Eve-Lynn Nelson1, Edward Alan Miller, Kiley A Larson. 1. KU Center for Telemedicine & Telehealth, The University of Kansas Medical Center, Mailstop 1048, 2012 Wahl Annex, 3901 Rainbow Blvd., Kansas City, KS 66160-7171, United States. enelson2@kumc.edu
Abstract
OBJECTIVE: This study's purpose was to adapt the Roter Interaction Analysis System (RIAS) for telemedicine clinics and to investigate the adapted measure's reliability. The study also sought to better understand the volume of technology-related utterance in established telemedicine clinics and the feasibility of using the measure within the telemedicine setting. This initial evaluation is a first step before broadly using the adapted measure across technologies and raters. METHODS: An expert panel adapted the RIAS for the telemedicine context. This involved accounting for all consultation participants (patient, provider, presenter, family) and adding technology-specific subcategories. Ten new and 36 follow-up telemedicine encounters were videotaped and double coded using the adapted RIAS. These consisted primarily of follow-up visits (78.0%) involving patients, providers, presenters, and other parties. Reliability was calculated for those categories with 15 or more utterances. RESULTS: Traditional RIAS categories related to socioemotional and task-focused clusters had fair to excellent levels of reliability in the telemedicine setting. Although there were too few utterances to calculate the reliability of the specific technology-related subcategories, the summary technology-related category proved reliable for patients, providers, and presenters. Overall patterns seen in traditional patient-provider interactions were observed, with the number of provider utterances far exceeding patient, presenter, and family utterances, and few technology-specific utterances. CONCLUSION: The traditional RIAS is reliable when applied across multiple participants in the telemedicine context. Reliability of technology-related subcategories could not be evaluated; however, the aggregate technology-related cluster was found to be reliable and may be especially relevant in understanding communication patterns with patients new to the telemedicine setting. Use of the RIAS instrument is encouraged to facilitate comparison between traditional, face-to-face clinics and telemedicine; among diverse consultation mediums and technologies; and across different specialties. Future research is necessary to further investigate the reliability and validity of adding technology-related subcategories to the RIAS. The limited number of technology-related utterances, however, implies a certain degree of comfort with two-way interactive video consultation among study participants. PRACTICE IMPLICATIONS: Telemedicine continues to increase access to healthcare. The technology-related categories of the adapted RIAS were reliable when aggregated, thereby providing a tool to better understand how telemedicine affects provider-patient communication and outcomes.
OBJECTIVE: This study's purpose was to adapt the Roter Interaction Analysis System (RIAS) for telemedicine clinics and to investigate the adapted measure's reliability. The study also sought to better understand the volume of technology-related utterance in established telemedicine clinics and the feasibility of using the measure within the telemedicine setting. This initial evaluation is a first step before broadly using the adapted measure across technologies and raters. METHODS: An expert panel adapted the RIAS for the telemedicine context. This involved accounting for all consultation participants (patient, provider, presenter, family) and adding technology-specific subcategories. Ten new and 36 follow-up telemedicine encounters were videotaped and double coded using the adapted RIAS. These consisted primarily of follow-up visits (78.0%) involving patients, providers, presenters, and other parties. Reliability was calculated for those categories with 15 or more utterances. RESULTS: Traditional RIAS categories related to socioemotional and task-focused clusters had fair to excellent levels of reliability in the telemedicine setting. Although there were too few utterances to calculate the reliability of the specific technology-related subcategories, the summary technology-related category proved reliable for patients, providers, and presenters. Overall patterns seen in traditional patient-provider interactions were observed, with the number of provider utterances far exceeding patient, presenter, and family utterances, and few technology-specific utterances. CONCLUSION: The traditional RIAS is reliable when applied across multiple participants in the telemedicine context. Reliability of technology-related subcategories could not be evaluated; however, the aggregate technology-related cluster was found to be reliable and may be especially relevant in understanding communication patterns with patients new to the telemedicine setting. Use of the RIAS instrument is encouraged to facilitate comparison between traditional, face-to-face clinics and telemedicine; among diverse consultation mediums and technologies; and across different specialties. Future research is necessary to further investigate the reliability and validity of adding technology-related subcategories to the RIAS. The limited number of technology-related utterances, however, implies a certain degree of comfort with two-way interactive video consultation among study participants. PRACTICE IMPLICATIONS: Telemedicine continues to increase access to healthcare. The technology-related categories of the adapted RIAS were reliable when aggregated, thereby providing a tool to better understand how telemedicine affects provider-patient communication and outcomes.
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