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Can We Crowdsource Medical Expertise I'm not sure if she heard me on the radio or came across crowdsourcing in some other way, but she raises an issue I've been wanting to dig into ever since publishing the original crowdsourcing article over two years ago: To what degree could the crowd lend its brainpower to the process of, say, diagnosing or suggesting treatments for diseases? One is tempted to dismiss this notion out of hand.

Let the crowd count birds, develop cell phone applications, even create a new restaurant. But keep them away from my MRI scans. This is a pretty understandable reaction, and I've louis vuitton shoes size 7 tended to view attempts to crowdsource the professions (law and medicine, namely) with considerable skepticism. But given the poor quality of much of the healthcare in the United States, to say nothing of the developing world, could the crowd really make so big a mess of things? Here's Maynard:Crowdsourcing would work for taking CT and MRI reading out of the hands of [radiologists] and into the hands of individuals who have become medical experts in pursuit of their own elusive diagnoses. Radiologists read scans in a couple of minutes, referring to any previous scans in hospital records which are pulled up as soon as social is entered, and simply note differences, if any. They have clues, from doctors "reason for request" which is their loophole to NOT closely examine a scan. The technology is wonderful. The vast majority of specialists refuse to do "exploratory" despite their patients desperate attempts to get relief from agony and, hopefully, live, because of the state of the art. "If there was a problem, we would have seen it," they say. Yet failure to find a problem, or five different interpretations, none hitting the mark, is the norm, resulting in no treatment or mistreatment. The missing ingredient is better interpretation of diagnostics, which could be accomplished by crowdsourcing. Ideally the demographic without borders would be louis vuitton hats amazon any reasonably intelligent person who has been on a medical merry go round with no help proffered, and who has resorted to examining and interpreting, for months, maybe years, their own scans. I don't know if missing the mark exactly the norm, but it's certainly a frequent occurrence. (Full disclosure: Our son had had two MRIs by the age of six months. The readings, by separate radiologists, contradicted each other and neither was conclusive). Without going into the personal details of her story, Maynard has endured an extraordinary range of interpretations, as she says. While I would never advocate going to the masses for radiology (this would, clearly, be ridiculous), this isn't quite what Maynard implies. Why not have an informed group of people some might even be radiologists, or MDs in other fields reviewing scans that were posted online. I fear that Maynard is right that overworked professionals have little time and little incentive to pour carefully over MRI and CT scans. If this particular crowd of semi professionals what Scott Page, the U. Michigan collective intelligence brillionaire I lean on in the crowdsourcing book, might call a "crowd of experts" was willing to act as a fact check back up resource, why not tap them? I'm getting a lot of additional traffic today due to all those afore posted radio gigs. So I put the question to you, and them: Would you trust the crowd to help analyze your medical data? (Ed's Note: Written on the fly between 25 radio interviews (we had two cancellations) and one Red Sox/Yankees game. Forgive mistakes and correct me in comments.) Pre correction correction: Scott actually calls this a "crowd of models," in his excellent book, The Difference, I believe. I've taken liberty with his terminology. I would definitely trust the crowd for medical advice and interpretation. If the crowd is big enough, I would even venture to drop the requirement for "expert" credentials. Why not let everyone comment but have ratings or credibility indicators for commenters that either have expert credentials or have been rated highly as having provided a large number of useful/accurate comments on other people medical tests?Congrats on your book! Can wait to read it. As a former healthcare researcher and as founder of InnoCentive, I appreciate the question raised by Maynard and in this post. It a meaty one. Of course, it goes without saying that many of the overall healthcare process (including research objectives) can and should be crowdsourced for a host of reasons that would improve outcome and quality. The specific issue of crowdsourcing diagnosis or treatment is far less clear, but a look at some actual calculations might be informative. An expert (say, right 95% of the time) is wrong 5% of the time. An amateur might be wrong 20% of the time, but the chance that two amateurs are both wrong is only 20%x20% or 4%. So two "informed" amateurs consistently reading a scan or collection of lab results has a pretty good record. Hmm, seems like a clear case FOR the crowd. Of course, as the number of semi professionals or informed amateurs goes up, the chance of them ALL being wrong goes down, but the chance of getting mixed diagnoses goes up very fast. (73% say "benign" and 27% say "malignant.") What to do then? Majority rules? Supermajority required? When is the "vote" compelling enough to stake your treatment on it? It would be well outside the scope of a blog comment to delve deeply into this. But let briefly return to our two amateurs. When they agree there is a 96% chance of them being right. But how often do they agree? If they are looking at a cancerous scan, with an 80% individual accuracy rate, they agree on the cancer diagnosis only 64% of the time. They split opinions (a very confusing state of affairs since they are equally likely to get it right and now you don know who to believe) 32% of the time (that a lot) and they both get it wrong only 4% (as we said already). There may well be some sophisticated statistical analyses that would supplement such crowdsourcing approaches BUT or or of experts, there will remain ambiguity when dealing with judgement calls. Our penchant for certainty is just not going to get fully louis vuitton small ring agenda illustre satisfied. Total non experts (the masses referred to in the post) do NOT help matters louis vuitton purses uk as their input is just noise obscuring a signal. But the crowd of semi experts could well be, in my opinion, desirable, and we should investigate appropriate systems and knowledge aggregation tools for its exploitation. but not to be treated over simply. (caveat: even this little treatment is over simple as it has failed to consider independently the error rates for alpha errors and beta errors (often not the same, quantitatively or consequentially) or correlated errors, as well as other factors. but you get the basic idea.) I seen various medical bloggers post mystery x rays and other scans on their blogs and then ask readers to the diagnosis (sometimes they also comment on the prognosis). Although I not a physician, nurse, PA, or other clinical professional, I do sometimes guess and post a reply in the comments. But these comments aren in any way connected back to the person in the scan, or the clinical evaluation and/or treatment they received as a result. This section of your post jumped off the screen: "I fear that Maynard is right that overworked professionals have little time and little incentive to pour carefully over MRI and CT scans." I wonder if blog readers participate in crowd sourcing findings on posted films because this is currently almost a form of clinical rather than the work this would morph into with a site dedicated to doing this? However, as an interesting business model example, you could certainly look at a site/service like that of American Well, where radiologists could join (from all over the world), have licensure/credentials checked, and then be paid to read scans whenever they had time available. Remote radiology firms do this sort of thing now.

Thanks for the thought provoking read! Why do we go to the doctor or get a diagnostic test? It to learn something about our bodies and then make a decision based on that result. All of us want to maximize the odds of health and minimize the odds of suffering. When it comes to getting a diagnostic test, there are three variables how good is the test itself, how good is the interpretation of the test, and how good is the doctor diagnosis based on all the information available to them.

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