  Information extraction is a critical step in the practice of conducting
biomedical systematic literature reviews. Extracted structured data can be
aggregated via methods such as statistical meta-analysis. Typically highly
trained domain experts extract data for systematic reviews. The high expense of
conducting biomedical systematic reviews has motivated researchers to explore
lower cost methods that achieve similar rigor without compromising quality.
Crowdsourcing represents one such promising approach. In this work-in-progress
study, we designed a crowdsourcing task for biomedical information extraction.
We briefly report the iterative design process and the results of two pilot
testings. We found that giving more concrete examples in the task instruction
can help workers better understand the task, especially for concepts that are
abstract and confusing. We found a few workers completed most of the work, and
our payment level appeared more attractive to workers from low-income
countries. In the future, we will further evaluate our results with reference
to gold standard extractions, thus assessing the feasibility of tasking crowd
workers with extracting biomedical intervention information for systematic
reviews.
