Secular trends in diagnostic code density in electronic healthcare data from health care systems in the Vaccine Safety Datalink Project

摘要: 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 number of per encounter regardless status referred as diagnostic code density, by healthcare setting, age, condition eight large health systems Vaccine Safety Datalink project during 2001–2009. An increasing trend density was observed all settings age groups, with variations across sites. Sudden increases were at certain sites when changes coding policies or data inclusion criteria took place. When an historical comparator, increased over time may generate low expected rates (based on data) high current data), suggesting a false positive association between AEFI. The ongoing monitoring can provide guidance study design choice appropriate comparison groups. It also be used ensure quality allow timely correction errors active surveillance system.