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Definition of EHR - Paper Example

2021-08-25 20:35:11
4 pages
905 words
University/College: 
Vanderbilt University
Type of paper: 
Literature review
This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

An electronic health record refers to a computerized model of a patients pharmaceutic data (Hashem, Yaqoob, Anuar, Mokhtar, Gani & Khan, 2015). It is gathered and controlled by various legitimate healthcare providers, which can be conveyed digitally among them. The gathered information encompass data collected over a duration which is commonly termed as a longitudinal record. The information contained involves medical background, clinical information such as pharmacy, laboratory and radiology, and demographic insights. Moreover, EHR systems allow individuals a means to obtain some digitized information using personal health record systems that permit people to see specified information like lab outcomes through a secure gateway.

Description of Problem

Before the 1960s, medical information was documented on paper and kept in a file (Zhang, Xu, Liang, Li & Zhang, 2017). Visit notes, pharmaceutical instructions, lab results and diagnoses were written and preserved and the papers bound together to form a patients clinical record. The records were identified using a patients surname, the last numbers of the individuals social security numeric or another manual identification system. These records were later filed and accessed from particular shelves that were systematically named to maintain the folders.

During the mid-1960s, a man named Lockheed innovated an automated system called the information system. From there, other establishments began constructing electronic medical records that could be implemented in both universities and hospitals.

The urgency to switch to EHRs was identified countrywide in 2004 by the Office of the National Coordinator. Presently, the EHR is a well-guarded and effectual device for sustaining a persons healthcare information, for interaction with patients and the issuers and promoting the rapport between the patients and the physician. There is no more struggling looking for papers or even delaying patiently for faxes to search for the most appreciate care for the subjects.

Documentation Integrity

Documentation integrity refers to the precision of the entire health database. It involves information oversight, patient recognition, authorship corroboration, improvements and record amendments in addition to auditing the database for documentation cogency when issuing compensation claims (Pasquier, Singh, Eyers & Bacon, 2017). EHRs are fitted with modifiable documentation operations that enable the application of crafty phrases and arrangements to help with documentation. Proper usage of these instruments is cardinal to ensure the integrity and the accuracy of the information. Predetermined protocols and processes like the audit functions should be present to ascertain necessary billing.

In the absence of these policies, the records could show an equivocal reflection of the patients state, either at an early stage or even in the course of time. The issuer should comprehend the mandates of assessing and altering all deficient data to make sure that the captured information reflects that particular visit only, while other insights given by the automated template is deleted. For instance, the digital production of regular negative findings within a test of systems for individual body section or organ system may give rise to an elevated level of service issued, except if the physician documents relevant positive outcomes and removes the inaccurate templates.

Patient Identification Errors

Improper documentation integrity is likely to occur when incorrect data is captured in the incorrect patient medical record. Mistakes in patient identification can influence the medical decisions adopted, and the safety of the person. It also affects the persons privacy and security and may give rise to duplicate reviews which may swell the costs incurred by both the patients and the providers. Patient identification mistakes may augment aggressively within the patients health record, health information exchange and EHR as the enlightenment mushrooms.

The ignorance of entities to implement front-end solutions that comprise of protocols such as refined similar models or other techniques like the execution of fingerprinting, photography and biometrics, the hospital can be susceptible. Distinctive alerts can be constructed and used within an EHR to circumvent safety concerns like when test results focusing on a patients allergy or blood type is not similar to the subject seeking treatment.

Advantages of EHR

Several advantages come with using EHR systems for both patients and the issuers. EHRs systems provide quick entry to patients information and a more informative and precise image of patient care. The systems can be very helpful in dwindling the costs connected to paperwork and enhance efficiency. EHRs are less prone to medical errors, and therefore they are safe at providing prescriptions. The system can provide medical decision support, to grip and inquire information salient to clinic care quality and to disperse computerized health information and also merge with other information sources. They also make medical information accessible, lowering replication of tests, decreasing deferment of treatment and the patients can make more informed decisions.

EHR systems can interact through a mechanism known as EHR interoperability. Through this technique, these systems can exchange and even use the insight distributed. However, because various EHR systems may grasp information in special manners and for unique uses, it can be challenging to disburse that material to a different system.

References

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The Rise of Big Data on Cloud Computing: Review and Open Research Issues. Information Systems, 47, 98-115.

Pasquier, T. F. M., Singh, J., Eyers, D., & Bacon, J. (2017). CamFlow: Managed Data-Sharing for Cloud Services. IEEE Transactions on Cloud Computing, 5(3), 472-484.

Zhang, Y., Xu, C., Liang, X., Li, H., Mu, Y., & Zhang, X. (2017). Efficient Public Verification of Data Integrity for Cloud Storage Systems from Indistinguishability Obfuscation. IEEE Transactions on Information Forensics and Security, 12(3), 676-688.

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