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Sunday, September 19, 2010

Rethinking Science

There is an excellent piece from The Economist:
Good sense is the most fairly distributed commodity in the world, Descartes once quipped, because nobody thinks he needs any more of it than he already has. 
It is always great when the lead off for an essay has such a pithy quote. The author goes on to write:
No group of believers has more reason to be sure of its own good sense than today’s professional scientists. There is, or should be, no mystery about why it is always more rational to believe in science than in anything else, because this is true merely by definition. What makes a method of enquiry count as scientific is not that it employs microscopes, rats, computers or people in stained white coats, but that it seeks to test itself at every turn. If a method is as rigorous and cautious as it can be, it counts as good science; if it isn’t, it doesn’t. Yet this fact sets a puzzle. If science is careful scepticism writ large, shouldn’t a scientific cast of mind require one to be sceptical of science itself?
 There is no full-blown logical paradox here. If a claim is ambitious, people should indeed tread warily around it, even if it comes from scientists; it does not follow that they should be sceptical of the scientific method itself. But there is an awkward public-relations challenge for any champion of hard-nosed science. When scientists confront the deniers of evolution, or the devotees of homeopathic medicine, or people who believe that childhood vaccinations cause autism—all of whom are as demonstrably mistaken as anyone can be—they understandably fight shy of revealing just how riddled with error and misleading information the everyday business of science actually is. When you paint yourself as a defender of the truth, it helps to keep quiet about how often you are wrong.

Thus, despite having a set of tools unrivaled in regards to identifying truth, science and scientists are wrong more often than begin right. The science is undergoing continuous revision. This is obviously relevant to the practice of medicine. It is cumbersome in a world where patients want to know THE ANSWER or THE DIAGNOSIS to respond with hedging.  It unquestionably cuts into billing to have to deal with the messy world of gray as opposed to black and white.  Furthermore, this may call into question the actual role of science and evidenced based medicine. 

When I see a patient and discuss options to deal with a particular problem, the science and evidence are important but represent only a part of the picture. They may help guide any decision by providing a background as to the likely outcomes. How the patient deals with this information (if actually available) is not a scientific question but a personal question. Science cannot and should not dictate the answers to personal decisions. It is critical that we know when our data is good and revealing of underlying trends. How people use this data and what outcome they decide is desirable should be their call. Only they know what their particular goals are.

The assumption promulgated in policy circles is that what should be delivered (and paid for) in the health care realm can be decided on the basis of science. That is one of  the driving forces behind the EBM movement. However, you need to ask whether patient decisions regarding health interventions are fundamentally scientific questions. While these decisions may be influenced greatly by data and products of scientific inquiry,  I believe the answer they are personal decisions. These decisions are also highly influenced by individual and personal goals which are highly disparate within any given population.      

However, this paradigm is not so simple because there is often another party involved, the payer of the service. The payer generally has some sort of fiduciary responsibility to yet another party (taxpayer, stockholder, business owner). Science is injected into this mix based upon the assumption that we can use science to decide what health care interventions are needed. Perhaps it is reasonable to use scientific and statistical methods to define whether on average a particular intervention and allocation of resources generates a net positive effect in a given population. However, it is a pretty poor tool when it comes to accommodating individual needs. Using scientific algorithms to decide personal questions will almost certainly result in wasteful allocation of resources and  substantial personal disappointment. 

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