RAND Health Insurance Experiment

[I finally begin to post on the "Hansonian" view of medicine, mentioned here, here, here, here.]

How useful is medicine, to the average person, wondering if he should go to the doctor or skip it?  We have perhaps a million medical studies, but how do we combine them into a total estimate of the value of medicine?  It is hard to see how to correct for many potential biases such as fraud, funding bias, treatment selection bias, publication selection bias, and so on. 

These biases can be partially overcome by focusing on studies of the aggregate effects of medicine on the general population, some of which compare millions of people over years.  Such studies usually find no health effect of more medicine, but most are correlation studies, so one may doubt if they controlled for enough relevant factors.  Fortunately, there has been one large randomized experiment on aggregate medicine.

If you remember only one medical study, it should be the RAND health insurance experiment, where from 1974 to 1982 the US government spent $50 million to randomly assign 7700 people in six US cities to three to five years each of either free or not free medicine, provided by the same set of doctors.   The plan was to compare five measures of general health, and also 23 physiologic health measures.  From their expanded 1983 New England Journal of Medicine article:

For the average person enrolled in the experiment, we observed two significant positive effects of free care relative to cost-sharing: corrected far vision … was better by 0.1 Snellen lines (p = 0.001) and diagnostic blood pressure was lower by 0.8mm HG (p = 0.03).   For the remaining measures … any true differences would be clinically and socially negligible.  For the five general health measures, we could detect no significant positive effect of free care for persons who differed by income .. and by initial health status.  … Among participants who were judged to be at elevated risk with respect to smoking habits, cholesterol levels, and weight, free care had no detectable effect.  … For persons who were in the upper quartile of the distribution of risk factors included in the risk of dying index, the risk of dying was 10 percent lower on the free than the cost-sharing plans (p = 0.02). 

It has long been obvious that eyeglasses help people see better, and eyeglasses are basically physics, not "medicine," so that result should be set aside.  Since this experiment looked at thirty measures in total then just by chance one of them should seem significant at the three percent level, explaining the blood pressure result.  The "risk of dying index" effect is mainly just the blood pressure effect, and the index came from a 1976 paper on heart attack risk, which was chosen well after the RAND experiment started, so the statistical significances reported for that clearly did not correct for data mining.

The bottom line is that thousands of people randomly given free medicine in the late 1970s consumed 30-40% more medical services, paid one more "restricted activity day" per year to deal with the medical system, but were not noticeably healthier!  So unless the marginal value of medicine has changed in the last thirty years, if you would not pay for medicine out of your own pocket, then don’t bother to go when others offer to pay; on average such medicine is as likely to hurt as to help.

Why is this shocking news unknown to most readers of the weekly health section of the newspaper?  More tomorrow on the RAND experiment. 

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  • Chuck

    I don’t think that’s quite what they conclude.

    Here’s a paper written by two profs from U. of Chicago that summarizes the RAND study and other studies as well.

    A few quotes:

    If you are talking about whether or not the people currently not covered by health care would benefit from it, I think the answer is yes…

    “Another lesson from this literature is that the size of the effect of health insurance on health depends very much on whose health we are talking about. Vulnerable populations such as infants and children on the fringes of Medicaid eligibility or low-income individuals in the RAND experiment have the most to gain from more resources, and do appear to benefit from them.”

    Furthermore, when you say, “These biases can be partially overcome by focusing on studies of the aggregate effects of medicine on the general population, some of which compare millions of people over years. Such studies usually find no health effect of more medicine, but most are correlation studies, so one may doubt if they controlled for enough relevant factors. Fortunately, there has been one large randomized experiment on aggregate medicine.” you again seem to be contradicted here…

    “The results of small quasi-experimental studies provide only mixed evidence that health insurance affects health, while larger quasi-experimental studies and the RAND Health Insurance Experiment provide consistent evidence that health insurance improves health. Only one large-scale quasi-experimental study (Perry and Rosen) fails to show a relationship between health insurance and health, and this study may not have adequate power to rule out the possibility that health insurance improves health. Taken as a whole, these high-quality studies of the health effects of health insurance strongly suggest that policies to expand insurance can also promote health.”

  • Stuart Armstrong

    More tomorrow on the RAND experiment.

    It’s fascinating, and I’m eagerly awaiting the rest.

    One issue (that is often touched upon in the weekly health section of the newspaper) is given by the line in the study “Confidence intervals were wider for subgroups of persons with low income or initially in poor health; therefore we cannot rule out clinically meaningful changes in particular subgroup”. Have they done further studies to clear up that issue?

  • michael vassar

    Technically, if you would not pay out of pocket for medicine *if it was offered at 1970s prices and with 1970s quality* you shouldn’t use it if someone else is paying. However, healthcare price has gone WAY up relative to median income and quality has also probably risen, so a this modifier is relevant.

  • Stuart Armstrong

    Ah, thanks Chuck, you answered my question before I asked it. Just to be sure – “more resources” means free or lower cost health insurance?

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Chuck, I am talking about our actual data, not about commentary from “two profs from U. of Chicago.” My post above shows the inaccuracy of the claim you quote, that “RAND Health Insurance Experiment provide consistent evidence that health insurance improves health.”

    Michael, that very sentence includes a modifier. Yes, total quantity has gone up. But if the ratio of helpful to harmful medicine has not changed, for medicine that price subsidizes induce folks to consume, the claim stands.

  • Chuck

    “Chuck, I am talking about our actual data, not about commentary from “two profs from U. of Chicago.” My post above shows the inaccuracy of the claim you quote, that “RAND Health Insurance Experiment provide consistent evidence that health insurance improves health.”"

    The paper from the University of Chicago (link might have been stripped or I forgot to include it, I’ll try to include it again) is by Helen Levy and David Meltzer. Both have PhD’s in economics, one from the University of Chicago and the other from Princeton, and also various other degress from Yale, etc, in economics and health. Metzler is also an MD.

    Their paper is titled “WHAT DO WE REALLY KNOW ABOUT WHETHER HEALTH INSURANCE
    AFFECTS HEALTH?” which sounds very relevant. Hopefully the link came through below.

    These two educated specialists in this field are commenting on the same data as you in a scholarly article and seeming to reach different conclusions.

    It seems to me worthy of meaningful reply.

    I wonder, for example, if the *average* person in the quote you cited is average for the study, or average for the population as a whole? Furthermore, what is the distinction between “free care vs. cost sharing”? Are we comparing two groups of people who have coverage, but it is paid for in different ways? I was under the impression we were comparing people without insurance to people with insurance. Perhaps that is the basis of the different conclusions?

    www!umich!edu/ %7Eeriu/ pdf/ wp6.pdf

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Chuck, the paper you cite cites the blood pressure result I mentioned, but notes “One caveat is that the analyses do not control for the presence of multiple comparisons (that is, hypothesis tests for multiple health outcomes).” That is, they are aware of but just choose to ignore the fact that we should have expected some such result by chance.

  • Stuart Armstrong

    Robin, not to dispute your overall conclusion, but the pragraph you wrote seems suspicious:
    It has long been obvious that eyeglasses help people see better, and eyeglasses are basically physics, not “medicine,” so that result should be set aside. Since this experiment looked at thirty measures in total then just by chance one of them should seem significant at the three percent level, explaining the blood pressure result. The “risk of dying index” effect is mainly just the blood pressure effect, and the index came from a 1976 paper on heart attack risk, which was chosen well after the RAND experiment started, so the statistical significances reported for that clearly did not correct for data mining.

    Three different reasons to set aside three results that disagree with your conclusion? That’s not appropriate. You should go with the conclusion “but by nearly every measure, they were not noticeably healthier!” instead. It doesn’t lose any of it’s potency in that form.

  • Douglas Knight

    I want to reiterate michael vassar’s comment. I don’t imagine the proportion of good and bad medicine has changed, but I imagine cheap medicine has a higher proportion of good than expensive medicine and I imagine that the proportion is maintained by cheap medicine getting better while more bad expensive medicine is added. In the 70s, medicine was null at the margin, but it has probably gotten better at that same point and the increase of price may mean that people are at a different point. In particular, the benefit for uninsured has probably risen.

    Stuart Armstrong:
    Robin Hanson gives three reasons for discarding two results. One is eyeglasses. That is a very interesting result, but I think he is right to separate it. The question with medicine is whether to trust experts. We don’t need to trust eye doctors, because we directly experience the improved vision.

    The other result he discards is blood pressure and he has two reasons for discarding it. The first is saying that the error bars are too small because of data mining (looking at 30 measures of health). The other, which seems less plausible to me, is that the measure is biased by data mining (choosing a study of how to translate blood pressure to life expectancy). If he wants to claim bias, he should point to some modern consensus saying blood pressure is less important or, better, to lower numbers both before and after.

  • http://profile.typekey.com/sentience/ Eliezer Yudkowsky

    I’d just like to say that my mental model of the marginal value of extra spending on healthcare has gone way down since Robin started posting on this subject. That is, I have actually shifted opinions. This is good to emphasize because rationalists typically post only disagreements, and I don’t want Robin to feel that he’s screaming into the empty dark.

    So it would seem that spending is spiraling out of control on consumables that help no one, but are viewed as morally obligated and are too sacred to question. Perhaps this conclusion will only be accepted in some more intelligent society, such as Japan or China, which will be the last country standing when all the rest of us have been reduced to penury.

  • scott clark

    I’d like to echo Eliezer’s comment and post agreement with Robin’s insights. I had Robin as a professor for health economics class at Mason, and the sheer volume of evidence he brings to the table lead inexorably to the conclusion that a large part of health spending has no discernable benefit, other than showing that you care.

    It is much clearer that getting excercise, sleeping 7 hours a night, etc. will improve longevity than spending time in the medical system. I may still have the handouts somewhere.

  • albatross

    Wow. This is really a fascinating bit of research.

    The two caveats that come to mind (I’ve skimmed the summary, so surely I’ve missed important details) are:

    a. Anecdotally, a lot of the trauma of dealing with the medical system involves getting clobbered by medical bills during or after a serious illness, or keeping a job they hate rather than lose their insurance.

    b. The tradeoff may be different for rare cases, with the cases too rare to show up in even this large study.

    It seems like this data, if I’ve understood it correctly, makes an argument for worrying much less about access to healthcare, and maybe thinking in terms of catastrophic coverage, so people don’t get clobbered by medical bills. All the participants had a yearly cap on their medical bills; something like that might be sufficient to make a huge improvement in well-being at fairly low cost.

    Oh, and I guess the glasses result suggests that it might make sense to run free eyeglass clinics or something. The “the glasses are only physics” comment seemed kind of silly to me–WTF is high blood pressure?

    The intuition here is that if you’re feeling serious symptoms of something nasty, you probably get yourself to a doctor somehow, even if you’re paying out of pocket.

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Albatross, pressure is indeed physics, but it takes much more than physics to believe that high blood pressure is bad and that certain drugs are a good way to fix that. With eyeglasses only physics is needed to see what the problem is and how to fix it. And we can each personally verify that the problem has in fact been fixed.

    Douglas, as best I understand it your model would predict a lower value now for the sort of medicine that lower prices would induce more of.

  • Carl Shulman

    Robin,

    Is there evidence that drugs, which have to go through clinical trials for efficacy (although not for off-label uses), are on average more effective than surgery and other procedures that doctors can introduce without regulatory screening?

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Carl “any evidence” is a very low standard, which I’m sure lots of studies out there meet. This post is about what if you set very high standards, because you are not sure what you can believe? I here show you the one study that meets the highest standards.

  • Carl Shulman

    Robin, please read that as ‘evidence you consider significant after extensive study of the literature.’

  • http://amnap.blogspot.com/ Matthew C

    I would suspect that diagnostic blood pressure would likely be lower among people who went to the doctor often.

    Blood pressure is very susceptible to nervousness, and people who had regularly been to a doctor and had their blood pressure taken are likely to be a bit less nervous about having their blood pressure measured than those who hadn’t been to see a doctor much, or at all.

  • http://profile.typekey.com/halfinney/ Hal Finney

    For people who want to comfort themselves that things are improving in medicine, take a look at this New York Times article from last year on medical misdiagnosis:

    http://www.nytimes.com/2006/02/22/business/22leonhardt.html

    “With all the tools available to modern medicine — the blood tests and M.R.I.’s and endoscopes — you might think that misdiagnosis has become a rare thing. But you would be wrong. Studies of autopsies have shown that doctors seriously misdiagnose fatal illnesses about 20 percent of the time. So millions of patients are being treated for the wrong disease.

    “As shocking as that is, the more astonishing fact may be that the rate has not really changed since the 1930′s. ‘No improvement!’ was how an article in the normally exclamation-free Journal of the American Medical Association summarized the situation.”

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Matthew, the large literature on placebo effects would lead us to expect some sort of placebo effect of more medicine. So for this reason if no other it is surprising that we don’t see more an effect.

  • eddie

    scott: is that “7 hours instead of 6 hours” or “7 hours instead of 8 hours” ? Enquiring (and sleepy) minds want to know.

  • Douglas Knight

    RH thinks that my “model would predict a lower value now for the sort of medicine that lower prices would induce more of.”

    Prices and consumers aren’t homogeneous. Lower prices at the low end of the scale should do good. It’s not clear what lower prices for the average consumer would do; there are opposing forces. To extrapolate that the marginal benefit for the average consumer is still zero seems reasonable, but the error bars are large.

    Probably, part of the increase of medical spending is increasing the proportion of new, expensive care. That suggests that the marginal benefit to the average person is worse than in the 70s. Other changes may be discouraging the use of cheap medicine. This may be true with the average person and not just with the uninsured. eg, the hassle of going through insurance is added to the cost of all things, because one really needs insurance to shield from hospital billing.

  • http://profile.typekey.com/halfinney/ Hal Finney

    People are often skeptical about these kinds of claims, on the basis that “extraordinary claims require extraordinary evidence.” The question is whether these claims are truly extraordinary or not; and more generally, how do we decide what constitutes an extraordinary claim? There are certain claims which are generally accepted among experts in a discipline but which are not widely appreciated by a larger audience. Medicine seems to be an area particularly prone to this kind of discrepancy.

  • Jor

    I haven’t read the details of the RAND study, but with the bias of a medical student, I can tell you that modern medicine has changed tremendously, even within the past 30 years. Preventive medicine (the thing that seems to being aimed at in the study) has improved tremendously as well. Several key studies were published subsequent to tha time period that almost compeletley reversed therapy for some chronic disease (Heart Failure, Arrythmias). Other diseases, Hypertension, high cholesterol, diabetes, psychiatric disorders, heart failure have had pharmacological revolutions since 1974.

    Much of the current preventitive medicine rx, have been shown in randomized controlled trials to improve mortality and decrease secondary complications. Further more, the push for evidence-based (or Randomized Control based) practice has really only taken hold within the past decade or so.

    If you want to make such a bold claim, I think you really gotta redo the RAND study _today_.

  • http://profile.typekey.com/sentience/ Eliezer Yudkowsky

    Jor, the obvious reply is that you’ve got to redo the RAND study today, because you’re the one who’s claiming that something has changed since the last experiment.

  • Carl Shulman

    It’s striking that the US government spends hundreds of billions on health care, but doesn’t set aside even 0.1% of that total to conduct similar studies on a regular basis and know what it’s buying. State bills to expand health insurance coverage could easily incorporate such an experiment as well.

  • Jeremy McKibben

    Perhaps I’ve got false dilemmas on the brain (thanks to Eliezer), but it would appear that there are conclusions other than “free health care is a waste of money” that one could draw from the RAND experiment. Here are a few examples that I thought up in under 5 minutes:

    1. Maybe health care services should be constructed in a way that helps ignorant consumers better compare marginal benefits to costs. In this case, free medicine would only be consumed if it at least provided a small benefit.

    2. There could easily be a mix of treatments with a larger marginal benefit, but doctors and patients (at least in the 70′s) did not have the resources to determine what it was. Advances in information technology (such as the widespread availability of systematic reviews on the internet) may have already solved this problem.

    3. If the marginal benefit of medicine is negligible when health care is free, isn’t it possible that the same is true even when consumption is slightly lower, as it is without free health care? In this case, we can consider consumers to be inflicting a negative externality on themselves under the current pricing scheme, and so it might make the most sense to tax rather than subsidize the consumption of health care. The additional revenue could be used to set up a prize committee a la Joe Stiglitz, which would certainly benefit consumers more than ineffective medicine:
    http://www.project-syndicate.org/commentary/stiglitz81
    This analysis would actually agree with Robin’s, and even carry it to an extreme.

    However, Robin has thought about this issue far longer than five minutes, and I have to admit that he’s beginning to sway my opinion. The only thing holding me back is that it that there is a decent possibility that the marginal value of medicine has changed in the last quarter century.

  • eddie

    Eliezer: on what rational basis do you conclude that “nothing has changed in thirty years” is sufficiently more likely than “something has changed in thirty years” that the claim “if you would not pay for medicine out of your own pocket, then don’t bother to go when others offer to pay” is justified by a thirty-year old study?

    Robin doesn’t make that claim, of course. His claim is not bold, but qualified: “unless the marginal value of medicine has changed in the last thirty years”. But the qualified claim is pretty useless, isn’t it? “Unless I flipped heads, you should bet that I flipped tails.” The truth of Robin’s qualifier is the important part, not his qualified conclusion.

    So if you’re content to make uninteresting statements, then you indeed have no reason to redo the Rand study today.

  • michael vassar

    Carl: It’s striking, but not surprising. Almost everyone underinvests in information. Variance for governments should be expected to be less than that for individuals when the governments inherit their behavioral patterns from the individuals of whom they are composed.

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    The correlation studies I mentioned have continued over the last thirty years and continue to usually give the same result: no effect of variations in medicine on health.

    I certainly support redoing the RAND experiment, this time with twice as many people and lasting twice as long. This would cost a half billion dollars. Donations anyone?

  • albatross

    Robin:

    I see the point you were making now. I started out thinking in terms of arguments about nationalized health care, what should be paid for, etc., and I think I missed the fact that you were also talking about how you know whether you should use more medical care. So, I’d guess that dental work is pretty similar, right–other than cleanings, you mainly go to the dentist when a toothache or abcess leaves no question in your mind that you need to see a dentist. By contrast, whether that high cholesterol level needs to be treated with a statin, or whether you really need that colonoscopy at age 50, is not directly observable.

    Does the phenomenon you’re discussing here relate to the often-quoted statistics about the US spending lots more per person on medicine than most other countries, but not getting better outcomes?

  • Jor

    I think I’ll go further, and state that the RAND study is actually a very poorly designed study to measure something like effect of health care — even though it has first blush appeal.

    For specific diseases, we know (through randomized controlled trials) we can improve mortality and prevent future disease. The significances in a RAND type experiment would come out through sub-group analysis of particular disease and particular physiologic measurements. The problem is, a RAND study really doesn’t have the power to measure current therapuetic differences in sub groups.

    I.e., two groups of 30, with 10 people ine ach group with Diabetes, 10 in each group with high cholesterol, and 10 in each group with high blood pressure. The effect of treating blood pressure in 10 people, is going to get lost in the noise of the 20 not being treated when you do a group comparison — unless you do sub-group analysis on patients who actually have hypertension.

  • http://profile.typekey.com/bayesian/ Peter McCluskey

    Hal, the extent to which these claims are extraordinary ought to be influenced by the extent to which they’re an example of a more widely known bias. There seems to be moderate evidence for a widespread bias toward overestimating the value of expert opinion (e.g. Tetlock’s Expert Political Judgment), which should lead us to expect people to overestimate the value of doctors’ advice.
    But that doesn’t seem like a very rigorous way of evaluating the extraordinariness of the claims, and it would be nice to have a better way of estimating extraordinariness.

  • Douglas Knight

    Jor: one explanation is that people in controlled studies can be helped by medicine, but the general public cannot. It is very clear from the numbers that the benefits observed in controlled studies are not obtained, at least in full, by the general public. One way that could be true is that the doctors in controlled studies are better (and, eg, nag about compliance), or that they know they’re being watched.

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Jor, I started my post by pointing to the severe problems we face using clinical trial results for specific conditions to estimate overall net benefits. There can be “funding bias, treatment selection bias, publication selection bias, and so on.” I don’t understand how you propose to overcome that.

  • Jor

    I defintiely lost site of the biases in clinical trials, however the RAND study is still under-powered (the commonly cited HTN trials have 6000 patients, the largest has 40,000) and really can’t be used as evidence for lack of efficacy of medicine even in the whole.

    Vaguely reminds me of soemthing I read this week (blackswan or here), no evidence of disease is not the same as evidence of no disease. No evidence of efficacy, can not be used in this case as evidence of no efficacy — especially when we have trials showing evidence of efficacy.

  • Stuart Armstrong

    no evidence of disease is not the same as evidence of no disease.

    No evidence of disease, in a situation where there would be evidence of that disease if the disease were present, is evidence of no disease.

    If I claim there is a (normal) lion in your room, and you can’t see him, smell him or touch him, that is evidence that he isn’t there.

  • http://www.bestdevices.info/best/ sizegenetics review

    Yes, no evidence of disease is not the same as evidence of no disease. With conclusing evidence it can be difficult

  • Michael Ash

    Just FYI, the RAND HIE only enrolled non-elderly people, a point that RH omits in the otherwise excellent precis of the experiment. (IIRC, Medicare legislation made it impossible to deny Medicare to the eligible, 65+ population, which precluded their enrollment in the HIE.)

    The experiment only provided three-to-five years of insurance, as RH does note.

    It’s not clear what health effects would be expected in a young population with three to five years of care. Successful blood-pressure screening and remediation seems like a pretty plausible result. BP improvement was declared in advance, not mined after the fact, as an outcome variable. BTW, what would be the appropriate multivariate significance test?

    A reasonable model of health care is that a lifetime of good care yields better health in the expensive, older years, and this would simply have no chance at all of showing up in the HIE.

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Michael, if you think we’d see more effects in a longer experiment, I presume that you will then sign our petition for a longer version?

  • http://profile.typekey.com/bayesian/ Peter McCluskey

    Here’s one more piece of anecdotal evidence against the effectiveness of medicine: http://fallenpegasus.livejournal.com/612622.html.

  • anon

    Thanks, Peter. Does anyone else have any anecdotes that they would like to share with us and waste more space on this board? :)

    THERE IS NO SUCH THING AS ANECDOTAL EVIDENCE… anyone who searches for anecdotal evidence to back up his/her own views will surely fall victim to confirmation bias.

  • anon

    Robin,

    I see that you only responded to part of Ash’s concern

    “It’s not clear what health effects would be expected in a young population with three to five years of care.”

    … probably biased by your own views of medicine… you are completely ignoring other interpretations and limitations of the Rand study in favor of using the study to confirm your own views.

    I also see that you dismissed Jor’s concerns in regards to statistical power on account of your belief of the existence of biases. Why don’t you think a little bit more about the statistical concern raised instead of side-stepping his argument by bringing up the existence of biases. The existence of the biases you bring up is ONE possible explanation, but there are other possible explanations. You really shouldn’t dismiss them so quickly.

    How can you be so sure you are right? What biases must you suffer from?

    Two people can have rational explanations for the same phenomenom… the unbiased person will realize that and admit that the evidence is not definitive.

  • http://profile.typekey.com/robinhanson/ Robin Hanson

    Anon, I would not claim exactly zero marginal effects of medicine. With limited statistical power, one can just infer a small effect, but not a zero effect.

  • Hopefully Anonymous

    Anon, in all serious, good thread policing. *thumbs up*.

  • http://profile.typekey.com/bayesian/ Peter McCluskey

    Anon, what evidence is there that using anecdotal evidence will “surely” cause confirmation bias? How do alternative approaches (short of running a new, improved Rand study) reduce the problem of confirmation bias?
    Part of the reason for my comment was to provide a hint about why people disagree about the effectiveness of medicine. Do you know of a way to think about the causes of such disagreements that doesn’t involve anecdotes?

  • anon

    Because anyone can find an anecdote which supports his view. If you go searching for evidence to support your view and find it, it will only serve to further increase your belief in the view you set out to prove. Statistics is about rising above anecdotal evidence.

    I have no doubt that anecdotal evidence contributes to disagreements about the effectiveness of medicine… it’s because people actually think that anecdotal evidence is evidence.

    “Do you know of a way to think about the causes of such disagreements that doesn’t involve anecdotes?”

    Yes, people not understanding statistics and misinterpreting study results.

  • Hopefully Anonymous

    I agree with anon. Anecdotal evidence serves almost entirely as appeal to (confirmation) bias. There is an alternative to running a new, improved RAND study. It’s to say “I intuitively think” or “in my unsubstantiated opinion”. That way one is appropriately labeling a model or hypothesis that hasn’t been shown to be supported by quality empirical methods.

  • jebs house

    I’m not sure what the hold-up is… maybe they have re-thought their stance on how this is going to actually make the company any money. Or perhaps their lawyers pointed out the liability of providing agents a platform to stick their feet in their mouth. Whatever it is, it’s hardly something I’d claim as being “Well done”.
    http://www.jebshouse.com

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  • http://hazard.com+ Dan Woodard

    The Rand HIE study did NOT compare patients who got care free with patients who had to pay for the actual cost of their care; it investigated ONLY the effects of co-pays at the time of service. ALL the groups had excellent insurance. The MAXIMUM out-of-pocket annual cost was only $1000.

    The study concluded that co-pays reduced “inappropriate or unnecessary” medical care, but also reduced “appropriate or needed” medical care.

    As a doctor this seems obvious to me. Regardless of what they pay (full cash to completely free) patients come in if 1) they think they need help and 2) they think they can afford to be seen. Generally they have no way of knowing whether care is really needed. I have been in practice 30 years and have known a number of patients who though they needed help, couldn’t afford it, and died.

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