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Evaluation of PICO as a knowledge representation for clinical questions.

Authors: Xiaoli Huang; Jimmy Lin; Dina Demner-Fushman;

Evaluation of PICO as a knowledge representation for clinical questions.

Abstract

The paradigm of evidence-based medicine (EBM) recommends that physicians formulate clinical questions in terms of the problem/population, intervention, comparison, and outcome. Together, these elements comprise a PICO frame. Although this framework was developed to facilitate the formulation of clinical queries, the ability of PICO structures to represent physicians' information needs has not been empirically investigated. This paper evaluates the adequacy and suitability of PICO frames as a knowledge representation by analyzing 59 real-world primary-care clinical questions. We discovered that only two questions in our corpus contain all four PICO elements, and that 37% of questions contain both intervention and outcome. Our study reveals prevalent structural patterns for the four types of clinical questions: therapy, diagnosis, prognosis, and etiology. We found that the PICO framework is primarily centered on therapy questions, and is less suitable for representing other types of clinical information needs. Challenges in mapping natural language questions into PICO structures are also discussed. Although we point out limitations of the PICO framework, our work as a whole reaffirms its value as a tool to assist physicians practicing EBM.

Related Organizations
Keywords

Evidence-Based Medicine, Physicians, Decision Making, Humans, Patient Care

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
337
Top 1%
Top 1%
Top 10%
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