Learning from “Learning from Hackers”

Alongside colleagues (Enrico Coiera and Richard Day) from here in Sydney and (Kenneth Mandl) from near Boston in the US, I wrote an article for Science Translational Medicine in which we related the current system of “clinical trial evidence translation” to the very successful open source software movement. We highlighted the factors in that success – open access, incentives for participation, and interoperability of source code.

In the article, we drew parallels between the production of source code for open source software and the “source code” of clinical trials – the patient level data that says how well an intervention worked for each patient. If the source code of clinical trials were to be made more widely available, we could start to answer much more interesting questions, more accurately. We think it has the potential to dramatically improve the speed at which we detect unsafe drugs, and help doctors provide the right drugs to the right patients.

Just so that I can keep a record, here is a rough timeline of what happened in the media after the article was published:

  • The article was published in Science Translational Medicine on the 2nd of May in the US (early am on the 3rd in Sydney time).
  • The article was covered by the Sydney Morning Herald on page 15 of Thursday’s (3rd May 2012) edition.
  • Joshua Gliddon was very quick to call me up and have a chat about the article, writing a nice piece about it at ehealthspace.org
  • Enrico Coiera and I wrote a piece for the Sydney Morning Herald’s National Times talking about the article in more detail (published online on the 4th May 2012).
  • The article was also covered by Higher Education section of The Australian on Friday (4th May 2012).
  • Australian Life Scientist collected up a wide selection of information and wrote a summary of the article and our comments (first recorded example of the phrase “all information should be free” that I found was in Levy’s Hackers published in 1984, which would pre-date Woz, I believe).
  • @RyanMFierce found irony in the publication because it argues for open data and was published behind a paywall.
  • The article was mentioned in the introduction to a piece on sharing in genetics on The Conversation (an excellent outlet), which quickly became the most read article on the website (3rd May 2012).
  • A summary of the SMH National Times story and the article appeared on Open Health News (4th May 2012).
  • Here is the original media release from UNSW.

Hopefully once this burst of activity falls away, it will leave some lasting resonance and help convince a few people to think harder about how we can fix the problems of evidence translation.

I learnt a couple of lessons from the media activity surrounding the publication. Firstly, I learnt that it is impossible to control the message from your own work – people will read whatever they want and will probably focus on sections you thought were less important. There’s nothing you can do about it other than to faithfully represent your work and push your own agenda. I also learnt that there is a wide and diverse group of people already dealing with open access issues in clinical trial data – many more than I originally realised when I wrote the piece.

The next steps in the research will include learning about how far we can push the limits of patient-level meta-analysis by pooling clinical trial data in clever ways, while maintaining rigorous de-identification. Eventually we may even be able to automate the rapid integration of new evidence into organic, linked and dynamic systematic reviews and guidelines, customised for groups or even individuals.

More aggressive marketing ∝ 1/benefit-to-harm ratio

New “Law” Attempts to Explain Strategies Drug Marketers Use to Sway Prescribing, March 16, 2011, Mitka 305 (11): 1083 — JAMA

An interesting and concise new article on the influence of marketing on prescribing patterns was published online in the American Journal of Public Health and then picked up in the commentary of JAMA. It is an interesting read and does a good job of describing one of the bigger problems in the translation of evidence into practice.

from JAMA

[a picture from the JAMA commentary]