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Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics

BACKGROUND: With the growing use of telehealth, understanding factors affecting patient follow-up in traditional and telehealth settings is important. Few data exist examining the use of telehealth compared with traditional settings. Bridging this gap is critical to optimizing telehealth use and red...

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Autores principales: Kemp, Michael T., Liesman, Daniel R., Brown, Craig S., Williams, Aaron M., Biesterveld, Ben E., Wakam, Glenn K., Wilson, Jesse K., Alam, Hasan B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: by the American College of Surgeons. Published by Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7470818/
https://www.ncbi.nlm.nih.gov/pubmed/32891797
http://dx.doi.org/10.1016/j.jamcollsurg.2020.08.760
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author Kemp, Michael T.
Liesman, Daniel R.
Brown, Craig S.
Williams, Aaron M.
Biesterveld, Ben E.
Wakam, Glenn K.
Wilson, Jesse K.
Alam, Hasan B.
author_facet Kemp, Michael T.
Liesman, Daniel R.
Brown, Craig S.
Williams, Aaron M.
Biesterveld, Ben E.
Wakam, Glenn K.
Wilson, Jesse K.
Alam, Hasan B.
author_sort Kemp, Michael T.
collection PubMed
description BACKGROUND: With the growing use of telehealth, understanding factors affecting patient follow-up in traditional and telehealth settings is important. Few data exist examining the use of telehealth compared with traditional settings. Bridging this gap is critical to optimizing telehealth use and reducing barriers. STUDY DESIGN: This is a retrospective cohort study of return and postoperative (electronic video [eClinic] and traditional) visits from January 2018 to March 2020 at single tertiary care center. There were 12,359 unique first-encounter patients with 903 eClinic and 11,456 traditional visits; 11,547 patients completed visits, while 812 patients did not show up. Multivariable logistic regression modeling was performed to identify factors associated with no-show. County-level mapping was used to identify patterns in no-show rates. RESULTS: Patients from the eClinic had twice the odds of no-show compared with those from a traditional clinic (p < 0.001). Age was inversely proportional to odds of no-show, with each additional decade associated with a 16% decrease in these odds (p < 0.001). African-American patients had greater odds of no-show compared to Caucasian patients (odds ratio [OR] 2.47; 95% CI 1.95–3.13, p < 0.001). Marital statuses of single and legal separation were associated with higher odds of no-show compared with married marital status (p < 0.001 and p = 0.04, respectively). Minimally invasive and endocrine surgery clinics had lower odds of no-show compared with acute care surgery clinic (p < 0.001 for both). County-level no-show rates demonstrate similar patterns between clinic settings. CONCLUSIONS: Several factors are associated with increased odds of no-show, including the visit being in eClinic. County-level analysis suggests no-show variation is not dependent on geographic location. Understanding these patterns allows for prospective identification of barriers and development of interventions to optimize access and patient care.
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spelling pubmed-74708182020-09-04 Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics Kemp, Michael T. Liesman, Daniel R. Brown, Craig S. Williams, Aaron M. Biesterveld, Ben E. Wakam, Glenn K. Wilson, Jesse K. Alam, Hasan B. J Am Coll Surg Original Scientific Article BACKGROUND: With the growing use of telehealth, understanding factors affecting patient follow-up in traditional and telehealth settings is important. Few data exist examining the use of telehealth compared with traditional settings. Bridging this gap is critical to optimizing telehealth use and reducing barriers. STUDY DESIGN: This is a retrospective cohort study of return and postoperative (electronic video [eClinic] and traditional) visits from January 2018 to March 2020 at single tertiary care center. There were 12,359 unique first-encounter patients with 903 eClinic and 11,456 traditional visits; 11,547 patients completed visits, while 812 patients did not show up. Multivariable logistic regression modeling was performed to identify factors associated with no-show. County-level mapping was used to identify patterns in no-show rates. RESULTS: Patients from the eClinic had twice the odds of no-show compared with those from a traditional clinic (p < 0.001). Age was inversely proportional to odds of no-show, with each additional decade associated with a 16% decrease in these odds (p < 0.001). African-American patients had greater odds of no-show compared to Caucasian patients (odds ratio [OR] 2.47; 95% CI 1.95–3.13, p < 0.001). Marital statuses of single and legal separation were associated with higher odds of no-show compared with married marital status (p < 0.001 and p = 0.04, respectively). Minimally invasive and endocrine surgery clinics had lower odds of no-show compared with acute care surgery clinic (p < 0.001 for both). County-level no-show rates demonstrate similar patterns between clinic settings. CONCLUSIONS: Several factors are associated with increased odds of no-show, including the visit being in eClinic. County-level analysis suggests no-show variation is not dependent on geographic location. Understanding these patterns allows for prospective identification of barriers and development of interventions to optimize access and patient care. by the American College of Surgeons. Published by Elsevier Inc. 2020-12 2020-09-03 /pmc/articles/PMC7470818/ /pubmed/32891797 http://dx.doi.org/10.1016/j.jamcollsurg.2020.08.760 Text en © 2020 by the American College of Surgeons. Published by Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Original Scientific Article
Kemp, Michael T.
Liesman, Daniel R.
Brown, Craig S.
Williams, Aaron M.
Biesterveld, Ben E.
Wakam, Glenn K.
Wilson, Jesse K.
Alam, Hasan B.
Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title_full Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title_fullStr Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title_full_unstemmed Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title_short Factors Associated with Increased Risk of Patient No-Show in Telehealth and Traditional Surgery Clinics
title_sort factors associated with increased risk of patient no-show in telehealth and traditional surgery clinics
topic Original Scientific Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7470818/
https://www.ncbi.nlm.nih.gov/pubmed/32891797
http://dx.doi.org/10.1016/j.jamcollsurg.2020.08.760
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