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Structured and Unstructured Data

Structured and Unstructured Data

Structured and Unstructured Data

What is the difference between structured and unstructured data? Compare the impact of using structured versus unstructured data.
Structured and Unstructured Data


Structured and Unstructured Data
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Structured and Unstructured Data
Healthcare data exists in various forms that may be structured or unstructured. This data comprises information such as vital signs, physician notes, x-ray images, and MRIs. It may be analyzed or validated against anticipated scientific ranges and evaluated periodically. Structured data comprises clearly defined, organized data that is searchable, while disorganization, irregularities, and ambiguities characterize unstructured data. Structured data is easier to capture and group in a particular healthcare information database. For example, accounting information such as billing notes shows structured data that may be easily interpreted. On the other hand, unstructured data comprises physician notes, patient signs description, and it forms the bulk of the healthcare information (Vest et al. 2017).
Structured data is more consistent and exists in pre-defined fields within the electronic healthcare records systems. It consists of numerical values such as blood pressure, temperature, height, weight, and heart rate. Besides, it may be in the form of defined groupings such as blood type or the stage of a particular disease. The disorganization of the unstructured data means that it needs to be manually analyzed and interpreted. Therefore, it is highly resource-intensive compared to structured data in time and other inputs such as machines. Data consistency is critical to ensure uniform use across various nursing or healthcare settings. Therefore, to improve the data consistency, various standards have been developed, such as Logical Observation Identification Names and Codes, LOINC, and HL7. These standards enhance the quality of the structured data and its utility in healthcare settings (Kong, 2019).
Nurses need to understand how to manage and analyze these forms of information. For instance, to be competent in analyzing unstructured data, there is a need to learn machine learning and artificial intelligence, which are often the best in analyzing unstructured data.

Kong, H. J. (2019). Managing big unstructured data in the healthcare system. Healthcare informatics research, 25(1), 1-2.
Vest, J. R., Grannis, S. J., Haut, D. P., Halverson, P. K., & Menachemi, N. (2017). Using structured and unstructured data to identify patients’ need for services that address the social determinants of health. International journal of medical informatics, 107, 101-106.

Structured and Unstructured Data

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