ArticleJMIR mHealth and uHealth2022
Reimagining Connected Care in the Era of Digital Medicine.
Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 27 citations in OpenAlex.
- Advancing Neurorehabilitation and Recovery Through Human Movement Quantification via Wearable Sensing.Neurorehabilitation and neural repair · 2026Article
- Review
- Perspectives of key stakeholders on integrating wearable sensor technology into rehabilitation care: a mixed-methods analysis.Frontiers in digital health · 2025Article
- From Gaps to Solutions: Semi-Structured Interviews to Identify Care Gaps in Breast Cancer Care and How to Solve Them with Digital Solutions.Geburtshilfe und Frauenheilkunde · 2024Article
- What characteristics of clinical decision support system implementations lead to adoption for regular use? A scoping review.BMJ health & care informatics · 2024Article
- Financial indicators utilization among community pharmacists: A comprehensive study for pharmacy management.PloS one · 2024Article
- Operational Implementation of Remote Patient Monitoring Within a Large Ambulatory Health System: Multimethod Qualitative Case Study.JMIR human factors · 2023Article
- Information and Communication Technology Medicine: Integrative Specialty for the Future of Medicine.Interactive journal of medical research · 2023Article
- Putting ChatGPT's Medical Advice to the (Turing) Test: Survey Study.JMIR medical education · 2023Article
- Envisioning Post-pandemic Digital Neurological, Psychiatric and Mental Health Care.Frontiers in digital health · 2021Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic accelerated the adoption of remote patient monitoring technology, which offers exciting opportunities for expanded connected care at a distance. However, while the mode of clinicians' interactions with patients and their health data has transformed, the larger framework of how we deliver care is still driven by a model of episodic care that does not facilitate this new frontier. Fully realizing a transformation to a system of continuous connected care augmented by remote monitoring technology will require a shift in clinicians' and health systems' approach to care delivery technology and its associated data volume and complexity. In this article, we present a solution that organizes and optimizes the interaction of automated technologies with human oversight, allowing for the maximal use of data-rich tools while preserving the pieces of medical care considered uniquely human. We review implications of this "augmented continuous connected care" model of remote patient monitoring for clinical practice and offer human-centered design-informed next steps to encourage innovation around these important issues.
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.