He's a physician who writes mostly about bad science reporting, pseudo-science and quackery and Bad Pharma is all about the tricks that pharmaceutical companies get up to to ensure that trials with negative outcomes never see the light of day and to try and spin their products in the best posible light - like telling doctors that drug X is more effective than a placebo, but failing to mention that it's no more effective than existing drugs on the market. Ultimately, if the doctors who are prescribing the drug don't have the complete picture, how are they supposed to make an informed choice about what to give you?
I heard him talk a few weeks ago and while I might not call him 100% unbiased (I think that some of his allegations are a touch exaggerated in terms of their potential harm) he's definitely very interesting and eye-opening.
And more recently, the proposed UK copyright reform - also expected to become legislation in the next year - included a specific fair dealing right for data mining on journals, like the work of Ionnadis. The publishers had been arguing that this was a separate right from reading (which the researchers have already paid for) http://www.out-law.com/en/articles/2012/june/publishers-and-... (link is to discussion of the older Hargreaves report; the exception made it into the final proposal)
It's not just business concerns though. Many of the individuals doing medical research are just flat-out unqualified/untrained to design a study and manipulate and analyze data. I'm not a statistics guru like some on HN, but I'm pretty good at knowing what to do with a given set of data. I'm exposed to the research efforts of medical professionals through my social network and fiancée, and generally I find their methods/analyses to be either explicitly bad or misguided. Two easy examples would be a general lack of a correction for alpha-inflation and little attention paid to normality of data.
Yes, it's anecdotal experience, and that must be recognized. But, in my observation, it's pervasiveness is noteworthy.
For example, my father is an oncologist who does a lot of clinical trials. When it comes to the number crunching side of the trials, he won't be doing any of it himself but relying on data analysts who work for him (who have statistics backgrounds) and statisticians who work for the MRC (Medical Research Council), CRUK (Cancer Research UK) and the academic institutions which his department is affiliated with.
My experience is anecdotal as well, but it largely can be summed up as 'doctors who are doing serious research and/or trials ensure that the stats are solid, however most doctors aren't doing research at that level'.
There is always the risk with science that you will "finish" which is to say you'll figure something out and by and large be done with it. Nothing else to see, etc. I read an article many years ago about the long lived efficacy of Asprin, or acetylsalicylic acid. Here is a drug that has been around literally since the stone age where folks chewed willow bark and it continues to be a 'wonder drug' whereas more modern drugs seem to arrive on the scene and fade away. While their were obvious cases like antibiotics which became ineffective against resistant bacteria, there was a number of drugs which seem to have never been effective, rather they were marketed, pushed really hard, and then faded. The paper observed that for all their lack of sophistication, witch doctors and other lay healers had a vested interest in keeping things that worked and not keeping things that didn't work. But that doesn't always seem to be the case for modern medicine. Rather there is the 'new recommendation' vs the 'old recommendation' but rarely any follow up on whether or not the old recommendation or the new recommendation actually do anything positive toward treatment.