ArticleHeart rhythm O22020
Digital health in electrophysiology and the COVID-19 global pandemic.
Article in Heart rhythm O2, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Patient Outcomes Associated with the First Remote Monitoring Experience of Cardiac Implantable Electronic Devices in South Korea.Clinical interventions in aging · 2023Article
- Role of Digital Health During Coronavirus Disease 2019 Pandemic and Future Perspectives.Cardiac electrophysiology clinics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The tools of digital health are facilitating a much-needed paradigm shift to a more patient-centric health care delivery system, yet our health care infrastructure is firmly rooted in a 20th-century model that was not designed to receive medical data from outside the traditional medical environment. COVID-19 has accelerated this adoption and illustrated the challenges that lie ahead as we make this shift. The diverse ecosystem of digital health tools share 1 feature in common: they generate data that must be processed, triaged, acted upon, and incorporated into the longitudinal electronic health record. Critical abnormal findings must be identified and acted upon rapidly, while semi-urgent and noncritical data and trends may be reviewed within a less urgent timeline. Clinically irrelevant findings, which presently comprise a significant percentage of the alerts, ideally would be removed to optimize the high-cost, high-value resource (ie, the clinicians' attention and time). We need to transform our established health care infrastructure, technologies, and workflows to be able to safely, effectively, and efficiently manage the vast quantities of data that these tools will generate. This must include new technologies from industry as well as expert consensus documents from medical specialty societies, including the Heart Rhythm Society. Ultimately, research will be fundamental to inform effective development and implementation of these tools.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.