With all the discussion of EBM in crisis and EBM on trial it strikes me that maybe these other folks have a different definition or concept of EBM than I do. I think to have any discussion needs to come from a common ground of just what is EBM.
Evidence based medicine is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.
This is the original definition of EBM published in 1996. It urged us to strive to use best available evidence in making clinical decisions. It also cautioned not to be a slave to evidence as evidence was often not applicable to individual patients. This definition served us well until the patient-centered paradigm of care became popular and the definition of EBM evolved to its current form:
This definition is more explicit about the order of importance of the individual elements of the components of EBM: patient preferences and actions is foremost, followed by the clinical state and circumstances and the research evidence. All this is tempered or tied together by our clinical expertise. The evidence tells us what could be done while the rest tells us what should be done.
The other way to look at EBM is that it is just a set of skills:
- asking an answerable clinical question
- finding the best available evidence
- critically appraising the evidence
- applying the evidence to individual patients
- appraising how well you did on each step and, I think, appraising the impact on a patient
So from this background I find it difficult to lay blame on EBM for many of the problems with the evidence. I blogged on this previously and will refute their claims at EvidenceLive2015 in April.
Carl Heneghan recently wrote a blog for BMJ blogs entitled Evidence based medicine on trial focusing mostly on the problem with the evidence part of EBM. While I mostly concur with his list of the problems (distortion of the research agenda, very poor quality research, and lack of transparency for published evidence) I wonder who is at fault. “EBM” seems to get the blame as if there is an entity that is EBM and it controls all research. EBM is but a set of skills: question asking, searching, critical appraisal, and application to individual patients. It is nothing more. So why are people being so critical and place so much blame on a set of skills? There will be several sessions at EvidenceLive 2015 (one of which I will be speaking at in defense of EBM) on real vs rubbish EBM.
I want to focus on the distortion of the research agenda. Professor Heneghan rightly points out that the research agenda is driven by industry. Is that good or bad? I think its both but mostly good. The only other major funders of research are governmental agencies like the NIH. Profit drives innovation. It is very expensive to bring a drug to market. The government could not afford to bring the current drugs we have and need to market. One failed drug alone would deplete the coffers. Failure is the biggest driver of cost. Fewer than 1 in 10 drugs tested makes it to market. Would we tolerate that poor of a success rate at such a big cost by the government? No.
…adjusting that estimate for current failure rates results in an estimate of $4 billion in research dollars spent for every drug that is approved.
I agree that industry seems at times to make a drug then find a “disease” for it. I think the example Professor Heneghan gives is spot on. I don’t believe in adult ADHD but we have drugs for it. Do we need them? No and this video demonstrates why: Drug free treatment of ADHD. Who is really at fault are the doctors who prescribe the drugs that Professor Heneghan feels aren’t necessary. Not the companies for making them.
On a serious note…what about all the devices we use regularly like stents, defibrillators, etc? Would government have independently brought these to market? Likely not. We had balloon angioplasty (without stenting) that worked just fine albeit short term only. It would have been “good enough for government work” as the saying goes. What about advancements in imaging modalities? Again likely not. The old CT scanners worked just fine. Industry is largely responsible for innovation and improvement in all walks of life. Yes for a profit but profit is not a bad thing. Those who say otherwise please return your iPhones.
I’ve left the hardest issue to deal with for last- “Overemphasis on following algorithmic rules”. This has been the most frustrating aspect of my primary care practice. Patients quit being viewed as patients but a set of goals that I had to achieve to be smiled upon fondly by my boss as being “a good doctor”. It took me some time to finally quit playing the game and just do the best I could do and whatever the numbers were so be it.
Algorithmic medicine couldn’t be any more antithetical to EBM. Everyone is viewed the same. EBM clearly, as I have argued in the last three posts, is about individual patient values and circumstances. It’s about clinical experience temporizing what we could do to what we should do. Algorithmic medicine allows no individuality. No temporizing. Thus to claim EBM is in crisis because of algorithmic medicine is wrong. True EBM protects us from the harms of algorithmic medicine.
Interestingly computerized decision support systems (mentioned as a culprit in the first sentence of this section of Greenhalgh’s paper) are at the top of Haynes’ 6S hierarchy of preappraised evidence.
“In these computerized decision support systems (CDSSs), detailed individual patient data are entered into a computer program and matched to programs or algorithms in a computerized knowledge base, resulting in the generation of patient-specific assessments or recommendations for clinicians” – Brian Haynes
At the VA we have a moderately sophisticated CDSS. It warns me if my patient with heart failure is not taking an ACE inhibitor and its smart enough that if I enter an allergy to ACE inhibitors it won’t prompt me to order one. If I tell it that a patient has limited life expectancy it will not prompt me to pursue certain routine health screenings. Thus, I don’t view CDSSs as problematic in and of themselves. The problem arises when physicians don’t consider the whole patient (remember those values and clinical circumstances) in deciding whether or not to follow prompted recommendations.
Greenhalgh has made great points about what happens when good ideas are hijacked and distorted for secondary gain but EBM is not to blame. Victor Montori (@VMontori) said it best in a Tweet to me:
“EBM principles are not in crisis, but corruption of healthcare has oft hidden behind the e-b moniker. EBM helps uncover it“.
In this installation I want to jump ahead in Greenhalgh’s paper to address her last cause of the EBM crisis: “Poor fit for multimorbidity“. Not to worry, I will come back in a future post to cover the remaining “problems” of EBM.
I concur with Greenhalgh that individual studies have limited applicability by themselves in a vacuum to patients with multimorbidity. Guidelines don’t help a they also tend to be single disease focused and developed by single disease -ologists. So is EBM at fault here again? Of course not. EBM skills to the rescue.
The current model of EBM demonstrated below contains 2 important elements: clinical state and circumstances and clinical experience.
Clinical state and circumstances largely refers to the patient’s comorbidities, various other treatments they are receiving, and the clinical setting in which the patient is being seen. Thus, the EBM paradigm is specifically designed to deal with multimorbidity. Clinical expertise is used to discern what impact other comorbidities have on the current clinical question under consideration. and, along with the clinical state/circumstance, helps us decide how to apply a narrowly focused study or guideline in a multimorbid patient. Is this ideal? No. It would be nice if we had studies that included patients with multiple common diseases but we have to treat patients with the best available evidence that we have.
Greenhalgh and colleagues report that the “second aspect of evidence based medicine’s crisis… is the sheer volume of evidence available”. EBM is not the purveyor of what is studied and published. EBM is a set of skills to effectively locate, evaluate, and apply the best available evidence. For much of what we do there is actually a paucity of research data answering clinically relevant questions (despite there being alot of studies- which gets back to her first complaint about distortion of the evidence brand. See part 1 of this series). I teach my students and housestaff to follow the Haynes’ 6S hierarchy when trying to answer clinical questions. As much of the hierarchy is preappraised literature someone else has had to deal with the “sheer volume of evidence”. Many clinical questions can be answered at the top of the pyramid.
I concur with Greenhalgh that guidelines are out of control. I have written on this previously. We don’t need multiple guidelines on the same topic, often with conflicting recommendations. I believe that we would be better off with central control of guideline development under the auspices of an agency like AHRQ or the Institute of Medicine. It would be much easier to produce trustworthy guidelines and guidelines on topics for which we truly need guidance. (Really American Academy of Otolaryngology….do we need a guideline on ear wax removal?) It can be done. AHCPR previously made great guidelines on important topics. Unfortunately we will probably never go back to the good ole days. Guidelines are big business now, with specialty societies staking out their territory and government and companies bastardizing them into myriad performance measures.
Dr. La Rochelle published an article in BMJ EBM this month with a very useful figure in it (see below). It is useful because it can help our learners (and ourselves) remember the relationship between the type of evidence and its believability/trustworthiness.
Lets work through this figure. The upright triangle should be familiar to EBM aficionados as it is the typical hierarchy triangle of study designs, with lower quality evidence at the bottom and highest quality at the top (assuming, of course, that the studies were conducted properly). The “Risk of Bias” arrow next to this upright triangle reflects the quality statement I just made. Case reports and case series, because they have no comparator group and aren’t systematically selected are at very high risk of bias. A large RCT or systematic review of RCTs is at the lowest risk of bias.
The inverted triangle on the left reflects possible study effects, with the width of the corresponding area of the triangle (as well as the “Frequency of Potential Clinically relevant observable effect arrow) representing the prevalence of that effect. Thus, very dramatic, treatment altering effects are rare (bottom of triangle, very narrow). Conversely, small effects are fairly common (top of triangle, widest part).
One way to use this diagram in teaching is to consider the study design you would choose (or look for) based on the anticipated magnitude of effect. Thus, if you are trying to detect a small effect you will need a large study that is methodologically sound. Remember bias is a systematic error in a study that makes the findings of the study depart from the truth. Small effects seen in studies lower down the upright pyramid are potentially biased (ie not true). If you anticipate very large effects then observational studies or small RCTs might be just fine.
An alternative way to use this diagram with learners is to temper the findings of a study. If a small effect is seen in a small, lower quality study they should be taught to question that finding as likely departing from the truth. Don’t change clinical practice based on it, but await another study. A very large effect, even in a lower quality study, is likely true but maybe not as dramatic as it seems (ie reduce the effect by 20-30%).
I applaud Dr. La Rochelle for developing a figure which explains these relationships so well.
I have always suspected that one reason that physicians don’t critically appraise articles is that the criteria for critical appraisal are not readily available in a convenient, easy to use package. No more. I, with the help of some undergraduate computer science students, have created a critical appraisal app for Android devices. Its in the Google playstore and will be listed in the Amazon app store. Hopefully will develop an iOS version if this version is successful.
I tried to take critical appraisal to the next step by “scoring” each study and giving an estimate of the bias in the study. I then make a recommendation of whether or not the user should trust the study or reject it and look for another study. I think one of the shortcomings of the Users’ Guides series is that no direction is given to the user about what to do with the article after you critically appraise it. EBM Rater will give a suggestion about the trustworthiness of the study.
EBM Rater contains criteria to critically appraise all the major study designs including noninferiority studies. It even contains criteria to evaluate surrogate endpoints, composite endpoints, and subgroup effects.
Finally, it contains standard EBM calculators like NNT, NNH, and posttest probability. I added 2 unique calculators that I have not seen in any other app: patients specific NNT and NNH. Many of our patients are sicker or healthier that the patients included in a study. NNTs and NNHs are typically calculated with data from a study so the NNT and NNH is for the study patients. With my calculator you can figure out your individual patient’s NNT or NNH.
I hope you will give it a try and give me some feedback.