Risk and SWOT Analysis of EHR System at UMUC Medical Center

This report presents a risk and SWOT analysis of the Electronic Health Record (EHR) system at the University of Maryland University College Medical Center. The analysis identifies strengths such as reduced human intervention and improved data accuracy, weaknesses including high costs and potential for data manipulation, opportunities like attracting more service users, and threats such as data breaches. The report emphasizes the importance of training and development as a risk mitigation strategy to ensure proper system operation and data security. The document also includes the introduction and context of the organization and the purpose of the RFP.

Running head: ELECTRONIC HEALTH RECORD SYSTEM
Electronic Health Record System
Name of the University:
Name of the Student:
Author’s note:

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Table of Contents
Risk Analysis...................................................................................................................................2
SWOT analysis................................................................................................................................2
Risk Mitigation................................................................................................................................4

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Risk Analysis
Electronic health record is the electronic version of the service user’s paper chart.
Electronic health records consist of details related to treatment as well as medication of the
patients (Friend, Jennings and Levine, 2017). All the administrative clinical information related
to patient is stored in Electronic health records of a medical service provider. In case of
University of Maryland University College Medical Center, all the details related to treatment
procedure and medication are stored in Electronic Health Records. It has been observed that
there are certain risks that are associated with this particular system. There are high chances that
a person might manipulate information regarding patient’s treatment details, demographics and
medication. This can cause a problem to the management of University of Maryland University
College Medical Center.
It has been noticed that if a person is not knowledgeable enough to handle the Electronic
Health Record System, then errors might occur that can death of a person. In addition to this, it
has been observed that if a person lacks the knowledge to handle the machine then it can be
stated that system breakdown might occur that can decrease the workflow of the entire health
and social care service provider. These are the risks that are associated with electronic health
record system (Andrus et al., 2015).
SWOT analysis
Strengths:
It has been observed that less human intervention occurs at the time of operating
Electronic Health Records of University of Maryland University College Medical Center. As
commented by Ehrlich et al., (2016), there are high chances that this automated machine will

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provide more accurate data because it is not intervened by humans. In other words, as this
machine of University of Maryland University College Medical Center, there is a probability that
it will provide more accurate information regarding the patient’s medication, treatment¸ progress
notes along with previous medical history. Accuracy of information is one of the key strengths of
Electronic Health Record System. Besides, Madden et al., (2016) commented that there will
fewer chances of making errors as this system is not manually operated by medical professionals
working at University of Maryland University College Medical Center.
Weaknesses:
The expensive nature of Electronic Health Record system is considered as one of the
major weaknesses of University of Maryland University College Medical Center. It becomes a
problem for the management of the respective health and social care service provider to bear the
cost of such an expensive machine. In accordance with the opinion of Holden et al., (2015),
there are high chances that data can be manipulated by the person who is operating the machine.
It might happen that the person who is handling machine such an automated machine might give
wrong inputs regarding the demographics and progress notes of the patient.
It might happen that the person who is handling the Electronic Health Record system
have given incorrect data related to patient’s immunization rates, diagnoses and treatment plans.
In accordance with the opinion of Clegg et al., (2016) wrong information given by the person in
the Electronic Health Record might cause death of a person. In accordance with the person might
cause serious illness to the person. Wrong input in the Electronic Health Record system might
lead to wrong diagnosis of the patient (Clegg et al., 2016)

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Opportunities:
It is seen that the installation of Electronic Health Record system within the workflow of
University of Maryland University College Medical Center creates a scope for the healthcare
service provider to attract more service users to avail their health services. It is seen that
installation of Electronic Health Record System within the premises of the respective health and
social care service provider creates an opportunity for the organization to attract more customers
to access their treatment facilities. By installing this automated machine within the working
procedures of the respective organization, there is an opportunity for the organization to earn
more revenue by retaining its consumer base.
Threat:
There are high chances that hackers might steal the confidential information of the
patients related to their personal details, details of progress, previous medical history,
demographics, etc. In other words, hackers can also steal the confidential information of the
patients related to diagnosis, type of illnesses and medication (Holden et al., 2015). As a result,
the respective organization will lose its clients base. This is one of the biggest threats associated
with Electronic Health Record system.
Risk Mitigation
It has been observed that training and development is considered as one of the effective
risk management strategy that can be undertaken by University of Maryland University College
Medical Center. In the opinion of Ehrlich et al., (2016) training and development would aid the
employees of this organization to understanding the functioning of this automated machine in a
better manner.

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References
Andrus, M. R., Forrester, J. B., Germain, K. E., & Eiland, L. S. (2015). Accuracy of pharmacy
benefit manager medication formularies in an electronic health record system and the
Epocrates mobile application. Journal of managed care & specialty pharmacy, 21(4),
281-286.
Clegg, A., Bates, C., Young, J., Ryan, R., Nichols, L., Ann Teale, E., ... & Marshall, T. (2016).
Development and validation of an electronic frailty index using routine primary care
electronic health record data. Age and ageing, 45(3), 353-360.
Ehrlich, J. R., Michelotti, M., Blachley, T. S., Zheng, K., Couper, M. P., Greenberg, G. M., ... &
Weizer, J. S. (2016). A two-year longitudinal assessment of ophthalmologists’
perceptions after implementing an electronic health record system. Applied clinical
informatics, 7(04), 930-945.
Friend, T. H., Jennings, S. J., & Levine, W. C. (2017). Communication patterns in the
perioperative environment during epic electronic health record system
implementation. Journal of medical systems, 41(2), 22.S
Holden, C., Thiamwong, L., Martin, D., Mathieson, K. M., & Nehrenz, G. M. (2015). The
Electronic Health Record System and Hospital Length of Stay in Patients Admitted with
Hip Fracture. American Research Journal of Nursing, 1 (2), 5.
Madden, J. M., Lakoma, M. D., Rusinak, D., Lu, C. Y., & Soumerai, S. B. (2016). Missing
clinical and behavioral health data in a large electronic health record (EHR)
system. Journal of the American Medical Informatics Association, 23(6), 1143-1149.

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