title: Ongoing monitoring of data clustering in multicenter studies.
abstract: BACKGROUND
  Multicenter study designs have several advantages, but the possibility of non-random measurement error resulting from procedural differences between the centers is a special concern. While it is possible to address and correct for some measurement error through statistical analysis, proactive data monitoring is essential to ensure high-quality data collection.
  
  
  METHODS
  In this article, we describe quality assurance efforts aimed at reducing the effect of measurement error in a recent follow-up of a large cluster-randomized controlled trial through periodic evaluation of intraclass correlation coefficients (ICCs) for continuous measurements. An ICC of 0 indicates the variance in the data is not due to variation between the centers, and thus the data are not clustered by center.
  
  
  RESULTS
  Through our review of early data downloads, we identified several outcomes (including sitting height, waist circumference, and systolic blood pressure) with higher than expected ICC values. Further investigation revealed variations in the procedures used by pediatricians to measure these outcomes. We addressed these procedural inconsistencies through written clarification of the protocol and refresher training workshops with the pediatricians. Further data monitoring at subsequent downloads showed that these efforts had a beneficial effect on data quality (sitting height ICC decreased from 0.92 to 0.03, waist circumference from 0.10 to 0.07, and systolic blood pressure from 0.16 to 0.12).
  
  
  CONCLUSIONS
  We describe a simple but formal mechanism for identifying ongoing problems during data collection. The calculation of the ICC can easily be programmed and the mechanism has wide applicability, not just to cluster randomized controlled trials but to any study with multiple centers or with multiple observers.
authors.affiliation: Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and the Harvard Pilgrim Health Care Institute, Boston, USA.
authors.forename: Lauren B
authors.initials: LB
authors.lastname: Guthrie
authors.forename: Emily
authors.initials: E
authors.lastname: Oken
authors.forename: Jonathan A C
authors.initials: JA
authors.lastname: Sterne
authors.forename: Matthew W
authors.initials: MW
authors.lastname: Gillman
authors.forename: Rita
authors.initials: R
authors.lastname: Patel
authors.forename: Konstantin
authors.initials: K
authors.lastname: Vilchuck
authors.forename: Natalia
authors.initials: N
authors.lastname: Bogdanovich
authors.forename: Michael S
authors.initials: MS
authors.lastname: Kramer
authors.forename: Richard M
authors.initials: RM
authors.lastname: Martin
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D000886:Anthropometry / Q000379:methods*; D001794:Blood Pressure; D002983:Clinical Competence; D016000:Cluster Analysis; D003266:Continuity of Patient Care; D003627:Data Interpretation, Statistical; D004493:Education; D005260:Female; D006801:Humans; D007318:Inservice Training; D008297:Male; D015337:Multicenter Studies as Topic; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D010372:Pediatrics / Q000592:standards*; D010820:Physicians / Q000523:psychology* / Q000592:standards; D010818:Practice Patterns, Physicians' / Q000592:standards*; D011785:Quality Assurance, Health Care / Q000592:standards / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D013223:Statistics as Topic; D016896:Treatment Outcome