Written by Onri Jay Benally on The Impact of Early Medical Record Systems on Modern Cloud Storage & Security Development.

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Onri Jay Benally
12/16/2021
History of Media Communication
The Impact of Early Medical Record Systems on Modern Cloud Storage & Security Development
When you sign up for a new Google account, you are given 15 gigabytes of free online
cloud storage (Google One). This may seem trivial to the average internet user, but online
information storage has come a long way since before its host was invented (Croteau et al.,
2021). To understand the growth of what we now call the cloud, derived from the internet, we
must first have a look at one of the major use cases where quick access to a large volume of
patient information was needed. Electronic health records (EHR) serve this very purpose.
Within the topic of EHR, both patient privacy and confidentiality have been an issue of great
concern since the beginning of medical history (Silverman, 1998). Introducing this filing system
of private information to computer networks gave rise to a higher probability of unauthorized
access to persons who wanted to view patient data, among other complications. Nonetheless,
EHR has helped drive the need for a stronger online-based storage and computing network.
The cloud is a way through which one can save files and data to an off-site location,
accessed through a private network connection or the public internet (IBM Cloud Team, 2017).
It is a constituent of cloud computing technology, which has been around since the 1950s.
Basically, physical spaces, called “server rooms”, that host large computer hardware
infrastructure, could be connected to other servers via cables or wireless transmission. This
allowed for a network of data to be shared over large distances, manageable and configurable

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through software implementation. By simply distributing computing power and memory
storage among multiple server nodes, you now have the cloud (IBM Cloud Team, 2017).
Benefits of the cloud include active and easy resource provision, automatic management of
information technology, almost limitless processing power, and low-cost to users (Achampong,
2013). As before mentioned, the main issues with this technology have always been related to
information security, and thus its adoption.
A major hassle that slows the proper and accurate diagnosis of patients lies in the
inability to quickly view patient records over time. To help put this into perspective, the study
by Fagan et al. (2006) talks about a hospital, the University of Texas Health Center (UTHC),
where it receives 138,500 outpatient visits and 3,700 inpatient stays annually. “The traditional
paper record has become large, unmanageable, illegible, and frequently unavailable”, (Fagan et
al., 2006). There was much to be desired as we can see. The paper record system presented
hazards and high costs of operation through its complex disorganization. Solving the problem of
having to meet in-person and request or retrieve these vital records would save precious time
and lives in the process (McColligan, 1994). This is what telemedicine tries to address; however,
its main utility involves providing a method of consultation for rural communities and
management/training in healthcare using digital infrastructure (Field, 1996). Field references
some of the earliest networks used in 1950s telemedicine to help medical doctors and
researchers transfer patient information. The clarity of information transmission improved over
time, however, storing that information and keeping it safe from unwanted hands was another
whole problem (Silverman, 1998).

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This led to the introduction of the 1996 National Information Infrastructure (NII), which
comprises of hardware and software integration, providing services and information resources
between people, (healthcare workers in this context), using computers (Lindberg, 1995). It
subsequently was passed by Congress as an act, known as The National Information
Infrastructure Protection Act of 1996, which prohibited unauthorized access and certain types
of fraud (McCollum, 1996). The aim of this institution was to provide a more reliable
information superhighway, under the guidance of the federal High Performance Computing and
Communications (HPCC) Program. HPCC’s introduction was motivated by a critical
demonstration at the time, in health care (Lindberg, 1995). Basically, what they were saying is
that for a more robust healthcare system to exist, providing a shorter path for sharing
information between healthcare workers was needed. The impacts of this development also
had economic implications, both good and bad. If every hospital adopted this information
system faster, then it would make everything more efficient, but if the security is weak, then
countless hospitals would be compromised simultaneously (Fagan et al., 2006). With the rise of
computer-related crime each year, the policies stated in the NII Protection Act surrounding this
problem were updated frequently (Lindberg, 1995). Essentially, the requirements of these
policy revisions provided more support for national supercomputer research centers, which
worked on beefing up the firewall and security of the national network infrastructure over time.
Since medical centers were recognized as a big potential end-user of this information
superhighway, microcomputer networks that used online servers, previously proposed by
McColligan et al., Hales et al., and McDonald & Tierney, were becoming possible. What these
networks and services provided was a way to easily interface with the newly introduced World

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Wide Web and the Gopher internet protocol (McColligan et al., 1994). A key driver for these
proposals was to fulfill a need through innovation and simplicity.
With the advent of more affordable, powerful, and compact personal computers in the
early 1990s, EHRs were beginning to show candidacy in pushing the limits of online information
storage (Evans, 2016). The current state of electronic health records is somewhat steady. Since
the recent implementation and subsequent use of computerized clinical decision support (CDS),
there has been an enhancement in the practice of modern medicine (Dexter et al., 2018). CDS
uses engineered algorithms to help organize a rich repository of physician orders, basically
medical receipts that doctors store on the cloud. The organization of these physician orders
automatically processes into a graphic through an algorithm to show dominant trends in
medicine. Medical practitioners are then able to share and present these findings in real-time
at medical conferences and training sessions (Evans, 2016). Voice recognition for data entry,
image acquisition device technology, and portability in emergency transport (ambulance usage)
have also been realized so far.
Although it has been shown that while many expectations have been realized today,
there are still complications to be dealt with in EHRs. One of the main obstacles that has been a
pain is data duplication, which can cause confusion (Evans, 2016). Quality of data that is
entered through personal computers are sometimes overlooked for some reason. The lack of
standards to correcting this issue is noted by Evans, but it is said that physicians are still
optimistic about the direction of future EHR systems. There is hope for the medical trends
displayed by newer EHR systems to help guide hospital quality improvement efforts.

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In the news today, it is still being said that physicians are spending a lot of time
navigating and clicking these electronic records (Zewe, 2021). The interface itself seems to lack
a comfortable user design. However, by unifying search processes and patient documentation
through new machine learning algorithms, researchers are hoping to improve EHR quality. This
has been put to the test due to the corona virus (COVID-19) pandemic (Meer, 2021). The rapid
innovation and implementation of these online systems has been motivated by the public
health crisis. This includes patient data analysis, care updates, results tracking, patient
communications, and telehealth (monitoring & consultation). Another significance in realizing
the speed of this machine learning development for EHR was the reframing of researchers’
perspectives in the position of doctors; on how EHRs were to actually benefit clinicians (Zewe,
2021).
On the other hand, informed patient care with the help of artificial intelligence (AI) and
machine learning is favored by the gold standard of randomized clinical trials (Winslow, 2021).
The issue demonstrated in these kinds of trials is that minority groups and those who live far
from medical research centers are underrepresented. This seems to be the problem with AI
that lacks ethical design implementations. However, researchers are keen on finding ways to
alleviate this issue by training the newer algorithms to focus on and highlight relevant records
(Zewe, 2021). In doing this, by placing relevance in the limelight, a space for ethics to dwell in
the idea of intelligent technology should be possible.
By comparing the new electronic health record system with the earlier version of itself,
we can learn how to focus on the experience of the end-users. It is helpful because the
comfortability factor seems to reduce strain on the network, leading to faster adoption. 2 birds

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can be hit with 1 stone by unifying the search process, which may lead to easier organization,
high quality data analysis, and possibly a new gold standard that will improve health care
everywhere. In achieving these goals, it may be possible to make the cloud more than an
enjoyable experience that reduces strain on the health care system and less stress for everyone
using this network. It is important to recognize that up to now, the frustrations and unrealized
expectations in media technology are a chance to reframe and reflect on how we choose to
adapt to sudden changes. We must never forget to add in a taste of ethical practice in the next
steps.

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References
Achampong, E. (2013). Electronic Health Record (EHR) and Cloud Security: The Current Issues.
International Journal of Cloud Computing and Services Science (IJ-CLOSER), 2.
https://doi.org/10.11591/closer.v2i6.5343
Croteau, D., Hoynes, W., & Childress, C. (2021). Media/Society: Technology, Industries, Content,
and Users (7th Edition). SAGE Publications.
https://books.google.com/books?id=xzwiEAAAQBAJ
Dexter, P., Warvel, J., & Takesue, B. (2018). Identifying dominant inpatient trends leveraging
electronic physician orders: The Medical Gopher 1993-2016. AMIA ... Annual Symposium
proceedings. AMIA Symposium, 2018, 377–384.
Evans, R. S. (2016). Electronic Health Records: Then, Now, and in the Future. Yearbook of
Medical Informatics, 25(Suppl 1), S48–S61. https://doi.org/10.15265/IYS-2016-s006
Fagan, M. H., Kilmon, C., & Belt, T. (2006). INTEGRATED RESULTS REPORTING: MOVING
TOWARD ELECTRONIC HEALTH RECORDS. Issues In Information Systems, 7(2), 64–68.
https://doi.org/10.48009/2_iis_2006_64-68
Field, M. J. (1996). Telemedicine A Guide to Assessing Telecommunications in Health Care. In
Telemedicine: A Guide to Assessing Telecommunications in Health Care. National
Academy Press (US). https://www.ncbi.nlm.nih.gov/books/NBK45445/
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One FAQ. Retrieved December 15, 2021, from https://one.google.com/faq/storage

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Hales, J. W., Low, R. C., & Fitzpatrick, K. T. (1993). Using the Internet Gopher Protocol to link a
computerized patient record and distributed electronic resources. Proceedings of the
Annual Symposium on Computer Application in Medical Care, 621–625.
Lindberg D. A. (1995). HPCC and the National Information Infrastructure: an overview. Bulletin
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IBM Cloud Team. (2017, January 6). A Brief History of Cloud Computing. IBM.
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McCollum, B. (1996, October 11). H.R.3723 - 104th Congress (1995-1996): Economic Espionage
Act of 1996 (1995/1996) [Legislation]. CONGRESS.GOV.
https://www.congress.gov/bill/104th-congress/house-bill/3723
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Meer, E. (2021, December 13). Electronic health records and COVID-19: Try that with your paper
chart [News]. Ophthalmology Times.

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https://www.ophthalmologytimes.com/view/electronic-health-records-and-covid-19-
try-that-with-your-paper-chart
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Winslow, R. (2021, December 3). Medical Records Data Offers Doctors Hope of Better Patient
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Zewe, A. (2021, September 23). Toward a smarter electronic health record [News]. MIT News |
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