Abstract WP333: Utilizing Data to Drive Stroke Program Management

Introduction: There is a lack of standard data management tools for neurovascular service lines and stroke programs. Many hospitals use “home grown” spreadsheets or upload to various registries which are designed more toward research initiatives than daily operations. Hypothesis: Installation of a dedicated Neurovascular Information System (NVIS), especially when electronically interfaced with other systems, will result in improved efficiency in operating a stroke program and/or neurovascular service line. Methods: A large health system in Tennessee has installed an NVIS for daily use within its Comprehensive Stroke Center. The system has been interfaced with other information systems in the hospital to support automated data entry. The service line directors and physician leaders have monitored data related to time spent in various aspects of program management (e.g. data entry/management, interaction with staff, interaction with patients, etc.) to understand how the use of a system can impact resource allocation. The system is being utilized through mobile technology, such as tablets, and static monitoring units in identified key locations. Results: The data collection time required has been reduced by more than 50% because of the system’s automated collection and reporting features. The leaders of the service line have also developed more detailed, data-driven dashboards which are being used for management decisions. Education is also data-driven as any process fall-outs are revealed through program dashboards. Conclusion: Utilization of a dedicated NVIS reverses the narrative related to stroke program management. It has allowed the program leaders to use data to drive programmatic decisions and development, rather than being tied to data entry requirements and struggling to enter post-dated information. This novel approach continues to support research endeavors and registry participation, while increasing efficiency and improving access to meaningful analytics.