Hi Michael,
Great question and I'd be very curious to hear other's thoughts on this. I have a similar situation, though in this case, its an update of a search for a review that is ongoing (and will eventually be a living review). We really want to optimize the search as much as possible as the first time around it was very sensitive also with low yield.
One thing I'm planning to do is a sort of text analysis, identifying any search terms that occurred zero times in our potentially relevant studies and multiple times in excluded studies, and thus simply removing those from the search string.
A couple of R packages (with Shiny apps, so you don't need to know R) are available to help with this sort of thing. One is CiteSource which can help determine what sources were most useful (you may be able to exclude certain sources that were searched based on whether they contributed anything useful to the review) and SearchBuildR (more of a text and keyword analysis tool). Note that CiteSource is still a bit in development, and there is a current issue with the Shiny that I'm trying to figure out, which will hopefully be fixed soon.
Looking forward to additional responses on this topic!
Sarah
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Sarah Young
Liaison Librarian
Carnegie Mellon University
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