Implementation Strategies for Telestroke: A Qualitative Study of Telestroke Networks in North Carolina.

Background: Telestroke services allow under-resourced hospitals to gain access to stroke specialists to improve the timeliness and quality of stroke care. However, limited research is available on how telestroke networks are developed, implemented, and sustained. Understanding the process of telestroke network implementation is critical for developing implementation guidance and for evaluating determinants of implementation effectiveness. Objective: This study examines the adoption decision process and strategies employed during telestroke network development, implementation, and sustainability. Research Design: We interviewed representatives from five telestroke networks in North Carolina. Each network consisted of a distant site from which stroke consultation was provided and multiple originating sites at which the patient presented. Subjects: The sample included 24 telestroke representatives (i.e., 5 network representatives and 19 hospital representatives) and 4 hospital representatives who do not participate in telestroke (i.e., nonadopters). Measures: The qualitative measures used in this study were based on Roger's stages of the innovation process in organizations. Stages included agenda setting and matching (pre-implementation), restructuring, redefining, and clarifying (implementation), and routinizing (sustainability). Results: Distant and originating sites employed various strategies in the pre-implementation, implementation, and sustainability stages. Although there are many commonalities across networks, there are also important differences, for example in terms of network structure, quality monitoring, and performance feedback. Some nonadopter hospitals reported difficulty accessing information about telestroke, suggesting that some hospitals are not reached by telestroke network marketing efforts. Conclusions: Identifying and/or tailoring strategies to support the needs of hospitals in different telestroke network models should be a priority for future research.