A practical method for transforming free-text eligibility criteria into computable criteria.
Formalizing eligibility criteria in a computer-interpretable language would facilitate eligibility determination for study subjects and the identification of studies on similar patient populations. Because such formalization is extremely labor intensive, we transform the problem from one of fully capturing the semantics of criteria directly in a formal expression language to one of annotating free-text criteria in a format called ERGO annotation. The annotation can be done manually, or it can be partially automated using natural-language processing techniques. We evaluated our approach in three ways. First, we assessed the extent to which ERGO annotations capture the semantics of 1000 eligibility criteria randomly drawn from ClinicalTrials.gov. Second, we demonstrated the practicality of the annotation process in a feasibility study. Finally, we demonstrate the computability of ERGO annotation by using it to (1) structure a library of eligibility criteria, (2) search for studies enrolling specified study populations, and (3) screen patients for potential eligibility for a study. We therefore demonstrate a new and practical method for incrementally capturing the semantics of free-text eligibility criteria into computable form.
Tu
Samson W
SW
Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA. swt@stanford.edu
Peleg
Mor
M
Carini
Simona
S
Bobak
Michael
M
Ross
Jessica
J
Rubin
Daniel
D
Sim
Ida
I
D002986:Clinical Trials as Topic; D019295:Computational Biology; D016208:Databases, Factual; D004608:Eligibility Determination / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D012660:Semantics; D018875:Vocabulary, Controlled