title: Linkage, evaluation and analysis of national electronic healthcare data: application to providing enhanced blood-stream infection surveillance in paediatric intensive care.
abstract: BACKGROUND
  Linkage of risk-factor data for blood-stream infection (BSI) in paediatric intensive care (PICU) with bacteraemia surveillance data to monitor risk-adjusted infection rates in PICU is complicated by a lack of unique identifiers and under-ascertainment in the national surveillance system. We linked, evaluated and performed preliminary analyses on these data to provide a practical guide on the steps required to handle linkage of such complex data sources.
  
  
  METHODS
  Data on PICU admissions in England and Wales for 2003-2010 were extracted from the Paediatric Intensive Care Audit Network. Records of all positive isolates from blood cultures taken for children <16 years and captured by the national voluntary laboratory surveillance system for 2003-2010 were extracted from the Public Health England database, LabBase2. "Gold-standard" datasets with unique identifiers were obtained directly from three laboratories, containing microbiology reports that were eligible for submission to LabBase2 (defined as "clinically significant" by laboratory microbiologists). Reports in the gold-standard datasets were compared to those in LabBase2 to estimate ascertainment in LabBase2. Linkage evaluated by comparing results from two classification methods (highest-weight classification of match weights and prior-informed imputation using match probabilities) with linked records in the gold-standard data. BSI rate was estimated as the proportion of admissions associated with at least one BSI.
  
  
  RESULTS
  Reporting gaps were identified in 548/2596 lab-months of LabBase2. Ascertainment of clinically significant BSI in the remaining months was approximately 80-95%. Prior-informed imputation provided the least biased estimate of BSI rate (5.8% of admissions). Adjusting for ascertainment, the estimated BSI rate was 6.1-7.3%.
  
  
  CONCLUSIONS
  Linkage of PICU admission data with national BSI surveillance provides the opportunity for enhanced surveillance but analyses based on these data need to take account of biases due to ascertainment and linkage error. This study provides a generalisable guide for linkage, evaluation and analysis of complex electronic healthcare data.
authors.affiliation: Institute of Child Health, University College London, London, United Kingdom.
authors.forename: Katie
authors.initials: K
authors.lastname: Harron
authors.affiliation: Institute of Child Health, University College London, London, United Kingdom ; Graduate School of Education, University of Bristol, Bristol, United Kingdom.
authors.forename: Harvey
authors.initials: H
authors.lastname: Goldstein
authors.affiliation: Institute of Child Health, University College London, London, United Kingdom.
authors.forename: Angie
authors.initials: A
authors.lastname: Wade
authors.affiliation: Healthcare Associated Infection and Antimicrobial Resistance Department, Public Health England, London, United Kingdom.
authors.forename: Berit
authors.initials: B
authors.lastname: Muller-Pebody
authors.affiliation: Division of Epidemiology, University of Leeds, Leeds, United Kingdom.
authors.forename: Roger
authors.initials: R
authors.lastname: Parslow
authors.affiliation: Institute of Child Health, University College London, London, United Kingdom.
authors.forename: Ruth
authors.initials: R
authors.lastname: Gilbert
mesh_terms: D016470:Bacteremia / Q000453:epidemiology*; D002648:Child; D003625:Data Collection / Q000379:methods*; D057286:Electronic Health Records; D062665:Epidemiological Monitoring; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D015278:Intensive Care Units, Pediatric