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Title: | Nurses' and community support workers' experience of telehealth: A longitudinal case study |
Authors: | Sharma, U Clarke, M |
Keywords: | Experience of threat;Telehealth;Nurses;Community support workers;Interpretative phenomenological analysis (IPA) |
Issue Date: | 2014 |
Publisher: | Biomed Central Ltd |
Citation: | BMC Health Services Research, 14, Article no. 164, 2014 |
Abstract: | Background - Introduction of telehealth into the healthcare setting has been recognised as a service that might be experienced as disruptive. This paper explores how this disruption is experienced. Methods - In a longitudinal qualitative study, we conducted focus group discussions prior to and semi structured interviews post introduction of a telehealth service in Nottingham, U.K. with the community matrons, congestive heart failure nurses, chronic obstructive pulmonary disease nurses and community support workers that would be involved in order to elicit their preconceptions and reactions to the implementation. Results - Users experienced disruption due to the implementation of telehealth as threatening. Three main factors add to the experience of threat and affect the decision to use the technology: change in clinical routines and increased workload; change in interactions with patients and fundamentals of face-to-face nursing work; and change in skills required with marginalisation of clinical expertise. Conclusion - Since the introduction of telehealth can be experienced as threatening, managers and service providers should aim at minimising the disruption caused by taking the above factors on board. This can be achieved by employing simple yet effective measures such as: providing timely, appropriate and context specific training; provision of adequate technical support; and procedures that allow a balance between the use of telehealth and personal visit by nurses delivering care to their patients. |
Description: | Copyright © 2014 Sharma and Clarke; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. This article has been made available through the Brunel Open Access Publishing Fund. |
URI: | http://www.biomedcentral.com/1472-6963/14/164 http://bura.brunel.ac.uk/handle/2438/8819 |
DOI: | http://dx.doi.org/10.1186/1472-6963-14-164 |
ISSN: | 1472-6963 |
Appears in Collections: | Computer Science Brunel OA Publishing Fund Dept of Computer Science Research Papers |
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