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Essay Available:
2 pages/≈550 words
3 Sources
Health, Medicine, Nursing
Annotated Bibliography
English (U.S.)
MS Word
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Data Quality: Importance of Standardized Terminology in Healthcare Information Systems (Annotated Bibliography Sample)


A. Create an annotated bibliography ...


Data Quality
Warren, J. (2012). Importance of Standardized Terminology in Healthcare Information Systems (1st ed.). University of Kansas School of Nursing. Retrieved from /qsen-informatics/2012-workshop/presentations/warren/Importance-of-Standardized-Terminology-Warren.pdf
The article by Judith J. Warren, brings out one the most debated aspects on data and quality of the same along with the aspect of usefulness in the healthcare system. The article, ‘Importance of Standardized Terminology in Healthcare Information Systems’, is one that highlights the various aspects of data quality and how this impacts the health care sector. There are quite a number of parties that use the health care information such as the research institutes, state public health, community practice, federal agencies, health information organizations, health center network, integrated delivery system along with the community. Given the number of organizations that interact with the data, it is crucial that the level of quality is enhanced. With quality data the health care facilities are able to enhance seamless and efficient delivery of the best practices of care. From the time that the data is received, the way that it is recorded, how it is compared to existing information and the point of exchange. It is important that the information is not lost through poor information management. This is relative to the use of standard terminologies, were every other health care provider is conversant with the terms and therefore will interpret the same with precision. According to the article, structured terminology helps achieve integration of evidence based practices guidelines knowledge, care coordination, flexibility in documentation, nursing visibility, knowledge discovery and quality measurement. This further enhances the data entry structure, decision support,

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