Large Language Models for More Efficient Reporting of Hospital Quality Measures.

Hospital quality measures are a vital component of a learning health system, yet they can be costly to report, statistically underpowered, and inconsistent due to poor interrater reliability. Large language models (LLMs) have recently demonstrated impressive performance on health care-related tasks and offer a promising way to provide accurate abstraction of complete charts at scale. To evaluate this approach, we deployed an LLM-based system that ingests Fast Healthcare Interoperability Resources data and outputs a completed Severe Sepsis and Septic Shock Management Bundle (SEP-1) abstraction.

Insights From Art Therapists on Using AI-Generated Art in Art Therapy: Mixed Methods Study.

Background: With the increasing integration of artificial intelligence (AI) into various aspects of daily life, there is a growing interest among designers and practitioners in incorporating AI into their fields. In health care domains like art therapy, AI is also becoming a subject of exploration. However, the use of AI in art therapy is still undergoing investigation, with its benefits and challenges being actively explored.

Agile monitoring dashboard for clinical research studies.

Background: Clinical trial success hinges on efficient participant recruitment and retention. However, slow accrual and attrition frequently hinder progress. To address these challenges, a novel dashboard tool with control charts has been developed to provide investigators on the multi-site study of Delirium and Neuropsychological Recovery among Emergency General Surgery Survivors (DANE study) with timely information to improve trial recruitment.

Deprescribing anticholinergics to preserve brain health: reducing the risk of dementia through deprescribing (R2D2): study protocol for a randomized clinical trial.

Background: Older adults commonly experience chronic medical conditions and are at risk of cognitive impairment as a result of age, chronic comorbidity, and medications prescribed to manage multiple chronic conditions. Anticholinergic medications are common treatments for chronic conditions and have been repeatedly associated with poor cognitive outcomes, including delirium and dementia, in epidemiologic studies. However, no study has definitively evaluated the causal relationship between anticholinergics and cognition in a randomized controlled trial design.

World delirium awareness and quality survey in 2023-a worldwide point prevalence study.

Background: Delirium, an acute brain dysfunction, is proposed to be highly prevalent in clinical care and shown to significantly increase the risk of mortality and dementia.

Objectives: To report on the global prevalence of clinically documented delirium and delirium-related clinical practices in wards caring for paediatric and adult patients in healthcare facilities.

Design: A prospective, cross-sectional, 39-question survey completed on World Delirium Awareness Day, 15 March 2023.

Creating demand for unmet needs: Agile Storytelling.

Introduction: The translational gap from the discovery of evidence-based solutions to their implementation in healthcare delivery organizations derives from an incorrect assumption that the need for change among executive, administrative, or clinical personnel is the same as the demand for change. For sickle cell disease (SCD), implementation of evidence-based guidelines is often delayed or obstructed due to lack of demand. This challenge allows for the persistence of resource limitations and care delivery models that do not meet the community's unique needs.

Increased spending on low-value care during the COVID-19 pandemic in Virginia.

Characterizing the value and equity of care delivered during the COVID-19 pandemic is crucial to uncovering health system vulnerabilities and informing postpandemic recovery. We used insurance claims to evaluate low-value (no clinical benefit, potentially harmful) and clinically indicated utilization of a subset of 11 ambulatory services within a cohort of ∼2 million Virginia adults during the first 2 years of the pandemic (March 1, 2020-December 31, 2021). In 2020, low-value and clinically indicated utilization decreased similarly, while in 2021, low-value and clinically indicated utilization were 7% higher and 4% lower, respectively, than prepandemic rates.

Clinician and Visitor Activity Patterns in an Intensive Care Unit Room: A Study to Examine How Ambient Monitoring Can Inform the Measurement of Delirium Severity and Escalation of Care.

The early detection of the acute deterioration of escalating illness severity is crucial for effective patient management and can significantly impact patient outcomes. Ambient sensing technology, such as computer vision, may provide real-time information that could impact early recognition and response. This study aimed to develop a computer vision model to quantify the number and type (clinician vs.

Prevalence of Unrecognized Cognitive Impairment in Federally Qualified Health Centers.

Importance: There is a need for early and equitable detection of cognitive impairment among older adults.

Objective: To examine the prevalence of unrecognized cognitive impairment among older adults receiving primary care from federally qualified health centers (FQHCs).

Design, Setting, And Participants: This cross-sectional study was conducted at 5 FQHCs providing primary care in Indianapolis, Indiana, between 2021 and 2023.

Development and validation of a deep learning algorithm for the prediction of serum creatinine in critically ill patients.

Objectives: Serum creatinine (SCr) is the primary biomarker for assessing kidney function; however, it may lag behind true kidney function, especially in instances of acute kidney injury (AKI). The objective of the work is to develop Nephrocast, a deep-learning model to predict next-day SCr in adult patients treated in the intensive care unit (ICU).

Materials And Methods: Nephrocast was trained and validated, temporally and prospectively, using electronic health record data of adult patients admitted to the ICU in the University of California San Diego Health (UCSDH) between January 1, 2016 and June 22, 2024.

Equity in Digital Mental Health Interventions in the United States: Where to Next?

Health care technologies have the ability to bridge or hinder equitable care. Advocates of digital mental health interventions (DMHIs) report that such technologies are poised to reduce the documented gross health care inequities that have plagued generations of people seeking care in the United States. This is due to a multitude of factors such as their potential to revolutionize access; mitigate logistical barriers to in-person mental health care; and leverage patient inputs to formulate tailored, responsive, and personalized experiences.

The Feasibility of AgileNudge+ Software to Facilitate Positive Behavioral Change: Mixed Methods Design.

Background: In today's digital age, web-based apps have become integral to daily life, driving transformative shifts in human behavior. "AgileNudge+" (Indiana University Center for Health Innovation and Implementation Science) is a web-based solution to simplify the process of positive behavior change using nudging as an intervention. By integrating knowledge from behavioral economics with technology, AgileNudge+ organizes multiple steps, simplifies complex tasks, minimizes errors by enhancing user engagement, and provides resources for creating and testing nudge interventions.

Urgent call for compulsory premarital screening: a crucial step towards thalassemia prevention in Bangladesh.

Thalassemia poses a major public health concern in Bangladesh with a high prevalence of carriers. However, there is a substantial knowledge gap regarding its epidemiology, clinical aspects, and treatment outcomes. Despite its high prevalence, there is a notable lack of awareness regarding thalassemia in the Bangladeshi population.

Resistance and Co-Resistance of Metallo-Beta-Lactamase Genes in Diarrheal and Urinary-Tract Pathogens in Bangladesh.

Carbapenems are the antibiotics of choice for treating multidrug-resistant bacterial infections. Metallo-β-lactamases (MBLs) are carbapenemases capable of hydrolyzing nearly all therapeutically available beta-lactam antibiotics. Consequently, this research assessed the distribution of two MBL genes and three β-lactamases and their associated phenotypic resistance in diarrheal and urinary-tract infections (UTIs) to guide future policies.

Home based cardiac rehabilitation: A retrospective cohort analysis on all-cause mortality and hospital readmission rates across sexes and races.

Objective: Studies have shown that both home-based cardiac rehabilitation (HBCR) and center-based cardiac rehabilitation (CBCR) exhibit comparable efficacy in reducing mortality during short-term follow-up periods of up to 12 months. However, research on sex- and race-specific outcomes associated with HBCR is limited. This study examines all-cause mortality and hospital readmission among patients referred to HBCR, with stratification by sex and race.

Delirium in the United States: Results From the 2023 Cross-Sectional World Delirium Awareness Day Prevalence Study.

Background: Delirium is an acute brain dysfunction associated with an increased risk of mortality and future dementia.

Objectives: To describe the prevalence of clinically documented delirium in the United States on World Delirium Awareness Day 2023.

Methods: This is a sub-analysis of a prospective, cross-sectional, online, international survey.

Uncovering multi-level mental healthcare barriers for migrants: a qualitative analysis across China, Germany, Netherlands, Romania, and South Africa.

Background: Forced displacement is a significant issue globally, and it affected 112 million people in 2022. Many of these people have found refuge in low- and middle-income countries. Migrants and refugees face complex and specialized health challenges, particularly in the area of mental health.

Nursing science at Mayo Clinic: An alternative model to traditional hospital-based nurse scientist positions.

The role of the Nurse Scientist in clinical settings represents a relatively new career path that has garnered attention in recent literature. Although there is considerable variability in how this role is operationalized across institutions, Mayo Clinic stands out as one of the few health systems in the United States employing nurse scientists who are fully and exclusively engaged in their own programs of research. Given the need for practical information to guide development and implementation of a research-focused nurse scientist role, the purpose of this paper is to describe the infrastructure and resources supporting Mayo Clinic nurse scientists, share role expectations and metrics for success, discuss both the facilitators of success and ongoing challenges, and compare our current practices to those found in the literature.

The Role of Cooperative Extension in Delivering Training and Technical Assistance to Support Evidence-Based Behavioral Health Practices in Rural Communities.

The opioid epidemic in the United States continues to disproportionately affect those in rural, compared to urban, areas due to a variety of treatment and recovery barriers. One mechanism to increase capacity of rural-serving providers is through delivery of training and technical assistance (TTA) for evidence-based programs by leveraging the Cooperative Extension System. Guided by the Interactive Systems Framework, the current study evaluates TTA delivered by the Northwest Rural Opioid Technical Assistance Collabroative to opioid prevention, treatment, and recovery providers on short- (satisfaction, anticipated benefit), medium-, (behavioral intention to change current practice), and long-term goals (changes toward adoption of evidence-based practices).

Moral foundations in autistic people and people with systemizing minds.

Background: Do autistic people share the same moral foundations as typical people? Here we built on two prominent theories in psychology, moral foundations theory and the empathizing-systemizing (E-S) theory, to observe the nature of morality in autistic people and systemizers.

Methods: In dataset 1, we measured five foundations of moral judgements (Care, Fairness, Loyalty, Authority, and Sanctity) measured by the Moral Foundations Questionnaire (MFQ) in autistic (n = 307) and typical people (n = 415) along with their scores on the Empathy Quotient (EQ) and Systemizing Quotient (SQ). In dataset 2, we measured these same five foundations along with E-S cognitive types (previously referred to as "brain types") in a large sample of typical people (N = 7595).