title: The design and implementation of an open-source, data-driven cohort recruitment system: the Duke Integrated Subject Cohort and Enrollment Research Network (DISCERN).
abstract: OBJECTIVE
  Failure to reach research subject recruitment goals is a significant impediment to the success of many clinical trials. Implementation of health-information technology has allowed retrospective analysis of data for cohort identification and recruitment, but few institutions have also leveraged real-time streams to support such activities.
  
  
  METHODS
  Duke Medicine has deployed a hybrid solution, The Duke Integrated Subject Cohort and Enrollment Research Network (DISCERN), that combines both retrospective warehouse data and clinical events contained in prospective Health Level 7 (HL7) messages to immediately alert study personnel of potential recruits as they become eligible.
  
  
  RESULTS
  DISCERN analyzes more than 500000 messages daily in service of 12 projects. Users may receive results via email, text pages, or on-demand reports. Preliminary results suggest DISCERN's unique ability to reason over both retrospective and real-time data increases study enrollment rates while reducing the time required to complete recruitment-related tasks. The authors have introduced a preconfigured DISCERN function as a self-service feature for users.
  
  
  CONCLUSIONS
  The DISCERN framework is adoptable primarily by organizations using both HL7 message streams and a data warehouse. More efficient recruitment may exacerbate competition for research subjects, and investigators uncomfortable with new technology may find themselves at a competitive disadvantage in recruitment.
  
  
  CONCLUSIONS
  DISCERN's hybrid framework for identifying real-time clinical events housed in HL7 messages complements the traditional approach of using retrospective warehoused data. DISCERN is helpful in instances when the required clinical data may not be loaded into the warehouse and thus must be captured contemporaneously during patient care. Use of an open-source tool supports generalizability to other institutions at minimal cost.
authors.affiliation: Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina 27705, USA.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Ferranti
authors.forename: William
authors.initials: W
authors.lastname: Gilbert
authors.forename: Jonathan
authors.initials: J
authors.lastname: McCall
authors.forename: Howard
authors.initials: H
authors.lastname: Shang
authors.forename: Tanya
authors.initials: T
authors.lastname: Barros
authors.forename: Monica M
authors.initials: MM
authors.lastname: Horvath
mesh_terms: D001249:Asthma; D002986:Clinical Trials as Topic; D003195:Computer Communication Networks; D019033:Delivery of Health Care, Integrated; D057208:Health Level Seven; D006801:Humans; D020407:Internet; D009657:North Carolina; D053918:Papillomavirus Vaccines; D018579:Patient Selection
chemical_list: D053918:Papillomavirus Vaccines