Benner From Novice To Expert Pdf 4
Introduction Efforts to improve healthcare quality and safety have focused on developing technology designed to improve diagnostic accuracy, provide easier and more rapid access to patient information and more complete medical records (). Clinical decision support systems (CDSS) are one prominent example of this type of technology. However, development and implementation of these tools to assist health care providers in their clinical practice has lagged especially in nursing. A significant obstacle has been the identification of nursing information and knowledge. Differential use and manipulation of nursing information by nurses with differing nursing practice levels compound this obstacle. Thus, not all nurses recognize the same nursing data or information as pertinent to their clinical practice and knowledge. The aim of this paper is to explore how Novice-to-Expert Nursing Practice framework can illuminate the challenges of and opportunities for planning and implementing a clinical decision support system in nursing practice.
Furthermore, we will provide a descriptive overview of clinical decision support systems and discuss the concepts of both nursing knowledge and roles as they pertain to the use of such systems in nursing practice. Information technology in nursing practice: risk and reward There has been an increasing trend over the past decade in the use of information technology (IT) in clinical settings; however, there has also been mounting evidence that many of these systems are failing ().
Actual costs associated with these system failures are difficult to determine and have rarely been reported. One recommendation to determine costs is to calculate differences in intended and observed effects of implementation processes (). For example, the process of automation could be equated with the rising costs associated with increased clerical workload. In the nursing process, the elimination of existing processes or duplication could represent decreased costs. Several reasons can lead to failure or poor adoption of information technology in a health care setting.
Patricia Benner •Created a theory of how nurses acquire their knowledge and expertise. •Wrote the famous work From Novice to Expert in 1982 in the American Journal of nursing. A Collection of Readings Related to Competency-Based Training. EAE604 Curriculum and Competencies. 'Competence-Based Education and Training' (Tuxworth); 'From Novice to Expert' (Benner); 'Concept of Competence' (Jessup); 'Competency-Based. From novice to expert. Patricia Benner. The concept of competence.
Information systems failures have been attributed to ineffective ongoing communication, competency of users, intuitiveness of the system design, system acceptance and change management procedures (, ). According to a framework developed by, failure to adopt IT systems in health care settings can be linked to a combination of several factors including attributes of the individual end users (e.g. Computer anxiety, motivation), attributes of the technology (e.g. Usability, performance) and attributes of the clinical tasks and processes that the IT application introduces or affects (e.g. Task complexity). Failure of IT solutions is often also attributed to lack of communication between end users and designers (). Clinical decision support systems Clinical decision support systems (CDSS) are information systems that model and provide support for human decision-making processes in clinical situations ().
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CDSS use technology to support clinical decision making by interfacing evidenced-based clinical knowledge at the point of care with real-time clinical data at significant clinical decision points (,, ). CDSS enable clinician-computer interactions that move away from traditional data gathering roles to support clinicians as knowledge workers and information users (). Four classes of CDSS have been described in patient care decision making: systems that (1) use alerts to respond to clinical data, (2) respond to decisions to alter care by critiquing decisions, (3) suggest interventions at the request of a care providers, or (4) conduct retrospective quality assurance reviews. Many systems have been developed for a myriad of clinical issues in acute care settings including diagnosis of chest pain, ventilator management and to improve adherence to recognized HIV treatment guidelines (,,, ); however these are rarely nursing specific. Nursing-specific decision support systems include nursing diagnosis systems such as the Computer Aided Nursing Diagnosis and Intervention (CANDI) system (); care planning systems such as the Urological Nursing Information System (); symptom management systems such as the Cancer Pain Decision Support system () and nursing education systems such as the Creighton Online Multiple Modular Expert System (COMMES; ).