unit of outcome change to $189 from the $497 without it, an improvement of 58.5 percent. They found their original model improved patient outcomes by nearly 35 percent, but that tweaking a few parameters could bring that number to 41.9 percent.

It’s not surprising that anyone would think computers and data analysis could be a boon for the health care system:

Furthermore, at Structure: Data on March 20, I’ll be discussing the marriage of big data and health care with Aetna innovation head Michael Palmer.

However, no one (or very few people, at least) suggests that Watson or any computer model can or should replace physicians’ judgment. What they can do, though, is digest quantities of research and case studies that no single human being could, meaning they can take a lot more information into account when computing possible outcomes and treatments.

So, although we won’t hear “Paging Dr. Watson” at the hospital anytime soon, there’s an increasingly high chance our doctors will retire to their offices with our charts and ask a computer system of some sort what might be wrong with us and how they might best fix it.

Feature image courtesy of Shutterstock user Luis Louro.

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  1. isn’t a physicians judgement just that a compilation of data that leads to diagnostics & a decision. i don’t want to hear any person tell me they can process information faster than a computerized data base. the best physicians of the future will be robotic and the future should be happening as soon as possible.
    slayerwulfe cave

    1. You can imagine a world where robots are emergency room docs and surgeons? That level of sophistication in a robot to be able to see a bleed suture it etc… I would be extremely impressed if this was feasible in the next 20 years.

      1. In the next 20 years regular physicians will be using these tools more and more to make intelligent decisions about treatments. There’s nothing that can replace a human intuition and there’s nothing that rival the learning capacity of a good machine learning algorithm. These two are a natural fit for each other. In the next 20 years the importance of the actual doctor diagnose will decrease. Also in the 20 years we will see a huge decrease in the number of people who aggregate information as their occupation (such as the lowly paralegal will be a thing of the past).

      2. In the next 20 years regular physicians will be using these tools more and more to make intelligent decisions about treatments. There’s nothing that can replace a human intuition and there’s nothing that rival the learning capacity of a good machine learning algorithm. These two are a natural fit for each other. In the next 20 years the importance of the actual doctor diagnose will decrease. Also in the 20 years we will see a huge decrease in the number of people who aggregate information as their occupation (such as the lowly paralegal will be a thing of the past).

    2. Hi SlayerWulfe.

      I agree with you on the notion that a physician’s judgment must, of course, be based on data. However, you should know that while computers are very good at some tasks (such as recursive calculation) they are very poor at others (e.g., pattern recognition) owing to the nature of how computers work (they are very good at doing one thing; one at a time). Computers have a hard time with multiple constraint satisfaction (again, this is why pattern recognition eludes computers) which I imagine is one thing physicians, for now, have the upper hand in.

      For more information, look into topics pertaining to cognitive science.

      1. Joe, I am going to have to disagree with you there. There is no inherent reason a reasonably parallel neural network (such as IBMs watson) cannot utilize an ensemble of modern machine learning techniques to perform intelligent pattern recognition much faster than the human mind. Although these algorithms are not as flexible as our native networks, a physician’s job is mostly reliant on Bayesian inference algorithms. Therefore, such systems are actually better suited toward diagnostics than humans in many (though not all) cases.

      2. Reaz Mohmed, E.I.T Joe Tuesday, February 12, 2013

        Pattern recognition ? In February 2011, IBM proved that computers can also recognize patterns, by demonstrating the Watson Supercomputer, which recognizes patterns in text data to surpass the capabilities of the human mind. Dude … research.

  2. i am concerned that in some ways we R still in the dark ages. in the future we will trust tech. more, even with R lives. it has no ego it makes no mistakes outside of programming, lasers R utilized, scanning R bodies with ultra sound etc.because we appreciate & trust the precision of R tech. and we trust in it every day.

    1. You left your English in the dark ages.

    2. R you sure you R not a programmer? :)

      1. Guybrush Threepwood srynobio Tuesday, February 12, 2013

        or R you a pirate? RRRRRRRRRRRRRR

      2. The R programming language. It’s popular among data scientists.

  3. My recent experience would have been faster and better diagnosed by a computer. Too many egos and not enough listening got in the way of a diagnosis. Two separate doctors told me I didn’t have what lab tests proved I did. They might have also been helped by Kaizen. Not enough asking why.

  4. You know whats really funny? We could have rolled this technology out years ago with the proper allocation of funds.

    1. Let the private sector “roll” it out.

      My interest in being monitored and probed by a government robot is even less than what the IRS, the Census or other 3-letter government agencies do now.

  5. Looking forward to what this can do to reduce healthcare costs in the future.

  6. I am a little confused by this article. So, these guys build a system to predict behavior and decision. Then, they used a simulation to test their own system. Isn’t that a bit self serving? This model of theirs isn’t actually used to treat patients, just simulated patients….I might be wrong, but somehow, I think a human body doesn’t always react the same as a simulation.

    Frankly, I think this is a pretty invalid comparison. Until such a day a program can be actually used to make all the clinical judgement instead of a doctor, you simply cannot compare the effectiveness of either.

    1. This article doesn’t give enough information to conclude that it’s an invalid comparison. I don’t know what they did, but I can give a little information about how some machine learning systems are trained. What is often done (and likely done in this case), is they compiled a large amount of real patient data, and then split it into a training set and validation set. The training set is used to train (duh) the network, and then the validation set is used to judge the systems efficacy. So they never had to create fake people and mock illnesses, they could have easily used real information, that they network had never seen.

  7. Maybe some physicians and doctors are purposefully prescribing incorrect/costly treatment so that they earn more money.

    1. They are a business after all. They are not in it to lose repeat customer; I think they prefer the trial and error approach to one that is more precise and provides an improved successful treatment. Isn’t it odd that Forbes published an article on why it is not a good idea for physicians to be rated on the level of care they provide ?

      1. Even better than giving doctors access to these technologies is giving us patients access to it so we can double check the work of the doctors.

  8. I’ve had too many doctors misdiagnose serious conditions on me, including Crohn’s disease as well as a punctured lung.

  9. I should also add, those misdiagnoses could have been resolved with proper analysis of the data at hand. I had a doctor that did not treat a stricture despite it being quite evident. The doctor was too wrapped up in his ego to care and too busy accusing me of drug seeking when in fact I needed surgery for an extremely painful condition.

    The ERs in the world also need all the help they can get. A computer giving a preliminary diagnosis would go a long way in getting people the help they need quickly. Or at least, getting them some relief while the doctors / computers sort out their health issues.

    1. so how did you end up finding out about the stricture/crohns?

  10. Amazing

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