ArticleBMC medical informatics and decision making2015
A scoping review of cloud computing in healthcare.
Article in BMC medical informatics and decision making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Security challenges and solutions using healthcare cloud computing.Journal of medicine and lifePooled it
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- Patient-centered radiology: a roadmap for outpatient imaging.European radiology · 2024Review
- Digital Transformation of Public Health for Noncommunicable Diseases: Narrative Viewpoint of Challenges and Opportunities.JMIR public health and surveillance · 2024Article
- Implementation of cloud computing in the German healthcare system.NPJ digital medicine · 2024Review
- Classification of dental implant systems using cloud-based deep learning algorithm: an experimental study.Journal of Yeungnam medical science · 2023Article
- Construction and evaluation of China older-adult care service smart supply chain system.Frontiers in public health · 2023Article
- Organizational and behavioral attributes' roles in adopting cloud services: An empirical study in the healthcare industry.PloS one · 2023Article
- Utility of a cloud-based lesion data collection software to record, monitor, and analyze an ablation strategy.Heart rhythm O2 · 2022Article
- The Development and Concurrent Validity of a Multi-Sensor-Based Frailty Toolkit for In-Home Frailty Assessment.Sensors (Basel, Switzerland) · 2022Article
- A scalable framework for smart COVID surveillance in the workplace using Deep Neural Networks and cloud computing.Expert systems · 2022Article
- Why Mayo Clinic Is Embracing the Cloud and What This Means for Clinicians and Researchers.Mayo Clinic proceedings. Innovations, quality & outcomes · 2021Review
- Resolution-based distillation for efficient histology image classification.Artificial intelligence in medicine · 2021Article
- A survey of multiscale modeling: Foundations, historical milestones, current status, and future prospects.AIChE journal. American Institute of Chemical Engineers · 2021Article
- Proposal and Assessment of a De-Identification Strategy to Enhance Anonymity of the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in a Public Cloud-Computing Environment: Anonymization of Medical Data Using Privacy Models.Journal of medical Internet research · 2020Article
- Impact of industry 4.0 to create advancements in orthopaedics.Journal of clinical orthopaedics and trauma · 2020Article
- Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications.Sensors (Basel, Switzerland) · 2020Review
- Laniakea: an open solution to provide Galaxy "on-demand" instances over heterogeneous cloud infrastructures.GigaScience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an "OMICS-context", e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain.
methodsMEDLINE was searched in July 2013 and in December 2014 for publications containing the terms "cloud computing" and "cloud-based". Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings.
results102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated.
conclusionsEven though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term "cloud" synonymously for "using virtual machines" or "web-based" with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.
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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.