Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose - Emerson, Scott D.; McLinden, Taylor; Sereda, Paul; Yonkman, Amanda M.; Trigg, Jason; Peterson, Sandra; Hogg, Robert S.; Salters, Kate A.; Lima, Viviane D.; Barrios, Rolando (International Journal of Population Data Science, 2024)
The use of routinely collected administrative health data for research can provide unique insights to inform decision-making and, ultimately, support better public health outcomes. Yet, since these data are primarily collected to administer healthcare service delivery, challenges exist when using such data for secondary purposes, namely epidemiologic research. Many of these challenges stem from the researcher's lack of control over the quality and consistency of data collection, and - furthermore - a lessened understanding of the data being analyzed. That said, we assert that these challenges can be partly mitigated through careful, systematic use of these data in epidemiologic research. This article presents considerations derived from experiences analyzing administrative health data (e.g., healthcare practitioner billings, hospitalizations, and prescription medication data) in the Canadian province of British Columbia (population of over 5 million in 2024), though we believe the underlying principles generalize beyond this region. Key considerations were organized around four themes: 1) Know the data and their primary use (understand their scope and limitations); 2) Understand classification and coding systems (appreciate the nuances regarding classification systems, versions, how they are employed in the primary uses of the data, and querying the values); 3) Transform data into meaningful forms (process data and apply identification algorithms, when necessary); 4) Recognize the importance of validity when defining analytic variables (make meaningful inferences based on data/algorithms). Although this article is not an exhaustive list of all considerations, we believe that it will provide pragmatic insights for those interested in leveraging administrative health data for epidemiologic research.