title: Should quality goals be defined for multicenter laboratory testing? Lessons learned from a pilot survey on a national surveillance program for diabetes.
abstract: OBJECTIVE
  Robust laboratory protocols and stringent quality control (QC) procedures are essential for meaningful collection of data from multiple sites in large-scale population-based studies. Failure to design and implement an effective QC program not only adversely affects the scientific outcome, but also affects public confidence in the acceptability of the data.
  
  
  METHODS
  A pilot survey was conducted to assess the analytical performance of multicenter plasma glucose measurements in a national surveillance program for diabetes in China.
  
  
  METHODS
  Quality goals of the imprecision in terms of coefficient of variation (CV) and total analytical error (TEa) were defined based on the Clinical Laboratory Improvement Amendments (CLIA) criteria for acceptable performance of proficiency testing (PT) for plasma glucose using commercial QC preparations.
  
  
  METHODS
  A web-based internal QC (IQC) program was established to monitor the analytical performance of the 302 centers participating in the survey.
  
  
  RESULTS
  The participation rate was 96% (289/302). Statistical analysis showed that the percentage of centers meeting the acceptable specifications of CV ≤5.0% and TEa ≤10% using the CLIA PT criteria was 91.7% while 76.4% of laboratories achieved the goals for desirable performance of CV ≤2.9% and TEa ≤6.9%, as proposed by the Laboratory Medicine Practice Guidelines for the management of diabetes mellitus based on biological criteria.
  
  
  CONCLUSIONS
  Communications and training are important in ensuring the data integrity of multicenter population-based studies. Performance verification and IQC programs should be implemented to help identify centers that can fulfill the eligibility criteria to perform laboratory analyses.
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
authors.forename: Limin
authors.initials: L
authors.lastname: Wang
authors.affiliation: KingMed Diagnostics, Guangzhou 510330, China.
authors.forename: Nanxun
authors.initials: N
authors.lastname: Mo
authors.affiliation: KingMed Diagnostics, Guangzhou 510330, China Pro Q Consulting Services, Hong Kong SAR, China.
authors.forename: Richard
authors.initials: R
authors.lastname: Pang
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Deng
authors.affiliation: KingMed Diagnostics, Guangzhou 510330, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.affiliation: KingMed Diagnostics, Guangzhou 510330, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Hu
authors.affiliation: KingMed Diagnostics, Guangzhou 510330, China.
authors.forename: Chaohui
authors.initials: C
authors.lastname: Hu
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
authors.forename: Linhong
authors.initials: L
authors.lastname: Wang
mesh_terms: D001786:Blood Glucose / Q000032:analysis; D019411:Clinical Laboratory Techniques / Q000379:methods / Q000592:standards*; D003920:Diabetes Mellitus / Q000097:blood* / Q000175:diagnosis; D006801:Humans; D009937:Organizational Objectives; D010865:Pilot Projects; D011159:Population Surveillance; D011786:Quality Control; D011787:Quality of Health Care / Q000592:standards*
chemical_list: D001786:Blood Glucose
keywords: chronic noncommunicable diseases; diabetes; multicenter population-based studies; quality control; quality goals; risk factors