EMR INTEGRATION REFLECTION.

You have examined how point of care technology can improve care and support collaboration. While the amount of data being entered into the computer system is staggering, the challenge is in getting that data back out as useful and actionable information. Consider Electronic Medical Record Adoption Model (EMRAM)?.

Running head: EMR INTEGRATION REFLECTION
EMR INTEGRATION REFLECTION
Name of Student
Name of University
Author’s Note

1EMR INTEGRATION REFLECTION
The use of thermometers, blood glucose monitors, pregnancy tests, strap tests and other
point of care testing has extensively improved care and treatment of patients (St John & Price,
2014). Although the large quantities of hard copy data being transformed to soft copy in
computers is overwhelming, but the extraction of that useful data is a major challenge. With the
advancement and adaption of the technology in the hospital organizations, the huge files of data
are stored in the computers. The main agenda behind the use of computers is to save paper and
long-term storage of data. The hospitals are adapting the Electronic Medical Record Adoption
Model (EMRAM) to go paperless (Ayat & Sharifi, 2016). With the help of the eight-staged
model (EMRAM), the hospitals are developing their Electronic Medical Records (EMR)
capabilities and records to grow globally. The adoption of EMRAM will help the hospitals to
provide safer and improved outcomes for patients in the world.
However, it is believed that a hospital when reaches the stage 7 of the EMRAM, the
hospital truly becomes “paperless”. The hospital illustrates their support by sharing and using
wellness and health information by the clients and providers alike. With the invention of
EMRAM, large files of data are being easily stored but the extraction of the accurate files is
getting difficult. To solve this agenda, the nurses or the organization’s officials of the hospital
use the data mining (Jothi & Husain, 2015) and warehousing process/techniques to extract and
analyze the required data patterns from the large quantities of the data stored.

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References
Ayat, M., & Sharifi, M. (2016). Maturity Assessment of Hospital Information Systems Based on
Electronic Medical Record Adoption Model (EMRAM)—Private Hospital Cases in Iran.
International Journal of Communications, Network and System Sciences, 9(11), 471.
Jothi, N., & Husain, W. (2015). Data mining in healthcare–a review. Procedia Computer
Science, 72, 306-313.
St John, A., & Price, C. P. (2014). Existing and emerging technologies for point-of-care testing.
The Clinical Biochemist Reviews, 35(3), 155.