Cloud Computing Essay Example

Published: 2022-04-08
Cloud Computing Essay Example
Type of paper:  Research paper
Categories:  Information technologies
Pages: 5
Wordcount: 1108 words
10 min read

Introduction and description of the case

Key issues and problems

Cloud computing is defined is an on-demand Internet infrastructure that allows users to access computing resources from anywhere and anytime (Mell and Grance, 2010). This is not a new technology but rather a new framework for providing computing resources. Although this model is yet to be applied in the healthcare industry fully, it is being used in many other applications such as Google Docs. In the healthcare sector, some of the applications used include Microsoft HealthVault ( Cloud-based computing offers some benefits to healthcare organizations including the on-demand availability of huge computing resources, lack of up-front user commitment, and payment for only what is needed (Armbrust et al., 2010). The application of cloud-based computing has gained momentum in many industries such as national security, business, and education (Behrend, Wiebe, London, & Johnson, 2011; Li, Chen, & Wang, 2011).

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Like in any other sector, the healthcare institutions need to innovate continuously and systematically to provide high-quality services, remain, efficient, cost-effective, and timely. It has been argued that cloud-based computing can improve the quality of healthcare services, health research, and the application of information technology in general (Chatman, 2010; Dudley et al., 2010; Schweitzer, 2011). For instance, it is well known that electronic health-recording infrastructure such as hardware, software, networking, and human capital in addition to licensing fees represent substantial resources to many healthcare organizations (Schweitzer, 2012). As such, cloud computing is believed to be a more affordable alternative that helps lower these expenses (Calabrese & Cannataro, 2015). One study pointed out that the bioinformatics community can take advantage of the cloud-based computing model to share data (Rosenthal et al., 2010). One of the major challenges in biomedical data management is associated with inappropriate data handling as well as complex and costly computational solutions (Anderson et al., 2007). Consequently, cloud-based computing is considered a potential solution for overcoming these issues (Avila-Garcia et al., 2008; Bateman & Wood, 2009; Dudley and Butte, 2010; Kuo, 2011; Memon et al., 2010; Schatz, Langmead, & Salzberg, 2010; Wall et al., 2010).

Despite the many benefits associated with the application of this model for health care, several issues associated with technology, security, management, and legal aspects need to be addressed. This paper discusses the concept of cloud-based computing and cloud computing strategy challenges. Various studies cite compliance issues as one of the most significant barriers to adoption of cloud-based computing by healthcare institutions alongside security. Strict compliance regulations have slowed down the uptake of the cloud-based computing paradigm.

It is noteworthy that whichever information technology used by the healthcare institutions must be domiciled somewhere. Besides, healthcare organizations are doing whatever they can to increase their capacity for more patients to the increasing patient loads. As such, a hospital may deem it fit to outsource data centres and infrastructure to trusted partners. However, these services must meet the standards of HIPAA regulations.

Implementation plan

Based on the potential solutions proposed, the next step is to devise an implementation plan for the healthcare organization. As suggested by Roberts (2011) a project plan is an important tool for instituting change but the requirements for implementation must be clearly stated and understood. McWhinney's (1997) and McWhinney's et al., (1997) provide useful concepts of change. According to these concepts, the problem owners need to review the skills, resources, and methods at their disposal that can assist in achieving the potential solutions. The implementation plan will need to solve the problem of teams that will lead the change, which in itself will require a clear demonstration of leadership and effective management (Mullins 2013).

In alignment with the problems, it is important to follow a proper approach, in which a plan can be developed and implemented successfully. McWhinneys et al.'s, (1997) social - sensory evaluative mode of change play an important role in drawing the implementation plan. In this case, the problem owners identify the team preferences through the 'Valuing' element of the team member values in the Social reality. The path of change then moves through the Emergent mode, where the generation of ideation occurs reflecting the individual values (Social - Mythic). The evolution of the plan moves from Mythic to Social during the creation of the implementation plan. Necessary resources are allocated accordingly, which leads to the completion of the 'Organisational Development' as envisaged in McWhinney's et al., (1997).

Planning for implementation should anticipate and plan for countermeasures to potential restraining factors, limited information flow, and perceived benefits of the change. The project implementation plan will involve small actionable tasks with set completion deadlines (Auty, 2005; Clayton, 2013). The planning required for the implementation of the cloud solution is similar to of an outsourcing arrangement. Activities will need to be carried out in-house by agencies. The phased implementation of the cloud computing environment will include:

Phase 1: Fostering the adoption of cloud-based computing

Phase 2: Optimizing the consolidation of data centres

Phase 3: Establishing the hospital's cloud infrastructure

Phase 4: Delivering the cloud services

Cost/benefit analysis

Costs associated with cloud computing

CapEx/ Opex

Data connection speed and expenses

Operation costs

Migration costs

Failure and data loss

Platform costs

Backup and archive costs

Risks associated with cloud computing

Policy and organizational risks

Technical risks,

legal constraints (compliance with HIPAA regulations)

Benefits of cloud computing

Scalability and flexible infrastructure

Resource management


Energy efficiency

Backup and Recovery


System complexity

Shared environment

Remote administrative access

Loss of control

Return on Investment analysis

Feasibility analysis (economic, technical, operational)


Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., ... & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.

Behrend, T. S., Wiebe, E. N., London, J. E., & Johnson, E. C. (2011). Cloud computing adoption and usage in community colleges. Behaviour & Information Technology, 30(2), 231-240.

Calabrese, B., & Cannataro, M. (2015). Cloud computing in healthcare and biomedicine. Scalable Computing: Practice and Experience, 16(1), 1-18.

Chatman, C. (2010). How cloud computing is changing the face of health care information technology. Journal of Health Care Compliance, 12(3), 37-38.

Dudley, J. T., Pouliot, Y., Chen, R., Morgan, A. A., & Butte, A. J. (2010). Translational bioinformatics in the cloud: an affordable alternative. Genome medicine, 2(8), 51.

Kuo, A. M. H. (2011). Opportunities and challenges of cloud computing to improve health care services. Journal of medical Internet research, 13(3).

Li, Z., Chen, C., & Wang, K. (2011). Cloud computing for agent-based urban transportation systems. IEEE Intelligent Systems, 26(1), 73-79.

Mell, P., & Grance, T. (2010). The NIST definition of cloud computing. Communications of the ACM, 53(6), 50.

Rosenthal, A., Mork, P., Li, M. H., Stanford, J., Koester, D., & Reynolds, P. (2010). Cloud computing: a new business paradigm for biomedical information sharing. Journal of biomedical informatics, 43(2), 342-353.

Schweitzer, E. J. (2011). Reconciliation of the cloud computing model with US federal electronic health record regulations. Journal of the American Medical Informatics Association, 19(2), 161-165.

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