Health Informatics and Cloud Computing Peer Reviewed Articles
There is now increasing recognition of the potential of deject technologies, which provide data storage and calculating resources managed past external service providers, to help improve prophylactic, quality, and efficiency of wellness care.
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All the same, adoption of cloud technology has been variable across health-care organisations, hampered by concerns that the technology might not align with existing methods of quality assurance and governance of privacy, data integrity, and service reliability.
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Guo Y, Kuo K-H, Sahama T. Cloud calculating for healthcare research data sharing. Fourth IEEE International Conference on Cloud Calculating Engineering and Science Proceedings; Taipei, Taiwan; Dec 3–vi, 2012 (abstr 889–94).
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The compelling shared purpose and informational needs in the context of the COVID-19 pandemic have provided a powerful incentive to adopt and do good from fast scale-upward of cloud-based solutions. Now that implementers have established this momentum, it is important to be mindful of the compromises and risks associated with these solutions and their implementation at speed.
Here, we provide an overview of how wellness-intendance settings have used cloud technologies to permit fast deployment of applications in individual organisations and integration of data analytics across organisations during the COVID-19 pandemic. We also hash out potential unintended consequences emerging from the scale and speed with which cloud technologies take been deployed. These include privacy and information governance considerations, lock-in of data structures, data silos, and unintended implications for piece of work practices and organisational performance. Although there are several examples of the implementation of cloud applications (appendix pp 1–3), information technology is of import to annotation that at that place take not yet been formal evaluations of these approaches, which makes it hard to assess their upshot on clinical outcomes. We therefore highlight the need to avoid drawing simple causal inferences in relation to relatively short-term experiences of using circuitous technological infrastructures such as deject technology.
Individual provider organisations have fatigued on cloud technologies to implement discrete COVID-xix-related functionality for organisational and clinical processes including monitoring, diagnostics, testing, triage, and consultations. Some applications facilitate real-time monitoring of patients in high-risk settings for COVID-19 through generating overviews of information from several sources, some enable interactions between health-care staff and patients at a distance, and others allow the development of operational management dashboards facilitating workforce, resource, and care planning.
A primal benefit of cloud-based services to individual organisations and specialties is that they allow fast implementation and upscaling beyond a range of settings, because they practise non require the organisation to buy additional hardware (such as servers needed for on-bounds solutions) and they can exist implemented remotely (provided that appropriate infrastructure exists). For example, Huawei Technologies report that they deployed a pneumonia diagnostic solution to a infirmary in Ecuador in only xiv·h,
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and the Oklahoma Land Department of Health deployed an application for medical staff, designed to follow-up people with reported symptoms of COVID-19, in 48·h.
Notwithstanding, such rapid implementations, although tackling immediate challenges, could have unintended consequences for existing health-care professional work practices and patient safety, specially when new functionality is implemented across multiple contexts on a big scale.
By contrast, on-premises solutions allow piloting and tailoring to contextual requirements every bit they permit a greater degree of organisational control. This is of import, every bit existing work with local electronic health records has identified the need to adjust to speedily changing challenges associated with COVID-19.
Health-care organisations should therefore consider prioritising depression-risk cloud solutions consisting of add-ons to existing functionality (eg, an awarding or a module on an existing deject-based platform to allow rapid shared admission), as these are more likely to enable better integration with existing practices than complex applications connecting departments and organisations.
Interorganisational information sharing in health care is difficult, peculiarly when data are held in local servers equally these might become information silos.
COVID-19 has introduced common and pressing informational needs surrounding incidence, loftier-risk patients, and testing activity. Health-intendance settings now increasingly use cloud technologies to share COVID-xix-related data and provide intelligence through real-time integrated data analytics from various sources across organisations (appendix pp ane–3). New applications range from dashboards connecting deject-based electronic health records to identify trends in high-adventure patients and testing activity, to the establishment of data hubs facilitating almost-real-time information aggregation and assay to inform decisions around resources and clinical care associated with COVID-nineteen beyond hospital groupings. There are also many examples of COVID-19 portals that requite overviews of national and international trends, hosted on cloud services, which are currently in development.
This degree of information sharing on a large scale is simply non possible with on-premises systems, where additional integration engines would need to be installed but would simply allow relatively little information sharing between organisations through standardised messages. Cloud technologies seem to offer a way frontward here. However, there is now a need to marshal purposes of existing cloud technologies, equally there is a risk of overlap betwixt clouds from different service providers. There is also a adventure of information silos in private clouds, and associated problems surrounding data ownership and lock-in of data structures (eg, patient or location identifiers, disease classifications). Collaborative efforts aligning activities of cloud providers could reduce this take chances, but this collaboration needs to be carefully balanced with information security considerations (which go exacerbated with larger scale every bit data transcends organisational boundaries). For instance, people accept warned that establishing large clouds at speed might increase the risks of a then-chosen cyberpandemic, resulting in potential boosted unanticipated risks and costs.
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The oft fast-paced implementation of cloud applications for COVID-19 might besides have compromised adequate negotiation around harmonising data structures and governance at the outset, leading to potential issues surrounding data integration.
Therefore, at that place are clear benefits of deject-based technologies compared with on-premises solutions, particularly in terms of agile implementation and scale-upwards of services where need is unknown (such as with COVID-19), and cross-organisational data integration. Whether these benefits are sustained, however, remains to be seen.
AS reports grants from Health Data Enquiry UK BREATHE Hub, outside the submitted work. KC and RW declare no competing interests.
Supplementary Material
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DOI: https://doi.org/10.1016/S2589-7500(20)30291-0
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