NR 599 Mid-Term review Fall 2020 – Grade A | NR599 Mid-Term review Fall 2020 – School Graded NR 599 MIDTERM REVIEW

NR 599 Mid-Term review Fall 2020 – Grade A | NR599 Mid-Term review Fall 2020 – School Graded NR 599 MIDTERM REVIEW General principles of Nursing Informatics • Verbalize the importance of health information systems with clinical practice. • Have knowledge of types and clinical and administrative uses of health information systems. • Ensure confidentiality of protected patient health information. • Assure access control in the use of health information systems. • Informatics: Science and art of turning data into info. • Nursing Informatics ANS: The specialty that integrates nursing science with multiple information and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice. ◦ Nursing Informatics supports nurses, consumers, patients, the inter-professional healthcare team, and all other stakeholders in their decision making in all roles and settings to achieve desired outcomes. ◦ 2 Levels NI practice: generalists and informatics-nurse specialists. Knowledge • Awareness and understanding of a set of information and ways that information can be made useful to support specific task or arrive at a decision • Information that’s synthesized so that relationships are identified and formalized. • Processed information that helps to clarify or explain some portion in our environment or world that we can use a as basis for action or upon which we can act. • Often affected by assumptions and central theories of a scientific discipline and is derived by discovering patterns of relationships between different clusters of information. • Answers questions of “why” and “how” • Data – uninterpreted items, often referred to as data elements. An example might be a person’s weight. Without additional data elements such as height, age, overall well-being it would be impossible to interpret the significance of an individual number. • Information – a group of data elements that have been organized and processed so that one can interpret the significance of the data elements. o For example, height, weight, age, and gender are data elements that can be used to calculate the BMI. The BMI can be used to determine if the individual is underweight, overweight, normal weight or obese.