I’m very happy to have been given access to a new analytic tool on Trip.  It analyses the near 100 million bits of clickstream data (sounds like ‘big data’ to me).

I simply enter a search term and it exports every instance of a person using that search term, what date and time, what they clicked on and if they used any additional search terms.  For example, a quick search on an incomplete data set (still only half way through full indexing the 100 million records) for Fingolimod (or the brand name Gilenya) revealed it had been searched over 350 times in the last five years.  The top five articles viewed were:

  1. Fingolimod for the treatment of highly active relapsing-remitting multiple sclerosis. National Institute for Health and Clinical Excellence – Technology Appraisals (47 views)
  2. Fingolimod – a potential new oral treatment for multiple sclerosis? NPC Rapid Reviews (40)
  3. Fingolimod – Multiple Sclerosis. Canadian Agency for Drugs and Technologies in Health – Common Drug Review (35)
  4. Fingolimod (Gilenya) – in highly active relapsing remitting multiple sclerosis. Scottish Medicines Consortium (30)
  5. Fingolimod versus Glatiramer for Adults with Relapsing Remitting Multiple Sclerosis: Clinical and Cost-Effectiveness. Canadian Agency for Drugs and Technologies in Health – Rapid Review (26)

And below is a tag cloud of the additional terms added to the search:

 NOTE: the tag cloud formation software capped the number of words displayed to something like the top fifty.

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