Already in his lifetime, Scottish physician Archibald Leman Cochrane
earned a reputation as the ‘father of
evidence-based medicine.’ Hailed as the gold standard in life sciences, the
notion of ‘evidence-based
medicine’ leads us to the rightful question typical of ideas whose time has
come whether and how there could ever actually be such a thing as non-evidence based medicine. And if we
look around, it becomes quickly and depressingly clear that there is. And
plenty of it, too. Whether one is to call it conjectural or speculative or
intuitive medicine, it may have merits in respect of matters where the evidence
is just not in, or studies have yet to be completed (say, typically: to be
financed…) and may explain why medicine retains the aura of an art as well as
of a science, but it falls short of scientific method, reliability,
verifiability and duplicability of results.
Evidence based medicine needs to rely on data
and on diligent and cautious interpretation thereof. Oxford dedicated an
interdisciplinary Center to the concept. Of
course there are plenty of areas where that is far from reality. Stanford’s John Ioannidis, a
leading scholar of meta-research
innovation, has claimed that every second medical study is either wrong or
seriously flawed. Part of the problem is that studies yielding negative results
are frequently not published at all. That which is published represents the tip
of an iceberg, cherries
picked carefully by greatly interested parties. But negative
results contain a wealth of information that may well point to different
lines of reasoning or research that can be almost
as valuable as positive results. Even for those, quite often nothing is
disclosed or at least published about potential side effects. That leads to significant
distortions of the picture in certain instances.
So long as publication
is the primary incentive fueling careers in science research (resulting
sometimes in a downright bizarre number
of co-authors, far exceeding motion picture credits), passing that hurdle
is all that matters in reality. Conflicts of interest abound.
Pharmaceutical companies, having
invested billions of dollars in clinical studies, have no interest in
missing out on a return on their investment. They have decidedly no interest in
publishing results that would appear to cast doubt on a product. As it stands,
conflicts of interest are crass and would not be tolerated in any other
setting: pharmaceutical companies who are paying for clinical studies also
assess them and decide
on the publication of their results. The egregious bias inherent in this
situation becomes clear if we were to substitute car manufacturers and had them
control tests about quality and product safety. Think of Volkswagen assessing
the emissions of its engines, or Ford assessing the rear-end
collision safety of its Ford Pinto tanks.
It would have to be a long-term objective to have clinical
studies evaluated by independent institutions far beyond
institutional review boards – however unlikely this is to happen in the
foreseeable future. But just like in a lot of other areas where disruptive
ideas press to the fore because their time has come – think capital markets
transparency, public integrity, freedom of information, executive liability and
private equity – corporations had better get in front or at least on the
bandwagon of a momentum that will not be stopped. Change is seldom desirable
for established interests, but where it has gathered the gale force of nature,
it is not sensible to resist it, especially where it is actually also good
business. In fact, the only way of doing business is the longer term. Of
course, here we go again, trying to presuppose that the actors prioritize
long-term interests of the institution over short-term interest in boni and
performance reviews. That, too, is a principal matter of flawed systems design.
Evidence-based analyses have lately been used in multifunctional nanotechnologies
and risk
analysis, not least at Columbia
University and the University
of Michigan.
Evidence-based medicine optimizes choices by using qualitative
criteria of epistemological strength for the empirical evidence to be relied
upon, that is, meta-analyses, systematic reviews and randomized controlled
trials, and by making all data available for future reference and additional analysis.
It is itself an offshoot of a greater conceptual category, evidence-based
design, one of the key elements in intelligent systems design. Systems design and regulation
provides a powerful methodological momentum for the advancement of quality
protocols and the improvement of decisional
quality.
