1086Methodological challenges using routine aggregated data in a primary care implementation trial on opioid prescribing. (2nd September 2021) - Farragher, Tracey; Alderson, Sarah; Carder, Paul; Willis, Tom; Foy, Robbie
Abstract: Focus of Presentation: There is international concern over rising trends in opioid prescribing, largely attributed to prescribing for chronic non-cancer pain. We conducted a controlled interrupted time series study on anonymised, aggregated practice data to evaluate the effect of the Campaign to Reduce Opioid Prescribing (CROP) in reducing the number of patients taking opioid medication in West Yorkshire UK practices targeted by the feedback intervention, compared to practices outside of West Yorkshire. We will discuss the methodological challenges addressed in the collection and analysis of these data, and the implications for using routine data in trials. Findings: Primary care data sources for feedback interventions include large-scale databases (General Practice Research Database), high-level nationally gathered databases (OpenPrescribing.com) or data extracted directly from electronic health records (EHR). We will discuss the implications of the different sources of data and compare the results from each, in understanding the impact of the feedback intervention of reducing opioid prescribing over time. The consequences of the heterogeneity of the data sources on the interrupted time series analysis undertaken will also be discussed and solutions outlined. Conclusions/Implications: Routine data are heterogeneous, with different purposes, structures and collection methods, which have considerable implications on their use, analysis and interpretation. Researchers need to understand that the utility of routine data sources have implications (both practically and methodologically) in conducting pragmatic trials, which should be considered when planning and conducting future studies using routine data.