Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study
BackgroundWith 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 bet...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2021-08-01
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| Series: | JMIR Medical Informatics |
| Online Access: | https://medinform.jmir.org/2021/8/e27977 |
| _version_ | 1797735709858070528 |
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| author | Kristin Nicole Gmunder Jose W Ruiz Dido Franceschi Maritza M Suarez |
| author_facet | Kristin Nicole Gmunder Jose W Ruiz Dido Franceschi Maritza M Suarez |
| author_sort | Kristin Nicole Gmunder |
| collection | DOAJ |
| description |
BackgroundWith 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.
ObjectiveThe 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.
MethodsData 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.
ResultsUsing 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.
ConclusionsThe 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. |
| first_indexed | 2024-03-12T13:03:01Z |
| format | Article |
| id | doaj.art-01e2c15deed146a0a734f874bc2ac5c4 |
| institution | Directory Open Access Journal |
| issn | 2291-9694 |
| language | English |
| last_indexed | 2024-03-12T13:03:01Z |
| publishDate | 2021-08-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Medical Informatics |
| spelling | doaj.art-01e2c15deed146a0a734f874bc2ac5c42023-08-28T18:35:17ZengJMIR PublicationsJMIR Medical Informatics2291-96942021-08-0198e2797710.2196/27977Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort StudyKristin Nicole Gmunderhttps://orcid.org/0000-0001-7529-4929Jose W Ruizhttps://orcid.org/0000-0002-6234-7865Dido Franceschihttps://orcid.org/0000-0002-2210-069XMaritza M Suarezhttps://orcid.org/0000-0003-4317-2438 BackgroundWith 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. ObjectiveThe 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. MethodsData 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. ResultsUsing 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. ConclusionsThe 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.https://medinform.jmir.org/2021/8/e27977 |
| spellingShingle | Kristin Nicole Gmunder Jose W Ruiz Dido Franceschi Maritza M Suarez Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study JMIR Medical Informatics |
| 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 |
| url | https://medinform.jmir.org/2021/8/e27977 |
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