Description
Thomas Clobes Posted :
Thanks for sharing your thoughts on this topic. Demigos (2022) complied a list of benefits of data warehousing:
Efficient reporting
Better clinical decisions
Optimized insurance claims and processing
Enhance strategic planning
Improved patient experience
Improved patient outcomes
Personalize value-based care
What else might you add to this list? Can you think of any drawbacks?
Dr. C
Reference
Demigos. (2022). Using a data warehouse in healthcare: Architecture, benefits, and use cases. https://demigos.com/blog-post/using-a-data-warehou…
this was my dissution
Discussion Five
Differences and Similarities
Within information technology and data management, there are three separate but related concepts: databases, data warehouses, and data mining. A systematic collection of data arranged and stored for convenient retrieval, modification, and access is called a database (Edastama et al., 2021). It acts as the system’s base for data management. In contrast, a data warehouse is a sizable, central store for information gathered from various sources inside a company. It offers a combined picture of recent and historical data and is used for reporting and analysis. A subclass of artificial intelligence, data mining focuses on identifying patterns and information inside massive datasets. The methodology employs many approaches, including machine learning and statistical analysis, to uncover latent patterns within the dataset.
These ideas are similar in that they are all centred around efficiently managing and using data. Although for different reasons, all three entail the organization, retrieval, and storage of data (Gupta & Chandra, 2020). Databases and data warehouses are closely related; to give
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thorough analytics, a data warehouse frequently uses data from several databases. Patterns and trends can be found in databases and data warehouses by using data mining techniques.
Challenges in Creating a Health Information Database
Building a valuable database of health information comes with several difficulties. Due to the complexity, diversity, and frequent incompleteness of healthcare data, data quality is a significant problem (Edastama et al., 2021). Ensuring the data is relevant, accurate, and consistent is essential for insightful analysis and decision-making. Data security and privacy present additional difficulties since health information is sensitive. It is essential to have strong security measures in place to safeguard patient privacy.
Since different systems and entities collect and maintain healthcare data, interoperability is another issue (Gupta & Chandra, 2020). Building an extensive health information database requires smooth data interchange and integration between various healthcare systems. Building a reliable and accountable health data repository also requires addressing ethical issues with data utilization and patient consent.
In conclusion, although databases, data warehouses, and data mining have distinct functions, they are all essential elements of efficient data management. To fully utilize healthcare data for research, analysis, and decision-making, it is necessary to address issues with data quality, security, interoperability, and ethics while building a meaningful health information database.
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References
Edastama, P., Dudhat, A., & Maulani, G. (2021). Use of Data Warehouse and Data Mining for Academic Data: A Case Study at a National University. International Journal of Cyber and IT Service Management, 1(2), 206-215. https://doi.org/10.34306/ijcitsm.v1i2.55
Gupta, M. K., & Chandra, P. (2020). A comprehensive survey of data mining. International Journal of Information Technology, 12(4), 1243-1257. https://doi.org/10.1007/s41870-020-00427-7
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