A strange commentary in the Washington Times this week entitled “‘Evidence-based’ Rx miscues” makes claims about evidence-based medicine (EBM): both what the terms means and what it implies for health policy. The author suggests that EBM is equivalent to “one-size-fits-all” medicine that removes physician autonomy in pursuit of a “political imperative to cut costs – not the medical imperative to give patients the best care possible.”

Dr. Roy Poses, a well-respected physician who has done a lot of work studying physician probability judgment (one example of which is mentioned in Chapter 7 of Medical Decision Making) has posted a rebuttal on the Health Care Renewal blog. Dr. Poses demolishes the misrepresentation of EBM that appears in the original article (as well as asking some on-point questions about the author’s interests in the matter), and does it quite effectively, so I won’t repeat his criticism here. Instead, I’ll focus on some other misunderstandings in the original commentary: that cutting health care costs is at odds with the medical imperative to improve care, that patients are so biologically unique that studies of patient groups has little value, and that EBM reduces physician autonomy.

Are considerations of costs at odds with the “medical imperative”?

The commentary invites us to “Consider an overweight man who is forced to take a cheaper, less effective anti-cholesterol drug. If he ends up in the emergency room because of undertreated cardiovascular disease, this could end up costing the health-care system significantly more money.” Setting aside that the author now seems concerned with health care costs in this situation (not only with effectiveness), we could equally consider a situation in which comparative effectiveness evidence helps ensure that the patient is prescribed one of a set of anti-cholesterol drugs that evidence suggests are equally effective and safe. The physician, knowing this, chooses which of these drugs to prescribe first on the basis of judgments about the needs of the patient, which might include which of the drugs the patient can afford, which offers the most convenient dosing, etc. A patient prescribed an equally effective but more costly drug who can not afford to fill the prescription may wind up in that same emergency room, when an equally effective and more affordable generic drug might have kept him healthy.

Here’s an example of a comparative effectiveness review from January 2007 by the US Agency for Healthcare Research and Quality (AHRQ): Comparative effectiveness of second generation antidepressants in the pharmacologic treatment of adult depression. Readers will note that this report makes no references to cost-effectiveness (it barely mentions cost at all), and focuses on reviewing the available evidence that compares the medical effectiveness of different second generation antidepressants on a variety of factors and for a variety of subgroups of patients. It points out the strength of evidence to answer different questions (which ranges from none to high), and, where evidence exists, what the evidence says (e.g. there is no difference in effectiveness between these drugs for major depressive disorder).

Is each patient biologically unique?

There is no question that individual human beings have unique genetic makeups that lead to unique biology. The question is whether this matters for medical treatment and medical research.

All medical research is based on the idea that biological similarity is as important as biological difference. When a new patient presents to a physician with the first strep throat of their lives, the physician considers prescribing an antibiotic, suggests the patient take an analgesic, but doesn’t offer an anticonvulsant. Why? Because the physicians knows the pathophysiology of strep throat, and understands that the infection can be eradicated and pain can be reduced with those medications. The physician knows this because we have studied enough people to enable us to generalize. Research on groups of people is fundamental to modern medicine.

Not every drug works as well for every person, but through well-designed research we can reduce the uncertainty and increase our confidence in how likely a drug is to work on average. We can, and do, also learn about how variable the drug’s effect is around that average, and for which patients it may perform better or worse.

As we learn more about genetic medicine, we may one day seek to tailor therapies to the specific genetic makeup of a patient. Of course, it will require extensive research on the application of these processes applied to large groups of patients before we can be confident of our ability to do this. If our knowledge is great enough that tailored therapies can complete reduce uncertainty in outcomes, the profession of medicine will experience fundamental changes. But people need health care now, too.

Does EBM reduce physician autonomy?

Physicians need the freedom to pursue effective treatments for a patient based on their knowledge — which should include available, credible research evidence — and judgment — which should include contextual factors that are individual to a patient (see, for example, this excellent article by my colleague, Dr. Saul Weiner). EBM enhances this freedom, by improving the knowledge base on which the physician relies.

Physician autonomy does not extend to prescribing ineffective cures when there is valid evidence of an effective cure. The same applies to diagnosis. No physician I know would prefer to measure fever by a hand on the forehead when a thermometer is available.

Physicians need evidence. Synthesizing evidence to review conclusions about comparative effectiveness allows the physician to reduce a major source of uncertainty, and to better inform his/her judgment in selecting a therapy. It also helps shield the physician and patient from spurious claims of effectiveness made by those with a vested interest in selling more profitable interventions — a financial imperative that can be much more at odds with the medical imperative than social imperatives to manage health care spending for the benefit of society as a whole.