Analysis of Electric Disaster Response for Healthcare Infrastructure

This assignment addresses a healthcare organization's response to an electric disaster that disables electrical lines and internet servers. The primary solution involves installing backup generators to maintain server room power and ensure continued internet service. The assignment emphasizes the importance of data protection and proposes using Google Cloud Dataproc for data storage and access, even if the EMR is unavailable. Dataproc's features, such as batch processing, querying, streaming, and machine learning capabilities, are highlighted. The research also recommends utilizing cloud-based data storage to ensure data availability during outages. The assignment concludes with recommendations for improvement, including the use of backup generators and cloud platforms to ensure data security and operational continuity. References are provided to support the proposed solutions.

Running head: ELECTRIC DISASTER
ELECTRIC DISASTER
Name of the Student
Name of the University
Author note

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What would your organization do if there was a natural disaster that destroyed electrical lines
and internet servers?
The main step that will be taken in order to mitigate the issues regarding the processing
of the destroyed electrical lines as well as the internet service will be installation of the backup
generators for the server room. In this process, proper investment on the commercial generator
which will be maintaining the power supply of the server room. This installation of the power
generator also imbibes the fact that the working of the internet server will continue.
How would you take care of your patients if you could not access the EMR for a week or
more?
It can be stated that the usage of the Google Cloud Dataproc will be acting beneficial in
the process. This is one of the main aspect that is to be considered. This section ensures that the
data that have been collected will be protected. Dataprotec is a managed Spar and Haddoop
service that provides the advantage of open source data tools and hence wise this ensures that
batch processing is made in a better manner (Jayalakshmi, Alam & Srinivasan 2017). Querying,
streaming as well as machine learning have been the major factors that will be providing proper
administration. Another aspect that is to be considered is that the entire process is super fast in
nature. The entire process is integrated in nature (Bisong 2019). As the platform uses the
technology of cloud, retrieving data from cloud is possible. This might be benefitting the entire
operational process. Even if the EMR goes out of order, usage of data that are stored in the cloud
can be used and the operational process might continue in this manner. Performing research for
proper storage of data is one of the major aspect that is to be considered ("Handbook of
Informatics for Nurses Healthcare Professionals (1).pdf", 2020). With the help of this research

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process, technologies for storing of data can be made in a better manner. This section will help in
proper storing of data and utilizing the same when EMR will not be functioning.
What recommendations can you make for improvement?
The major recommendations that are to be considered are as follows: -
 Usage of the backup generator will be useful: This usage of backup generator ensures the
fact that better getting management of the electricity flow in the server lines can be
managed. This will ensure that power related issues will be eliminated.
 Usage of cloud platform for data storing also acts beneficial. This section ensure that the
data that are present will be ensuring that the functional process will be getting
benefitted.

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References
Handbook of Informatics for Nurses Healthcare Professionals (1).pdf. (2020). Retrieved 9
February 2020, from https://drive.google.com/file/d/16BXMTM-
Lo9wc1XZbk6dUQO9VxJK8A4JT/view
Jayalakshmi, D. S., Alam, S. R., & Srinivasan, R. (2017, May). Approaches to deployment of
Hadoop on cloud platforms: Analysis and research issues. In 2017 2nd IEEE International
Conference on Recent Trends in Electronics, Information & Communication Technology
(RTEICT) (pp. 1985-1990). IEEE.
DOI: 10.1109/RTEICT.2017.8256946
Bisong, E. (2019). An Overview of Google Cloud Platform Services. In Building Machine
Learning and Deep Learning Models on Google Cloud Platform (pp. 7-10). Apress, Berkeley,
CA.
DOI: 10.1007/978-1-4842-4470-8_2