Transformation of Data Access Models In BC

IntroductionThe current data access model in BC involves project-specific applications and data provisioning. The timeline from application to provisioning is 6-8 months. Novel initiatives including Program of Research (POR), Core Data Sets (CORE), and Data Reuse are being explored and evaluated. Objectives and ApproachWe aim to develop data provisioning models that improve efficiency and access timelines by reducing process duplication and adopting open and flexible approaches to data use while ensuring data privacy. ResultsPOR allows researchers to access broad programmatic data that fulfills data requirements for multiple thematically-linked projects. While we provision the program data, a research team data manager extracts the project-specific data from the program dataset. A pilot program with two active projects is ongoing. The timeline from application to program data provisioning was 8 months. Project data was delivered in 2-3 months. CORE is a transformative data provisioning model that allows researchers to access entire data sets that contain a group of pre-approved and non-sensitive data variables for the BC population for all available years. This decreases the possibility of variable omission which is prevalent under the existing process. Additionally, this model allows researchers the flexibility to identify their cohort using their preferred methodology. Data Reuse allows re-use of data between similar projects conducted by the same investigator. Projects were surveyed for similar objectives, investigators and data requirements. Similar projects were grouped and analyzed to evaluate pre-implementation timelines. Application to provisioning timeline for one group of six projects ranged from 7-18 months. Post-implementation timelines will be evaluated once Data Reuse is implemented. Conclusion / ImplicationsThese new initiatives have shown promising results in access efficiency and data privacy in the pilot phase. Continuous process and privacy evaluations are involved and ongoing collaborations with the data providers and researchers are required prior to full implementation.