Impact of different assumptions on estimates of childhood diseases obtained from health care data: A retrospective cohort study

Abstract

Purpose: Accurate estimates of disease incidence in children are required to support pediatric drug development. Analysis of electronic health care records (EHR) may yield such estimates but pediatric-specific methods are lacking. We aimed to understand the impact of assumptions regarding duration of disease episode and length of run-in period on incidence estimates from EHRs. Methods: Children aged 0 to 17 years (5–17 years for asthma) registered in the Integrated Primary Care Information database between 2002 and 2014 were studied. We tested the impact of the following: maximum duration of disease episode (0, 14, 30, 60, and 90 days) on recurrent diseases (acute otitis media [common] and acute pyelonephritis [rare]); and database run-in period on chronic diseases—asthma (common) and type 1 diabetes (DM) (rare). We calculated incidence rate ratios with 95% confidence intervals and stratified using 1-year age categories. Results: Altogether, 503 495 children were registered. The incidence of acute otitis media was highest in <2-year-old children; using 30 days disease duration as reference, the rate increased with 8% if the duration was 14 days and decreased with 8% when extended to 60 days. Disease duration did not impact acute pyelonephritis (rare). No run-in (to exclude prevalent cases) versus 24-month run-in period overestimated the incidence rate for asthma and DM by a factor of 2. Conclusions: Analysis of EHR allows for estimation of disease incidence in children, but assumptions regarding episode length and run-in period impact the incidence estimates. Such assumptions may be routinely explored.