Show simple item record

Putting the network to work: Learning networks in rapid response situations

dc.contributor.authorVinson, Alexandra H.
dc.date.accessioned2021-02-04T21:50:08Z
dc.date.available2022-02-04 16:50:07en
dc.date.available2021-02-04T21:50:08Z
dc.date.issued2021-01
dc.identifier.citationVinson, Alexandra H. (2021). "Putting the network to work: Learning networks in rapid response situations." Learning Health Systems 5(1): n/a-n/a.
dc.identifier.issn2379-6146
dc.identifier.issn2379-6146
dc.identifier.urihttps://hdl.handle.net/2027.42/166192
dc.description.abstractIntroductionThe rapid response to COVID‐19 has necessitated infrastructural development and reorientation in order to safely meet patient care needs.MethodsA qualitative case study was constructed within a larger ethnographic field study. Document collection and fieldnotes and recordings from nonparticipant observation of network activities were compiled and chronologically ordered to chart the network’s response to changes in epilepsy care resulting from COVID‐19 and the rapid transition to telemedicine.ResultsThe network’s response to COVID‐19 was characterized by a predisposition to action, the role of sharing as both a group practice and shared value, and the identification of improvement science as the primary contribution of the group within the larger epilepsy community’s response to COVID‐19. The findings are interpreted as an example of how group culture can shape action via a transparent and mundane shared infrastructure.ConclusionsThe case of one multi‐stakeholder epilepsy Learning Network provides an example of the use of infrastructure that is shaped by the group’s culture. These findings contribute to the development of a social theory of infrastructure within Learning Health Systems.
dc.publisherWiley Periodicals, Inc.
dc.subject.otherCOVID‐19
dc.subject.otherinfrastructure
dc.subject.otherlearning health system
dc.subject.otherlearning network
dc.subject.othertelemedicine
dc.titlePutting the network to work: Learning networks in rapid response situations
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBiomedical Health Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/166192/1/lrh210251.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/166192/2/lrh210251_am.pdf
dc.identifier.doi10.1002/lrh2.10251
dc.identifier.doihttps://dx.doi.org/10.7302/115
dc.identifier.sourceLearning Health Systems
dc.identifier.citedreferenceKarasti H, Millerand F, Hine C, Bowker G. Knowledge infrastructures—part I. Sci Technol Stud. 2016; 29 ( 1 ): 2 ‐ 12.
dc.identifier.citedreferenceStar SL. The ethnography of infrastructure. Am Behav Sci. 1999; 43 ( 3 ): 377 ‐ 391.
dc.identifier.citedreferenceStar L, Ruhleder K. Steps towards an ecology of infrastructure: complex problems in design and access for large‐scale collaborative systems. Inf Syst Res. 1996; 7 ( 1 ): 253 ‐ 264.
dc.identifier.citedreferencePlatt J, Wienroth M, Raj M. An analysis of the learning health system in its first decade in practice: scoping review. J Med Internet Res. 2020; 22 ( 3 ): e17026.
dc.identifier.citedreferenceSeid M, Hartley D, Dellal G, Myers S, Margolis P. Organizing for collaboration: an actor‐oriented architecture in ImproveCareNow. Learn Health Syst. 2020; 4: e10205.
dc.identifier.citedreferenceBraun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006; 3: 77 ‐ 101.
dc.identifier.citedreferenceFine GA, Hallett T. Group cultures and the everyday life of organizations: interaction orders and meso‐analysis. Organ Stud. 2014; 35 ( 12 ): 1773 ‐ 1792.
dc.identifier.citedreferenceVertesi J. Seamful spaces: heterogeneous infrastructures in interaction. Sci Technol Hum Values. 2014; 39 ( 2 ): 264 ‐ 284.
dc.identifier.citedreferenceBritto M, Fuller S, Kaplan H, et al. Using a network organisational architecture to support the development of learning healthcare systems. BMJ Qual Saf. 2018; 27: 937 ‐ 946.
dc.identifier.citedreferenceMann D, Chen J, Chunara R, Testa P, Nov O. COVID‐19 transforms health care through telemedicine: evidence from the field. J Am Med Inform Assoc. 2020; 0 ( 0 ): 1 ‐ 4.
dc.identifier.citedreferenceHollander J, Carr B. Virtually perfect? Telemedicine for Covid‐19. N Engl J Med. 2020; 382: 1679 ‐ 1681.
dc.identifier.citedreferenceOhannessian R, Duong TA, Odone A. Global telemedicine implementation and integration within health systems to fight the COVID‐19 pandemic: a call to action. JMIR Public Health Surveill. 2020; 6 ( 2 ): e18810.
dc.identifier.citedreferenceDingwall R, Hoffman L, Staniland K. Introduction: why a Sociology of pandemics? Sociol Health Illn. 2013; 35 ( 2 ): 167 ‐ 173.
dc.identifier.citedreferenceLarkin B. The politics and poetics of infrastructure. Annu Rev Anthropol. 2013; 42: 327 ‐ 343.
dc.working.doi10.7302/115en
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.