Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing.

Delirium is an acute decline or fluctuation in attention, awareness, or other cognitive function that can lead to serious adverse outcomes. Despite the severe outcomes, delirium is frequently unrecognized and uncoded in patients' electronic health records (EHRs) due to its transient and diverse nature. Natural language processing (NLP), a key technology that extracts medical concepts from clinical narratives, has shown great potential in studies of delirium outcomes and symptoms.

The use of artificial intelligence for graduate nursing education: An educational evaluation.

With artificial intelligence (AI) rapidly advancing, advanced practice nurses must understand and use it responsibly. Here, we describe an assignment in which Doctor of Nursing Practice (DNP) students learned to use generative text AI. Using our program and course outcomes, developed from the 2021 American Association of Colleges of Nursing (AACN) Essentials competency for DNP students to learn and use AI, we reviewed the literature seeking examples using ChatGPT for the DNP informatics course.

Unveiling Fall Risk Factors: Nurse-Driven Corpus Development for Natural Language Processing.

Hospital-acquired falls are a continuing clinical concern. The emergence of advanced analytical methods, including NLP, has created opportunities to leverage nurse-generated data, such as clinical notes, to better address the problem of falls. In this nurse-driven study, we employed an iterative process for expert manual annotation of RNs clinical notes to enable the training and testing of an NLP pipeline to extract factors related to falls.

Clinical Prediction Models for Hospital-Induced Delirium Using Structured and Unstructured Electronic Health Record Data: Protocol for a Development and Validation Study.

Background: Hospital-induced delirium is one of the most common and costly iatrogenic conditions, and its incidence is predicted to increase as the population of the United States ages. An academic and clinical interdisciplinary systems approach is needed to reduce the frequency and impact of hospital-induced delirium.

Objective: The long-term goal of our research is to enhance the safety of hospitalized older adults by reducing iatrogenic conditions through an effective learning health system.

The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review.

Objectives: Electronic health records (EHRs) user interfaces (UI) designed for data entry can potentially impact the quality of patient information captured in the EHRs. This review identified and synthesized the literature evidence about the relationship of UI features in EHRs on data quality (DQ).

Materials And Methods: We performed an integrative review of research studies by conducting a structured search in 5 databases completed on October 10, 2022.

Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium.

Background: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies, candidate predictors are selected on the basis of existing knowledge, including knowledge from clinical practice. The purpose of this article is to describe the process of identifying and operationalizing candidate predictors of hospital-induced delirium for application in a prediction model development study using a practice-based approach.

Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review.

Purpose: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units.

Methods: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction.

Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses' Graph Literacy: National, Web-Based Randomized Controlled Trial.

Background: The proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs.

Management of Fall Risk Among Older Adults in Diverse Primary Care Settings.

Objectives: Falls are persistent among community-dwelling older adults despite existing prevention guidelines. We described how urban and rural primary care staff and older adults manage fall risk and factors important to integration of computerized clinical decision support (CCDS).

Methods: Interviews, contextual inquiries, and workflow observations were analyzed using content analysis and synthesized into a journey map.

Usability Testing of an Interoperable Computerized Clinical Decision Support Tool for Fall Risk Management in Primary Care.

Background: Falls are a widespread and persistent problem for community-dwelling older adults. Use of fall prevention guidelines in the primary care setting has been suboptimal. Interoperable computerized clinical decision support systems have the potential to increase engagement with fall risk management at scale.

Fall risk management using clinical decision support in a rural nursing-led primary care practice.

Background: The leading cause of injuries among older adults in the United States is unintentional falls. The American Geriatrics Society/British Geriatrics Society promote fall risk management in primary care; however, this is challenging in low-resource settings.

Local Problem: Archer Family Health Care (AFHC), an Advanced Practice Registered Nurse (APRN)-managed and federally designated rural health clinic, identified a care gap with falls adherence to guidelines for patients at higher risk for falls.

Clinical Decision Support for Fall Prevention: Defining End-User Needs.

Background And Significance: Falls in community-dwelling older adults are common, and there is a lack of clinical decision support (CDS) to provide health care providers with effective, individualized fall prevention recommendations.

Objectives: The goal of this research is to identify end-user (primary care staff and patients) needs through a human-centered design process for a tool that will generate CDS to protect older adults from falls and injuries.

Methods: Primary care staff (primary care providers, care coordinator nurses, licensed practical nurses, and medical assistants) and community-dwelling patients aged 60 years or older associated with Brigham & Women's Hospital-affiliated primary care clinics and the University of Florida Health Archer Family Health Care primary care clinic were eligible to participate in this study.

Assessing the Usability of a Clinical Decision Support System: Heuristic Evaluation.

Background: Poor usability is a primary cause of unintended consequences related to the use of electronic health record (EHR) systems, which negatively impacts patient safety. Due to the cost and time needed to carry out iterative evaluations, many EHR components, such as clinical decision support systems (CDSSs), have not undergone rigorous usability testing prior to their deployment in clinical practice. Usability testing in the predeployment phase is crucial to eliminating usability issues and preventing costly fixes that will be needed if these issues are found after the system's implementation.

Conducting a representative national randomized control trial of tailored clinical decision support for nurses remotely: Methods and implications.

Clinical Decision Support (CDS) systems, patient specific evidence delivered to clinicians via the electronic health record (EHR) at the right time and in the right format, has the potential to improve patient outcomes. Unfortunately, outcomes of CDS research are mixed. A potential cause lies in its testing.

Spiritual Interventions Delivered by Nurses to Address Patients' Needs in Hospitals or Long-Term Care Facilities: A Systematic Review.

Despite increasing evidence of the benefits of spiritual care and nurses' efforts to incorporate spiritual interventions into palliative care and clinical practice, the role of spirituality is not well understood and implemented. There are divergent meanings and practices within and across countries. Understanding the delivery of spiritual interventions may lead to improved patient outcomes.

Nurses' Perceptions of Recommended Fall Prevention Strategies: A Rapid Review.

Background: Limited studies have synthesized evidence on nurses' perceptions of recommended fall prevention strategies and potential differences between those and the practiced strategies.

Purpose: To synthesize evidence about nurses' perceptions of recommended fall prevention strategies for hospitalized adults.

Methods: Using PubMed, 50 records underwent abstract and full-text screening, and 10 studies were retained.

Improving secure messaging: A framework for support, partnership & information-giving communicating electronically (SPICE).

Background: Patient-centered communication benefits patients and is widely endorsed. However, it is primarily associated with face-to-face contexts, although patients are increasingly using electronic platforms, such as secure messaging in patient portals, to communicate with providers.

Purpose: Given the popularity of secure messaging and its ability to impact the patient-provider relationship, this study aimed to determine which attributes of patient-centered communication are most desired by cancer patients using secure messaging.

Nutrition Support Therapies on the Medication Administration Record: Impacts on Staff Perception of Nutrition Care.

Background: It has been reported that many hospitals in the United States have fragmented and ineffective ordering, administration, documentation, and evaluation/monitoring of nutrition therapies. This paper reports on a project to investigate if perceived hospital staff awareness and documentation of nutrition support therapies (NSTs) improves by including them as part of the medication administration record (MAR).

Methods: Surveys were conducted with nursing staff, physicians, and dietitians before and after adding NSTs to the MAR to evaluate the perceived impact on the outcome of interest.

Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach.

Background: Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don't necessarily signal which factors are most important for predicting falls. Artificial intelligence (AI) methods provide an opportunity to improve predictive performance while also identifying the most important risk factors associated with hospital-acquired falls.

Fall Prevention Decision Making of Acute Care Registered Nurses.

Objective: The aim of this study was to examine acute care registered nurses' (RNs') fall prevention decision-making.

Background: The RN decision-making process related to fall prevention needs to be investigated to ensure that hospital policies align with nursing workflow and support nursing judgment.

Methods: Qualitative semistructured interviews based on the Critical Decision Method were conducted with RNs about their planning and decision making during their last 12-hour shift worked.

Patient Falls and Injuries in U.S. Psychiatric Care: Incidence and Trends.

Objective: The goal of this study was to estimate the incidence of falls (total, injurious, and assisted) in U.S. psychiatric care across 6 years (April 2013-March 2019).

Using an Electronic Medication Event-Monitoring System for Antiretroviral Therapy Self-Management Among African American Women Living With HIV in Rural Florida: Cohort Study.

Background: HIV remains a significant health issue in the United States and disproportionately affects African Americans. African American women living with HIV (AAWH) experience a particularly high number of barriers when attempting to manage their HIV care, including antiretroviral therapy (ART) adherence. To enable the development and assessment of effective interventions that address these barriers to support ART adherence, there is a critical need to understand more fully the use of objective measures of ART adherence among AAWH, including electronic medication dispensers for real-time surveillance.

Assessing Sexual Orientation and Gender Identity in Home Health Care: Perceptions and Attitudes of Nurses.

The purpose of this study was to explore home health care nurses' attitudes, perceptions, and experiences related to routine collection and documentation of sexual orientation and gender identity data. This was a qualitative descriptive study. Twenty-four nurses from a large home health care agency in the New York metropolitan area were interviewed between November 2014 and December 2015.

The Role of Nurse Managers in the Adoption of Health Information Technology: Findings From a Qualitative Study.

Objective: This study aims to investigate the role of nurse managers in supporting point-of-care nurses' health information technology (IT) use and identify strategies employed by nurse managers to improve adoption, while also gathering point-of-care nurses' perceptions of these strategies.

Background: Nurse managers are essential in facilitating point-of-care nurses' use of health IT; however, the underlying phenomenon for this facilitation remains unreported.

Methods: A qualitative descriptive study was conducted with 10 nurse managers and 14 point-of-care nurses recruited from a mental health hospital environment in Ontario, Canada.