Publication Date

2017

Abstract

Background: Stroke telemedicine can reduce healthcare inequities by increasing access to specialists. Successful telemedicine networks require specialists adapting clinical practice to provide remote consultations. Variation in experiences of specialists between different countries is unknown. To support future implementation, we compared perceptions of Australian and United Kingdom specialists providing remote acute stroke consultations. Methods: Specialist participants were identified using purposive sampling from two new services: Australia’s Victorian Stroke Telemedicine Program (n = 6; 2010–13) and the United Kingdom’s Cumbria and Lancashire telestroke network (n = 5; 2010–2012). Semi-structured interviews were conducted pre- and post-implementation, recorded and transcribed verbatim. Deductive thematic and content analysis (NVivo) was undertaken by two independent coders using Normalisation Process Theory to explore integration of telemedicine into practice. Agreement between coders was M = 91%, SD = 9 and weighted average κ = 0.70. Results: Cross-cultural similarities and differences were found. In both countries, specialists described old and new consulting practices, the purpose and value of telemedicine systems, and concerns regarding confidence in the assessment and diagnostic skills of unknown colleagues requesting telemedicine support. Australian specialists discussed how remote consultations impacted on usual roles and suggested future improvements, while United Kingdom specialists discussed system governance, policy and procedures. Conclusion: Australian and United Kingdom specialists reported telemedicine required changes in work practice and development of new skills. Both groups described potential for improvements in stroke telemedicine systems with Australian specialists more focused on role change and the United Kingdom on system governance issues. Future research should examine if cross-cultural variation reflects different models of care and extends to other networks.

Document Type

Open Access Journal Article

Access Rights

Open Access

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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