Data Mining: Helpful Relationships to Nurse Administrators (Health, Medicine, Nursing Essay)

Data Mining
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Data Mining
Helpful Relationships to Nurse Administrators
Data mining is examining a large amount of data to get important information. Data mining use predictive models based on historical and existing data to predict the outcomes of business transactions and activities. One of nursing administrators' primary responsibilities is to coordinate nursing practices with the health facility's organizational goals. Chief Nursing Officers (CNO), who are part of the administration, have to ensure that excellence in patients' outcome is attained by aligning nursing practices to organizational goals. Toellence in patients' outcomes, nursing administrators such as CNOs must communicate strategic goals of an organization to other staff in various health facility levels (Englebright & Caspers, 2016). Nurse administrators should establish a stronger relationship with other nurses, especially departmental heads in different groups such as nurse managers and direct care nurses, tasked with such colossal responsibility. In addition to communicating the goals to various departments, Chief Nurse Executives (CNEs), including the CNOs, are responsible for designing and implementing quality improvement measures that can only be informed by the big data analytic (Englebright & Caspers, 2016). As a result, the CNEs, who are equal members of the administration in health facilities, have to establish strong relationships with big data analytic professionals.
Importance of Analytics Professional Relationship with Nurse Executives
Continuous quality improvement in nursing is an element of both administrative mandates as well as a professional responsibility. With the advent and increased utilization of data analytics, it becomes even more evident to identify data elements and establish a relationship between them, which can help develop a knowledge base about the same. To this end, the data elements involved in quality improvement include the data on staff numbers, the rate of turnover annually, and feedback from patients. When a database with such data is compiled, it becomes quite easy to develop data attributes and establish relationships therein. Such relationships can, in turn, play an important role in data optimization, forecasting, and such, which are quite crucial in ascertaining the quality of healthcare being meted out to the patients within a clinical setup. On the other hand, it is also quite important to have a record of errors committed within the clinical set up so that they can be compared against the services to determine the nursing efficiency.
Tasked with spearheading quality and system improv...