Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User Interface for Intensive Care Unit Instability Decision Support.

Background: Critical instability forecast and treatment can be optimized by artificial intelligence (AI)-enabled clinical decision support. It is important that the user-facing display of AI output facilitates clinical thinking and workflow for all disciplines involved in bedside care.

Objectives: Our objective is to engage multidisciplinary users (physicians, nurse practitioners, physician assistants) in the development of a graphical user interface (GUI) to present an AI-derived risk score.

Strategies for success in a nursing PhD program and beyond.

Purpose: The purpose of this article is to inform newly enrolled PhD students of program expectations, strategies for success, and next steps in the career of a nurse scientist.

Methods: We used empirical evidence and insights from the authors to describe strategies for success during a nursing PhD program and continued career development following graduation.

Findings: Measures of success included maintaining health, focus, integrity, and a supportive network, identifying mentors, pursuing new knowledge and advancing research to transform health outcomes.

Engaging clinicians early during the development of a graphical user display of an intelligent alerting system at the bedside.

Background: Artificial Intelligence (AI) is increasingly used to support bedside clinical decisions, but information must be presented in usable ways within workflow. Graphical User Interfaces (GUI) are front-facing presentations for communicating AI outputs, but clinicians are not routinely invited to participate in their design, hindering AI solution potential.

Purpose: To inform early user-engaged design of a GUI prototype aimed at predicting future Cardiorespiratory Insufficiency (CRI) by exploring clinician methods for identifying at-risk patients, previous experience with implementing new technologies into clinical workflow, and user perspectives on GUI screen changes.

Intensive Care Unit Scoring Systems.

Background: Illness severity scoring systems are commonly used in critical care. When applied to the populations for whom they were developed and validated, these tools can facilitate mortality prediction and risk stratification, optimize resource use, and improve patient outcomes.

Objective: To describe the characteristics and applications of the scoring systems most frequently applied to critically ill patients.

Accuracy of identifying hospital acquired venous thromboembolism by administrative coding: implications for big data and machine learning research.

Big data analytics research using heterogeneous electronic health record (EHR) data requires accurate identification of disease phenotype cases and controls. Overreliance on ground truth determination based on administrative data can lead to biased and inaccurate findings. Hospital-acquired venous thromboembolism (HA-VTE) is challenging to identify due to its temporal evolution and variable EHR documentation.

A developmental trajectory supporting the evaluation and achievement of competencies: Articulating the Mastery Rubric for the nurse practitioner (MR-NP) program curriculum.

Background: Advanced practice registered nursing (APRN) competencies exist, but there is no structure supporting the operationalization of the competencies by APRN educators. The development of a Mastery Rubric (MR) for APRNs provides a developmental trajectory that supports educational institutions, educators, students, and APRNs. A MR describes the explicit knowledge, skills, and abilities as performed by the individual moving from novice (student) through graduation and into the APRN career.

A call to alarms: Current state and future directions in the battle against alarm fatigue.

Research demonstrates that the majority of alarms derived from continuous bedside monitoring devices are non-actionable. This avalanche of unreliable alerts causes clinicians to experience sensory overload when attempting to sort real from false alarms, causing desensitization and alarm fatigue, which in turn leads to adverse events when true instability is neither recognized nor attended to despite the alarm. The scope of the problem of alarm fatigue is broad, and its contributing mechanisms are numerous.