General Principles of Nursing Informatics

Verbalize the Importance of Health Information Systems in Clinical Practice Health information systems (HIS) are essential in clinical practice as they provide healthcare professionals with access to accurate and timely information, enabling them to make informed decisions that enhance patient care. HIS facilitates the integration of data from various sources, offering a comprehensive view of patient health and improving care coordination among healthcare teams.

Knowledge of Types and Clinical and Administrative Uses of Health Information Systems Healthcare professionals must understand the different types of health information systems and their clinical and administrative applications. These systems include electronic health records (EHRs), which store patient data, and clinical decision support systems (CDSS), which assist in making evidence-based clinical decisions. Administrative uses include scheduling, billing, and resource management, which streamline operations and improve efficiency in healthcare settings.

Ensure Confidentiality of Protected Patient Health Information (PHI) Protecting the confidentiality of PHI is paramount in nursing informatics. This involves implementing safeguards such as encryption, access controls, and secure communication protocols to prevent unauthorized access to sensitive patient data.

Assure Access Control in the Use of Health Information Systems Access control mechanisms are crucial in maintaining the security and integrity of health information systems. These controls ensure that only authorized personnel can access specific data, thereby reducing the risk of data breaches and ensuring compliance with regulatory requirements.

Informatics: The Science and Art of Turning Data into Information Informatics involves the transformation of raw data into meaningful information that can be used to improve healthcare outcomes. This process requires both scientific knowledge and creative problem-solving skills to effectively manage and analyze data.

Nursing Informatics Nursing informatics is 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. It supports nurses, consumers, patients, the inter-professional healthcare team, and other stakeholders in their decision-making processes across all roles and settings to achieve desired outcomes.

• Two Levels of Nursing Informatics Practice:
  • Generalists: Nurses who use informatics tools in their daily practice to improve patient care.
  • Informatics-Nurse Specialists: Experts who focus on the development, implementation, and evaluation of informatics solutions within healthcare.

Knowledge in Nursing Informatics

Awareness and Understanding of Information Knowledge in nursing informatics involves awareness and understanding of information and how it can be used to support specific tasks or decisions. It is synthesized information that identifies and formalizes relationships, allowing healthcare professionals to make informed decisions.

Processed Information for Clarification and Action Knowledge is processed information that helps clarify or explain a particular aspect of our environment, providing a basis for action. It is often influenced by the assumptions and central theories of a scientific discipline and is derived from discovering patterns of relationships between different clusters of information. Knowledge answers the questions of “why” and “how.”

Data vs. Information

• Data: Uninterpreted items, often referred to as data elements. For example, a person’s weight is a data element. Without additional context, such as height, age, or overall health, the significance of this number is unclear.
• Information: A group of data elements that have been organized and processed so that one can interpret their significance. For instance, height, weight, age, and gender can be combined to calculate Body Mass Index (BMI), which helps determine if an individual is underweight, overweight, normal weight, or obese.

Building Knowledge Through Relationships Between Data and Information Knowledge is built on the formalization of the relationships and interrelationships between data and information. For example, understanding that an individual may have a BMI over 30 but is not necessarily obese requires integrating various data points and contextual information.

Automated Decision Support Systems and Knowledge Bases Many automated decision support systems include a knowledge base and a set of rules for applying that knowledge in specific situations. For example, a knowledge base might include information about the onset of fever, where a chill may precede an elevated temperature. A rule might state: “If a patient complains of chills, then take the patient’s temperature and repeat in 30 minutes,” guiding clinical actions based on established knowledge.

These principles and competencies in nursing informatics are critical for improving patient outcomes, ensuring data security, and enhancing the efficiency of healthcare systems.