Abstract WP93: Providing Stroke Reports to Emergency Medical Services (EMS) Agencies Improves Data Quality in Michigan's Statewide EMS Data Repository

Abstract

Intro: The Michigan Stroke Program (MiSP) monitors statewide EMS stroke care performance and data quality. Starting in 2018, quarterly performance and outcome benchmark data were shared with EMS agency partners to support prehospital quality improvement (QI) for stroke patients. Objective: To improve EMS data quality and prehospital stroke care performance. Methods: This is a retrospective before and after study of the impact of tailored QI interventions to improve EMS compliance with three prehospital stroke quality metrics selected by MiSP EMS partners: (prehospital stroke scale documentation, last known well documentation, and prehospital notification). Five MiSP EMS partners participated in the intervention which consisted of provision of quarterly performance reports generated from linked data from Michigan’s EMS Information System and the Michigan Stroke Registry. The MiSP team reviewed agency performance with EMS leadership to select the target measures for intervention and then assisted in development of a QI plan to improve agency performance. Measure compliance was compared from three months prior to and six months after data quality solutions were implemented. Results: Through data sharing and communication with EMS agencies and EMS software data vendors, common themes were identified related to poor data quality beginning in January 2020. A sample of agencies and resolutions to address these issues are displayed in the Table. Compliance with the targeted metric improved significantly at each agency at three and six months following intervention. Conclusions: Analysis of EMS data and sharing performance data directly with EMS agency partners identified correctable data quality issues negatively impacting EMS quality measures. Correcting these issues led to dramatic and sustained improvement in EMS quality metric compliance. This approach may serve as a model for improving the accuracy of EMS performance data in state-level EMS registries.