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Cited by 405Internet of Things and AITechnology and Human Factors in Education and HealthTelemedicine and Telehealth Implementation

Connected healthcare: Improving patient care using digital health technologies

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Awad, Atheer, Trenfield, Sarah J., Pollard, Thomas D., Ong, Jun Jie, Elbadawi, Moe, McCoubrey, Laura E., Goyanes, Alvaro, Gaisford, Simon +1 more·2021·Advanced Drug Delivery Reviews
DOI 10.1016/j.addr.2021.113958
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Abstract

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are under investigation for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery, rehabilitation, or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and opportunities for clinical adoption.

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  • In chronic disease management, AI systems can support transitions between care settings, enhance remote monitoring, and offer predictive insights that guide therapeutic decisions.

    “For chronic disease management, where continuity and coordination of care are essential, AI systems can support transitions between care settings, enhance remote monitoring, and offer predictive insights that guide therapeutic decisions [106,107,108].”

    From Barriers and Facilitators to Artificial Intelligence Implementation in Diabetes Management from Healthcare Workers’ Perspective: A Scoping Review (2025) · cites this paper as [106]

    The Introduction describes remote monitoring and chronic-condition management outside traditional care settings, and §2 (Sensors) says AI can improve interpretations of real-time sensor data. The paper does not establish that AI supports transitions between care settings. Section 5.1 describes predictive analysis for its diabetes-monitoring example as a future possibility, not an existing source of insights guiding treatment decisions. Page numbers were not provided in our copy. (LLM, conf=0.85)

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Cited by

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Authors
Awad, A., Trenfield, S. J., Pollard, T. D., Ong, J. J., Elbadawi, M., McCoubrey, L. E., Goyanes, A., Gaisford, S., & Basit, A. W.
Affiliations
UCL School of Pharmacy (GB)
Corresponding author
Basit, Abdul W.
ORCID
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2021-11
Volume
178
Pages
113958
ISSN
0169-409X (ISSN-L)
DOI
10.1016/j.addr.2021.113958
OpenAlex
W3198084704
Cited by
405
References
6
Citations by year
2026: 42 · 2025: 141 · 2024: 102 · 2023: 75 · 2022: 37 · 2021: 8
FWCI
8.47
Type
journal article
Language
en
Open access
Licence
Locations
  • Advanced Drug Delivery Reviews (publishedVersion)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
Engineering and Physical Sciences Research Council (EP/S009000/1, EP/S023054/1)
Topics
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
Keywords
digital health technologies, Healthcare 4.0, patient monitoring, wearable sensors, 3D printing, personalized medicine, surgical robots, precision surgery, rehabilitation robots, medical drones, Internet of Things, remote patient monitoring, healthcare logistics, clinical adoption
MeSH terms
Digital Technology, Patient Care, Humans, Biomedical Technology

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