Telehealth Fatigue: Is It Real? What Should Be Done?
Date
2024-01
Journal Title
Journal ISSN
Volume Title
Citation Stats
Attention Stats
Abstract
This commentary article discusses the recent trends and changes in popularity of telehealth usage as well as the most recent efforts to redefine telehealth value and usability. Six strategies to improve the patient experience and increase telehealth acceptance by overcoming simultaneous barriers are presented, which include (1) creating a new healthcare paradigm using telehealth, (2) scheduling the telehealth visit, (3) preparing for the telehealth visit, (4) conducting the telehealth visit, (5) using data and biomarkers, and (6) providing digital equity. With the application of these strategies, we believe that the recent decline in the popularity of telehealth can be reversed.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Huang, Jingtong, Andrea M Yeung, Leslie A Eiland, Erich S Huang, Jennifer K Raymond and David C Klonoff (2024). Telehealth Fatigue: Is It Real? What Should Be Done?. Journal of diabetes science and technology, 18(1). pp. 196–200. 10.1177/19322968221127253 Retrieved from https://hdl.handle.net/10161/33621.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
Erich Senin Huang
Former Chief Data Officer for Quality, Duke Health
Former Director of Duke Forge
Former Director of Duke Crucible
Former Assistant Dean for Biomedical Informatics
Dr. Huang is currently Associate Chief Clinical Officer for Informatics & Technology at Verily (Google's life sciences subsidiary), and is now adjunct faculty at Duke. Dr. Huang’s research interests span applied machine learning, research provenance and data infrastructure. Projects include building data provenance tools funded by the NIH’s Big Data to Knowledge program, regulatory science funded by the Burroughs Wellcome Foundation. Applied machine learning applications include “Deep Care Management” a highly interdisciplinary project with Duke Connected Care, Duke’s Accountable Care Organization, that integrates claims and EHR data for predicting unplanned admissions and risk stratifying patients for case management; CALYPSO, a collaboration with the Department of Surgery for utilizing machine learning to predict surgical complications. My team is also building the data platform for the Department of Surgery's "1000 Patients Project" an intensive biospecimen and biomarker study based around patients undergoing the controlled injury of surgery.
As Director of Duke Forge, Dr. Huang built a data science culture and infrastructure across Duke University that focused on actionable health data science. The Forge emphasized scientific rigor, awareness that technology does not supersede clinicians’ responsibilities and human relationship with their patients, and the role of data science in society.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.