Electronic Health Record System Analysis

Running head: ANNOTATED BIBLIOGRAPHY
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Name of the student
Name of the university
Author’s name

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Blijleven, V., Koelemeijer, K., Wetzels, M., & Jaspers, M. (2017). Workarounds emerging
from electronic health record system usage: Consequences for patient safety,
effectiveness of care, and efficiency of care. JMIR human factors, 4(4), e27.
The research aims to provide insight of the EHR workarounds effects on organizational
workflows and also aims at evaluating their scopes, rationales and hoe they impact workflows of
the healthcare providers, safety of the patients, effectiveness and efficiency of the care delivered.
In order to conduct the study direct observations and follow up semi structured interviews were
conducted with 13 nurses, 31 physicians and 3clerks. Qualitative bottom up coding techniques
was used for identifying, analyzing and classifying EHR workarounds. The research was
conducted at a large university hospital across 3 specialties and settings. Rationales were related
to the components including technology, persons and tools, organization, tasks and physical
environment of the Systems Engineering Initiative for Patient Safety (SEIPS) framework for
revealing their source of origin and also for determining both the scope as well as the impact of
HER workaround.
Churpek, M. M., Yuen, T. C., Park, S. Y., Gibbons, R., &Edelson, D. P. (2014). Using
electronic health record data to develop and validate a prediction model for adverse
outcomes on the wards. Critical care medicine, 42(4), 841.
This retrospective cohort study was conducted in an academic medical center in the
United States with around 500 beds for the inpatients. The study aims at developing a prediction
model and validate it to detect cardiac arrest during the course of the treatment in the ICU as a
challenging risk with the help of EHR. The study has developed a prediction model for inpatients
in the ward that can assist in predicting the risk associated with cardiac arrest and ICU transfer.

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According to the authors, healthcare facilities incorporating the HER system allows to add other
variables and vital signs about the individual patients to the prediction model such as lab values
and other data of the patients that will help to evaluate and determine the risk scores of the
patient that will eventually help in increasing patient outcome by implementing treatment
strategies addressing those risk areas.
Graham, H. L., Nussdorfer, D., & Beal, R. (2018). Nurse attitudes related to accepting
electronic health records and bedside documentation. CIN: Computers, Informatics,
Nursing, 36(11), 515-520.
The study was conducted to explore the attitude of nurses related to beside
documentation and EHR and it aimed at gaining a better understanding of the practices of the
same by the nursing staffs. This study was conducted through a narrative qualitative approach for
carrying out in depth interviews in the focus group meetings. Two 60-90 minute group
interviews were conducted at a time and location that were convenient for the nurses. The study
analyzed nurse’s attitudes regarding bedside documentation and EHR and 3 themes emerged
from the study which will be helpful in designing nursing educational in service opportunity for
the nurses that will promote positive attitudes towards HER and bedside documentation that will
further facilitate a high quality care delivery increasing patient’s health outcomes.
Hamamura, F. D., Withy, K., & Hughes, K. (2017). Identifying barriers in the use of
electronic health Records in Hawai ‘i. Hawai'i Journal of Medicine & Public
Health, 76(3 Suppl 1), 28.