title: Accrual Index: A Real-Time Measure of the Timeliness of Clinical Study Enrollment.
abstract: BACKGROUND
  Achieving timely accrual into clinical research studies remains a challenge for clinical translational research. We developed an evaluation measure, the Accrual Index (AI), normalized for sample size and study duration, using data from the protocol and study management databases. We applied the AI retrospectively and prospectively to assess its utility.
  
  
  METHODS
  Accrual Target, Projected Time to Accrual Completion (PTAC), Evaluable Subjects, Dates of Recruitment Initiation, Analysis, and Completion were defined. AI is (% Accrual Target accrued/% PTAC elapsed). Changes to recruitment practices were described, and data extracted from study management databases.
  
  
  RESULTS
  December 2014 (or final) AI was analyzed for 101 studies initiating recruitment from 2007 to 2014. Median AI was ≥1 for protocols initiating recruitment in 2011, 2013, and 2014. The AI varied widely for studies pre-2013. Studies with AI > 4 utilized convenience samples for recruitment. Data-justified PTAC was refined in 2013-2014 after which the AI range narrowed. Protocol characteristics were not associated with study AI.
  
  
  CONCLUSIONS
  Protocol AI reflects the relative agreement between accrual feasibility assessment (PTAC), and accrual performance, and is affected by recruitment practices. The AI may be useful in managing accountability, modeling accrual, allocating recruitment resources, and testing innovations in recruitment practices.
authors.affiliation: Clinical Research Support Office, The Rockefeller University Center for Clinical and Translational Science, New York, New York, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: Corregano
authors.affiliation: Clinical Research Support Office, The Rockefeller University Center for Clinical and Translational Science, New York, New York, USA.
authors.forename: Katelyn
authors.initials: K
authors.lastname: Bastert
authors.affiliation: Department of Research Design and Biostatistics, The Rockefeller University Center for Clinical and Translational Science, New York, New York, USA.
authors.forename: Joel
authors.initials: J
authors.lastname: Correa da Rosa
authors.affiliation: Clinical Research Support Office, The Rockefeller University Center for Clinical and Translational Science, New York, New York, USA.
authors.forename: Rhonda G
authors.initials: RG
authors.lastname: Kost
mesh_terms: D002986:Clinical Trials as Topic; D006801:Humans; D015233:Models, Statistical; D018579:Patient Selection; D011446:Prospective Studies; D012189:Retrospective Studies; D018401:Sample Size; D013997:Time Factors; D057170:Translational Research, Biomedical / Q000379:methods* / Q000639:trends
keywords: clinical research methods; clinical trial; participant recruitment, clinical research; translational research