title: Secular trends in diagnostic code density in electronic healthcare data from health care systems in the Vaccine Safety Datalink project.
abstract: Large observational vaccine safety studies often use automated diagnoses extracted from medical care databases to identify pre-specified potential adverse events following immunization (AEFI). We assessed the secular trends and variability in the number of diagnoses per encounter regardless of immunization status referred as diagnostic code density, by healthcare setting, age, and pre-specified condition in eight large health care systems of the Vaccine Safety Datalink project during 2001-2009. An increasing trend in diagnostic code density was observed in all healthcare settings and age groups, with variations across the sites. Sudden increases in diagnostic code density were observed at certain sites when changes in coding policies or data inclusion criteria took place. When vaccine safety studies use an historical comparator, the increased diagnostic code density over time may generate low expected rates (based on historical data) and high observed rates (based on current data), suggesting a false positive association between a vaccine and AEFI. The ongoing monitoring of the diagnostic code density can provide guidance on study design and choice of appropriate comparison groups. It can also be used to ensure data quality and allow timely correction of errors in an active safety surveillance system.
authors.affiliation: Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States. Rulin.C.Hechter@kp.org
authors.forename: Rulin C
authors.initials: RC
authors.lastname: Hechter
authors.forename: Lei
authors.initials: L
authors.lastname: Qian
authors.forename: Lina S
authors.initials: LS
authors.lastname: Sy
authors.forename: Sharon K
authors.initials: SK
authors.lastname: Greene
authors.forename: Eric S
authors.initials: ES
authors.lastname: Weintraub
authors.forename: Allison L
authors.initials: AL
authors.lastname: Naleway
authors.forename: Ali
authors.initials: A
authors.lastname: Rowhani-Rahbar
authors.forename: James G
authors.initials: JG
authors.lastname: Donahue
authors.forename: Matthew F
authors.initials: MF
authors.lastname: Daley
authors.forename: Gabriela
authors.initials: G
authors.lastname: Vazquez-Benitez
authors.forename: Marlene M
authors.initials: MM
authors.lastname: Lugg
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Jacobsen
mesh_terms: D000293:Adolescent; D000328:Adult; D016907:Adverse Drug Reaction Reporting Systems / Q000592:standards / Q000706:statistics & numerical data* / Q000639:trends; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data* / Q000639:trends; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D011786:Quality Control; D014612:Vaccines / Q000009:adverse effects*; D055815:Young Adult
chemical_list: D014612:Vaccines