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Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study
BACKGROUND: With COVID-19 there was a rapid and abrupt rise in telemedicine implementation often without sufficient time for providers or patients to adapt. As telemedicine visits are likely to continue to play an important role in health care, it is crucial to strive for a better understanding of h...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404776/ https://www.ncbi.nlm.nih.gov/pubmed/34254936 http://dx.doi.org/10.2196/27977 |
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author | Gmunder, Kristin Nicole Ruiz, Jose W Franceschi, Dido Suarez, Maritza M |
author_facet | Gmunder, Kristin Nicole Ruiz, Jose W Franceschi, Dido Suarez, Maritza M |
author_sort | Gmunder, Kristin Nicole |
collection | PubMed |
description | BACKGROUND: With COVID-19 there was a rapid and abrupt rise in telemedicine implementation often without sufficient time for providers or patients to adapt. As telemedicine visits are likely to continue to play an important role in health care, it is crucial to strive for a better understanding of how to ensure completed telemedicine visits in our health system. Awareness of these barriers to effective telemedicine visits is necessary for a proactive approach to addressing issues. OBJECTIVE: The objective of this study was to identify variables that may affect telemedicine visit completion in order to determine actions that can be enacted across the entire health system to benefit all patients. METHODS: Data were collected from scheduled telemedicine visits (n=362,764) at the University of Miami Health System (UHealth) between March 1, 2020 and October 31, 2020. Descriptive statistics, mixed effects logistic regression, and random forest modeling were used to identify the most important patient-agnostic predictors of telemedicine completion. RESULTS: Using descriptive statistics, struggling telemedicine specialties, providers, and clinic locations were identified. Through mixed effects logistic regression (adjusting for clustering at the clinic site level), the most important predictors of completion included previsit phone call/SMS text message reminder status (confirmed vs not answered) (odds ratio [OR] 6.599, 95% CI 6.483-6.717), MyUHealthChart patient portal status (not activated vs activated) (OR 0.315, 95% CI 0.305-0.325), provider’s specialty (primary care vs medical specialty) (OR 1.514, 95% CI 1.472-1.558), new to the UHealth system (yes vs no) (OR 1.285, 95% CI 1.201-1.374), and new to provider (yes vs no) (OR 0.875, 95% CI 0.859-0.891). Random forest modeling results mirrored those from logistic regression. CONCLUSIONS: The highest association with a completed telemedicine visit was the previsit appointment confirmation by the patient via phone call/SMS text message. An active patient portal account was the second strongest variable associated with completion, which underscored the importance of patients having set up their portal account before the telemedicine visit. Provider’s specialty was the third strongest patient-agnostic characteristic associated with telemedicine completion rate. Telemedicine will likely continue to have an integral role in health care, and these results should be used as an important guide to improvement efforts. As a first step toward increasing completion rates, health care systems should focus on improvement of patient portal usage and use of previsit reminders. Optimization and intervention are necessary for those that are struggling with implementing telemedicine. We advise setting up a standardized workflow for staff. |
format | Online Article Text |
id | pubmed-8404776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84047762021-09-14 Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study Gmunder, Kristin Nicole Ruiz, Jose W Franceschi, Dido Suarez, Maritza M JMIR Med Inform Original Paper BACKGROUND: With COVID-19 there was a rapid and abrupt rise in telemedicine implementation often without sufficient time for providers or patients to adapt. As telemedicine visits are likely to continue to play an important role in health care, it is crucial to strive for a better understanding of how to ensure completed telemedicine visits in our health system. Awareness of these barriers to effective telemedicine visits is necessary for a proactive approach to addressing issues. OBJECTIVE: The objective of this study was to identify variables that may affect telemedicine visit completion in order to determine actions that can be enacted across the entire health system to benefit all patients. METHODS: Data were collected from scheduled telemedicine visits (n=362,764) at the University of Miami Health System (UHealth) between March 1, 2020 and October 31, 2020. Descriptive statistics, mixed effects logistic regression, and random forest modeling were used to identify the most important patient-agnostic predictors of telemedicine completion. RESULTS: Using descriptive statistics, struggling telemedicine specialties, providers, and clinic locations were identified. Through mixed effects logistic regression (adjusting for clustering at the clinic site level), the most important predictors of completion included previsit phone call/SMS text message reminder status (confirmed vs not answered) (odds ratio [OR] 6.599, 95% CI 6.483-6.717), MyUHealthChart patient portal status (not activated vs activated) (OR 0.315, 95% CI 0.305-0.325), provider’s specialty (primary care vs medical specialty) (OR 1.514, 95% CI 1.472-1.558), new to the UHealth system (yes vs no) (OR 1.285, 95% CI 1.201-1.374), and new to provider (yes vs no) (OR 0.875, 95% CI 0.859-0.891). Random forest modeling results mirrored those from logistic regression. CONCLUSIONS: The highest association with a completed telemedicine visit was the previsit appointment confirmation by the patient via phone call/SMS text message. An active patient portal account was the second strongest variable associated with completion, which underscored the importance of patients having set up their portal account before the telemedicine visit. Provider’s specialty was the third strongest patient-agnostic characteristic associated with telemedicine completion rate. Telemedicine will likely continue to have an integral role in health care, and these results should be used as an important guide to improvement efforts. As a first step toward increasing completion rates, health care systems should focus on improvement of patient portal usage and use of previsit reminders. Optimization and intervention are necessary for those that are struggling with implementing telemedicine. We advise setting up a standardized workflow for staff. JMIR Publications 2021-08-27 /pmc/articles/PMC8404776/ /pubmed/34254936 http://dx.doi.org/10.2196/27977 Text en ©Kristin Nicole Gmunder, Jose W Ruiz, Dido Franceschi, Maritza M Suarez. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 27.08.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Gmunder, Kristin Nicole Ruiz, Jose W Franceschi, Dido Suarez, Maritza M Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title | Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title_full | Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title_fullStr | Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title_full_unstemmed | Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title_short | Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study |
title_sort | factors to effective telemedicine visits during the covid-19 pandemic: cohort study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404776/ https://www.ncbi.nlm.nih.gov/pubmed/34254936 http://dx.doi.org/10.2196/27977 |
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