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Data Warehousing & Data Mining - Assignment Example

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Data warehousing and data mining are critical aspect of modern healthcare practices. Data mining (DM) is a process that aims to use existing data to uncover new relationships unknown thorough common analysis practices. The process is similar to the extraction of valuable metal hence the term “mining”…
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Data Warehousing & Data Mining
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Data Warehousing & Data Mining a. Why are organizations moving toward implementation of data warehouses? What are the benefits of data warehouses? Data warehousing and data mining are critical aspect of modern healthcare practices. Data mining (DM) is a process that aims to use existing data to uncover new relationships unknown thorough common analysis practices. The process is similar to the extraction of valuable metal hence the term “mining” (Jackson, 2003). Data mining is the process of analyzing extensive data with the aim of establishing correlation between different variables. Consequently, data warehousing is the process of storing data in relational databases that facilitate such queries and analysis.   b. What issues need to be considered by an organization before and during data warehouse development? Organizations are moving towards implementation of data warehousing as reformation strategy. The health sector has been reluctant in the application of information technology and information system. Therefore, implementation of data warehousing can be viewed as a competitive advantage to the health sector. Data warehousing has numerous advantages to a health organization. Ideally, data warehousing is meant to promote comparability of clinical data, which is a significant aspect in the health sector. Before and during data warehouse development, organizations need to consider various issues. Firstly, the organization needs to consider the role of data warehousing. This is because the role of the data warehouse will determine the quality and capacity of the required database. Developers of the data warehouse also need to consider data modification and data integration requirements. c. How is data mining used in conjunction with a data warehouse? The aim of data warehousing is to facilitate decision-making. Data mining can be used in conjunction with data warehousing to facilitate certain decision-making initiatives. Data mining is the process of extracting useful information from raw or summarized data. Thus, data warehousing provides data that is required for this activity. Thus, data warehousing is the process of collecting raw data sufficient for the data mining process. Raw data is obtained from medical records, clinical trials, and diagnostic information. Data mining is considered as a knowledge discovery process. This is because the process enables a researcher to re-discover significant facts about certain type of data. For instance through data mining a researcher can establish special type of correlation that might not be visible through ordinary observations (Jackson, 2003). Thus, data mining is the process of extracting knowledge while data warehouses provide the required knowledge. Data mining also enhance the quality of data that is contained in a data warehouse. The process helps in data classification or partitions. This enables different sets of data to be indentified using specific parameters or combination of parameters. Lastly, data mining promotes in the organization of data. This promotes optimization of space, time, and monetary resources. d. What are the benefits of data mining? Data mining has numerous benefits that depend on the type of industry involved. In healthcare, data mining is an essential practice. Firstly, data mining enables organizations to make prediction on certain aspects of their operations. For instance, a health organization can use data mining to track the flow of patients. This enables the organization to respond appropriately in order to meet patient/client’s requirements. On the other hand, data mining promotes efficiency in handling and retrieval of data. The process utilizes different patterns and parameters to identify data from a database. Such classification is essential in data retrieval and management. This form of classification enhances utilization of data handling resources and work force. Data mining also enables organization to detect fraud and malpractices. For instance, the process can be used to detect insurance frauds that continue to affect the health sector. Lastly, data mining promotes medical researches and research based practice. e. What role should HIM professionals play in data warehouse development and maintenance? According to Bailey & Rudman (2004), health information management (HIM) professional are becoming increasingly essential in modern healthcare environment. The role of HIM in data warehouse maintenance and development depends on the nature of a health organization. The professionals are expected to ensure accuracy in collections and recording of health data. “The primary responsibilities of the HIM professional are providing quality data to support the delivery of quality healthcare and balancing the right to privacy with providing access to health data for legitimate users-remain constant” (Bailey & Rudman, 2004). Thus, the HIM professionals are charged with the responsibility of ensuring data security as well as accessibility by legitimate users. The HIM professionals are also supposed to promote of facilitate application of information technology in healthcare services. The professionals are expected to oversee the conversion of paper records into electronic ones. This responsibility requires the HIM professionals to be agents of change in their respective organizations. This role requires them to act as trainers for other healthcare professionals who may not be conversant with application of technology in healthcare practices. References Bailey, J. & Rudman, W. (2004). The Expanding Role of the HIM Professional: Where Research and HIM Roles Intersect. Perspect Health Inf Management, 1:7. Jackson, K. (2003). Connecting for Health: Rallying for the Personal Electronic Medical Record. For the Record 15(18):16–19. Read More
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