title: A data-driven concept schema for defining clinical research data needs.
abstract: OBJECTIVE
  The Patient, Intervention, Control/Comparison, and Outcome (PICO) framework is an effective technique for framing a clinical question. We aim to develop the counterpart of PICO to structure clinical research data needs.
  
  
  METHODS
  We use a data-driven approach to abstracting key concepts representing clinical research data needs by adapting and extending an expert-derived framework originally developed for defining cancer research data needs. We annotated clinical trial eligibility criteria, EHR data request logs, and data queries to electronic health records (EHR), to extract and harmonize concept classes representing clinical research data needs. We evaluated the class coverage, class preservation from the original framework, schema generalizability, schema understandability, and schema structural correctness through a semi-structured interview with eight multidisciplinary domain experts. We iteratively refined the schema based on the evaluations.
  
  
  RESULTS
  Our data-driven schema preserved 68% of the 63 classes from the original framework and covered 88% (73/82) of the classes proposed by evaluators. Class coverage for participants of different backgrounds ranged from 60% to 100% with a median value of 95% agreement among the individual evaluators. The schema was found understandable and structurally sound.
  
  
  CONCLUSIONS
  Our proposed schema may serve as the counterpart to PICO for improving the research data needs communication between researchers and informaticians.
authors.affiliation: Department of Biomedical Informatics, Columbia University, NY, New York, USA.
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Hruby
authors.affiliation: Department of Biomedical Informatics, Columbia University, NY, New York, USA.
authors.forename: Julia
authors.initials: J
authors.lastname: Hoxha
authors.affiliation: Department of Biomedical Informatics, Columbia University, NY, New York, USA.
authors.forename: Praveen Chandar
authors.initials: PC
authors.lastname: Ravichandran
authors.affiliation: Department of Pediatrics, University of Wisconsin, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA.
authors.forename: Eneida A
authors.initials: EA
authors.lastname: Mendonça
authors.affiliation: Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA; School of Information, University of Michigan, Ann Arbor, MI, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Hanauer
authors.affiliation: Department of Biomedical Informatics, Columbia University, NY, New York, USA. Electronic address: chunhua@columbia.edu.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Weng
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D002986:Clinical Trials as Topic / Q000379:methods; D057186:Comparative Effectiveness Research; D003625:Data Collection / Q000379:methods* / Q000592:standards; D006801:Humans; D008962:Models, Theoretical; D020380:Needs Assessment
keywords: Comparative effectiveness research; Data collection; Medical informatics; Models; Needs assessment; Theoretical