Grant: Travel Awards - Institute Community Support

Large health administrative datasets provide a unique opportunity to estimate healthcare costs at the population-level, however infectious diseases present a number of unique challenges in accomplishing this objective. To explore these challenges, we used an analysis of the healthcare costs associated with Streptococcus pneumoniae infections as a case study. This analysis was conducted in Ontario, Canada using healthcare utilization data as well as laboratory datasets from local public health agencies and surveillance networks. Retrospective cohorts of infected subjects were matched with uninfected subjects, with attributable costs defined as the mean difference between the costs of the matched pairs. Based on our case study and other related costing projects, we identified 5 primary challenges to estimating the costs of infectious disease using administrative data: (1) identifying infected subjects, (2) defining an accurate index date of infection, (3) minimizing residual confounding when matching to uninfected subjects, (4) defining an appropriate period of time for the accrual of relevant costs, (5) deciding on the most suitable costing framework (e.g. phase-of-care, unadjusted for survival).